From 095e9dcf0c089e8ccb50107ebe34e0859d470b1e Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Sun, 16 Jun 2024 11:09:14 -0400 Subject: [PATCH 1/9] Adding data module to import truefx data --- SlopeMomentum.html | 61 +++++++++++++++++++++++++++++++++++++++++++++ fx_backtest/main.py | 6 +++-- poetry.lock | 25 +++++++++++++++++++ pyproject.toml | 2 +- 4 files changed, 91 insertions(+), 3 deletions(-) create mode 100644 SlopeMomentum.html diff --git a/SlopeMomentum.html b/SlopeMomentum.html new file mode 100644 index 0000000..5d31489 --- /dev/null +++ b/SlopeMomentum.html @@ -0,0 +1,61 @@ + + + + + SlopeMomentum.html + + + + + +
+ + + + + \ No newline at end of file diff --git a/fx_backtest/main.py b/fx_backtest/main.py index 1b57975..5da3fee 100644 --- a/fx_backtest/main.py +++ b/fx_backtest/main.py @@ -7,8 +7,10 @@ def calculate_stop_loss(cash, pair, price, risk=0.01): pass -with open("/home/kyle/Downloads/GBPUSD_M5.csv") as fh: - data = pd.read_csv(fh, delimiter="\t", parse_dates=["Time"]) +with open("/home/kyle/Tick_Data/ohlc/2024/January/GBPUSD-2024-01_5Min.csv") as fh: + data = pd.read_csv(fh, parse_dates=["Timestamp"]) + data.rename(columns={"open": "Open", "high": "High", "low": "Low", "close": "Close"}, inplace=True) + data = data.dropna() bt = Backtest( data, SlopeMomentum, commission=0.000, exclusive_orders=False, margin=0.02 diff --git a/poetry.lock b/poetry.lock index 98b8059..d07042d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -297,6 +297,26 @@ mccabe = ">=0.7.0,<0.8.0" pycodestyle = ">=2.11.0,<2.12.0" pyflakes = ">=3.2.0,<3.3.0" +[[package]] +name = "fx-lib" +version = "0.1.0" +description = "" +optional = false +python-versions = "^3.10" +files = [] +develop = true + +[package.dependencies] +backtesting = "^0.3.3" +numpy = "^1.26.4" +pandas = "^2.2.2" +pandas-stubs = "^2.2.2.240603" +pytest = "^8.1.1" + +[package.source] +type = "directory" +url = "../fx-lib" + [[package]] name = "fx-strategy" version = "0.1.0" @@ -306,6 +326,11 @@ python-versions = "^3.10" files = [] develop = true +[package.dependencies] +fx-lib = {path = "../fx-lib", develop = true} +pandas = "^2.2.2" +pandas-stubs = "^2.2.2.240603" + [package.source] type = "directory" url = "../fx-strategy" diff --git a/pyproject.toml b/pyproject.toml index 3dd9b86..9538ba1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,9 +7,9 @@ readme = "README.md" [tool.poetry.dependencies] python = "^3.10" -fx-strategy = {path = "../fx-strategy", develop = true} pandas-stubs = "^2.2.2.240603" backtesting = "^0.3.3" +fx-strategy = {path = "../fx-strategy", develop = true} [tool.poetry.group.dev.dependencies] From 1fe234f076df69d9928e40bd0245fb4696ee4b99 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Tue, 2 Jul 2024 19:35:17 -0400 Subject: [PATCH 2/9] Updating to build out bot init logic --- .flake8 | 8 +- =1.3 | 58 + ...rategy(_klass=SlopeMome\342\200\246).html" | 61 + BacktestStrategy.html | 61 + README.md | 120 + SlopeMomentum.html | 10 +- SmaCross(fast=4,slow=6).html | 61 + SmaCross.html | 61 + fx_backtest/__init__.py | 63 + fx_backtest/_exceptions.py | 2 + fx_backtest/_interfaces.py | 31 + fx_backtest/_models.py | 447 ++ fx_backtest/_plotting.py | 963 ++++ fx_backtest/_stats.py | 185 + fx_backtest/_util.py | 207 + fx_backtest/_version.py | 17 + fx_backtest/autoscale_cb.js | 35 + fx_backtest/backtesting.py | 1447 +++++ fx_backtest/lib.py | 558 ++ fx_backtest/main.py | 17 +- .bandit => fx_backtest/py.typed | 0 makefiles/local.mk | 2 +- poetry.lock | 134 +- pyproject.toml | 10 +- tests/unit/EURUSD.csv | 5001 +++++++++++++++++ tests/unit/GOOG.csv | 2149 +++++++ tests/unit/__init__.py | 28 + tests/unit/__main__.py | 7 + tests/unit/test_backtest.py | 1055 ++++ tests/unit/test_default.py | 2 - 30 files changed, 12723 insertions(+), 77 deletions(-) create mode 100644 =1.3 create mode 100644 "BacktestStrategy(_klass=SlopeMome\342\200\246).html" create mode 100644 BacktestStrategy.html create mode 100644 SmaCross(fast=4,slow=6).html create mode 100644 SmaCross.html create mode 100644 fx_backtest/_exceptions.py create mode 100644 fx_backtest/_interfaces.py create mode 100644 fx_backtest/_models.py create mode 100644 fx_backtest/_plotting.py create mode 100644 fx_backtest/_stats.py create mode 100644 fx_backtest/_util.py create mode 100644 fx_backtest/_version.py create mode 100644 fx_backtest/autoscale_cb.js create mode 100644 fx_backtest/backtesting.py create mode 100644 fx_backtest/lib.py rename .bandit => fx_backtest/py.typed (100%) create mode 100644 tests/unit/EURUSD.csv create mode 100644 tests/unit/GOOG.csv create mode 100644 tests/unit/__main__.py create mode 100644 tests/unit/test_backtest.py delete mode 100644 tests/unit/test_default.py diff --git a/.flake8 b/.flake8 index 79a16af..af263cd 100644 --- a/.flake8 +++ b/.flake8 @@ -1,2 +1,8 @@ [flake8] -max-line-length = 120 \ No newline at end of file +max-line-length = 120 +exclude = + .git, + .eggs, + __pycache__, + doc/examples +extend-ignore = E203, E701 \ No newline at end of file diff --git a/=1.3 b/=1.3 new file mode 100644 index 0000000..140f249 --- /dev/null +++ b/=1.3 @@ -0,0 +1,58 @@ +Using version ^0.11.0 for pdoc3 +Using version ^1.16.2 for jupytext +Using version ^7.16.4 for nbconvert +Using version ^6.29.4 for ipykernel +Using version ^8.6.2 for jupyter-client + +Updating dependencies +Resolving dependencies... + +Package operations: 45 installs, 0 updates, 0 removals + + - Installing attrs (23.2.0) + - Installing rpds-py (0.18.1) + - Installing referencing (0.35.1) + - Installing jsonschema-specifications (2023.12.1) + - Installing traitlets (5.14.3) + - Installing asttokens (2.4.1) + - Installing executing (2.0.1) + - Installing fastjsonschema (2.20.0) + - Installing jsonschema (4.22.0) + - Installing jupyter-core (5.7.2) + - Installing parso (0.8.4) + - Installing ptyprocess (0.7.0) + - Installing pure-eval (0.2.2) + - Installing pyzmq (26.0.3) + - Installing wcwidth (0.2.13) + - Installing decorator (5.1.1) + - Installing jedi (0.19.1) + - Installing jupyter-client (8.6.2) + - Installing matplotlib-inline (0.1.7) + - Installing nbformat (5.10.4) + - Installing pexpect (4.9.0) + - Installing prompt-toolkit (3.0.47) + - Installing soupsieve (2.5) + - Installing stack-data (0.6.3) + - Installing webencodings (0.5.1) + - Installing beautifulsoup4 (4.12.3) + - Installing bleach (6.1.0) + - Installing comm (0.2.2) + - Installing debugpy (1.8.1) + - Installing ipython (8.25.0) + - Installing jupyterlab-pygments (0.3.0) + - Installing defusedxml (0.7.1) + - Installing mako (1.3.5) + - Installing mistune (3.0.2) + - Installing nbclient (0.10.0) + - Installing markdown (3.6) + - Installing psutil (6.0.0) + - Installing nest-asyncio (1.6.0) + - Installing tinycss2 (1.3.0) + - Installing pandocfilters (1.5.1) + - Installing mdit-py-plugins (0.4.1) + - Installing ipykernel (6.29.4) + - Installing jupytext (1.16.2) + - Installing nbconvert (7.16.4) + - Installing pdoc3 (0.11.0) + +Writing lock file diff --git "a/BacktestStrategy(_klass=SlopeMome\342\200\246).html" "b/BacktestStrategy(_klass=SlopeMome\342\200\246).html" new file mode 100644 index 0000000..fa85df8 --- /dev/null +++ "b/BacktestStrategy(_klass=SlopeMome\342\200\246).html" @@ -0,0 +1,61 @@ + + + + + BacktestStrategy(_klass=SlopeMome…).html + + + + + +
+ + + + + \ No newline at end of file diff --git a/BacktestStrategy.html b/BacktestStrategy.html new file mode 100644 index 0000000..f2ad72f --- /dev/null +++ b/BacktestStrategy.html @@ -0,0 +1,61 @@ + + + + + BacktestStrategy(_klass=SlopeMome…).html + + + + + +
+ + + + + \ No newline at end of file diff --git a/README.md b/README.md index e69de29..bbbcd83 100644 --- a/README.md +++ b/README.md @@ -0,0 +1,120 @@ +[![](https://i.imgur.com/E8Kj69Y.png)](https://kernc.github.io/backtesting.py/) + +Backtesting.py +============== +[![Build Status](https://img.shields.io/github/actions/workflow/status/kernc/backtesting.py/ci.yml?branch=master&style=for-the-badge)](https://github.com/kernc/backtesting.py/actions) +[![Code Coverage](https://img.shields.io/codecov/c/gh/kernc/backtesting.py.svg?style=for-the-badge)](https://codecov.io/gh/kernc/backtesting.py) +[![Backtesting on PyPI](https://img.shields.io/pypi/v/backtesting.svg?color=blue&style=for-the-badge)](https://pypi.org/project/backtesting) +[![PyPI downloads](https://img.shields.io/pypi/dd/backtesting.svg?color=skyblue&style=for-the-badge)](https://pypi.org/project/backtesting) +[![GitHub Sponsors](https://img.shields.io/github/sponsors/kernc?color=pink&style=for-the-badge)](https://github.com/sponsors/kernc) + +Backtest trading strategies with Python. + +[**Project website**](https://kernc.github.io/backtesting.py) + [Documentation] + +[Documentation]: https://kernc.github.io/backtesting.py/doc/backtesting/ + + +Installation +------------ + + $ pip install backtesting + + +Usage +----- +```python +from backtesting import Backtest, Strategy +from backtesting.lib import crossover + +from backtesting.test import SMA, GOOG + + +class SmaCross(Strategy): + def init(self): + price = self.data.Close + self.ma1 = self.I(SMA, price, 10) + self.ma2 = self.I(SMA, price, 20) + + def next(self): + if crossover(self.ma1, self.ma2): + self.buy() + elif crossover(self.ma2, self.ma1): + self.sell() + + +bt = Backtest(GOOG, SmaCross, commission=.002, + exclusive_orders=True) +stats = bt.run() +bt.plot() +``` + +Results in: + +```text +Start 2004-08-19 00:00:00 +End 2013-03-01 00:00:00 +Duration 3116 days 00:00:00 +Exposure Time [%] 94.27 +Equity Final [$] 68935.12 +Equity Peak [$] 68991.22 +Return [%] 589.35 +Buy & Hold Return [%] 703.46 +Return (Ann.) [%] 25.42 +Volatility (Ann.) [%] 38.43 +Sharpe Ratio 0.66 +Sortino Ratio 1.30 +Calmar Ratio 0.77 +Max. Drawdown [%] -33.08 +Avg. Drawdown [%] -5.58 +Max. Drawdown Duration 688 days 00:00:00 +Avg. Drawdown Duration 41 days 00:00:00 +# Trades 93 +Win Rate [%] 53.76 +Best Trade [%] 57.12 +Worst Trade [%] -16.63 +Avg. Trade [%] 1.96 +Max. Trade Duration 121 days 00:00:00 +Avg. Trade Duration 32 days 00:00:00 +Profit Factor 2.13 +Expectancy [%] 6.91 +SQN 1.78 +Kelly Criterion 0.6134 +_strategy SmaCross(n1=10, n2=20) +_equity_curve Equ... +_trades Size EntryB... +dtype: object +``` +[![plot of trading simulation](https://i.imgur.com/xRFNHfg.png)](https://kernc.github.io/backtesting.py/#example) + +Find more usage examples in the [documentation]. + + +Features +-------- +* Simple, well-documented API +* Blazing fast execution +* Built-in optimizer +* Library of composable base strategies and utilities +* Indicator-library-agnostic +* Supports _any_ financial instrument with candlestick data +* Detailed results +* Interactive visualizations + +![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png) + + +Bugs +---- +Before reporting bugs or posting to the +[discussion board](https://github.com/kernc/backtesting.py/discussions), +please read [contributing guidelines](CONTRIBUTING.md), particularly the section +about crafting useful bug reports and ```` ``` ````-fencing your code. We thank you! + + +Alternatives +------------ +See [alternatives.md] for a list of alternative Python +backtesting frameworks and related packages. + +[alternatives.md]: https://github.com/kernc/backtesting.py/blob/master/doc/alternatives.md diff --git a/SlopeMomentum.html b/SlopeMomentum.html index 5d31489..3cad09c 100644 --- a/SlopeMomentum.html +++ b/SlopeMomentum.html @@ -18,10 +18,10 @@ -
+
- + + + +
+ + + + + \ No newline at end of file diff --git a/SmaCross.html b/SmaCross.html new file mode 100644 index 0000000..3c557b2 --- /dev/null +++ b/SmaCross.html @@ -0,0 +1,61 @@ + + + + + SmaCross.html + + + + + +
+ + + + + \ No newline at end of file diff --git a/fx_backtest/__init__.py b/fx_backtest/__init__.py index e69de29..79616eb 100644 --- a/fx_backtest/__init__.py +++ b/fx_backtest/__init__.py @@ -0,0 +1,63 @@ +""" + +![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png) + +## Manuals + +* [**Quick Start User Guide**](../examples/Quick Start User Guide.html) + +## Tutorials + +* [Library of Utilities and Composable Base Strategies](../examples/Strategies Library.html) +* [Multiple Time Frames](../examples/Multiple Time Frames.html) +* [**Parameter Heatmap & Optimization**](../examples/Parameter Heatmap & Optimization.html) +* [Trading with Machine Learning](../examples/Trading with Machine Learning.html) + +These tutorials are also available as live Jupyter notebooks: +[![Binder](https://mybinder.org/badge_logo.svg)][binder] +[![Google Colab](https://colab.research.google.com/assets/colab-badge.png)][colab] +
In Colab, you might have to `!pip install backtesting`. + +[binder]: \ + https://mybinder.org/v2/gh/kernc/backtesting.py/master?\ +urlpath=lab%2Ftree%2Fdoc%2Fexamples%2FQuick%20Start%20User%20Guide.ipynb +[colab]: https://colab.research.google.com/github/kernc/backtesting.py/ + +## Example Strategies + +* (contributions welcome) + + +.. tip:: + For an overview of recent changes, see + [What's New](https://github.com/kernc/backtesting.py/blob/master/CHANGELOG.md). + + +## FAQ + +Some answers to frequent and popular questions can be found on the +[issue tracker](https://github.com/kernc/backtesting.py/issues?q=label%3Aquestion+-label%3Ainvalid) +or on the [discussion forum](https://github.com/kernc/backtesting.py/discussions) on GitHub. +Please use the search! + +## License + +This software is licensed under the terms of [AGPL 3.0]{: rel=license}, +meaning you can use it for any reasonable purpose and remain in +complete ownership of all the excellent trading strategies you produce, +but you are also encouraged to make sure any upgrades to _Backtesting.py_ +itself find their way back to the community. + +[AGPL 3.0]: https://www.gnu.org/licenses/agpl-3.0.html + +# API Reference Documentation +""" + +try: + from ._version import version as __version__ +except ImportError: + __version__ = "?.?.?" # Package not installed + +from . import lib # noqa: F401 +from ._plotting import set_bokeh_output # noqa: F401 +from .backtesting import Backtest, Strategy # noqa: F401 diff --git a/fx_backtest/_exceptions.py b/fx_backtest/_exceptions.py new file mode 100644 index 0000000..25c70e6 --- /dev/null +++ b/fx_backtest/_exceptions.py @@ -0,0 +1,2 @@ +class _OutOfMoneyError(Exception): + pass \ No newline at end of file diff --git a/fx_backtest/_interfaces.py b/fx_backtest/_interfaces.py new file mode 100644 index 0000000..f8a2a0e --- /dev/null +++ b/fx_backtest/_interfaces.py @@ -0,0 +1,31 @@ +from abc import abstractmethod, ABCMeta +from typing import List, Optional +from fx_backtest._models import Trade, Order + +class IBroker(metaclass=ABCMeta): + + @property + @abstractmethod + def trades(self) -> List[Trade]: + raise NotImplementedError + + @property + @abstractmethod + def orders(self) -> List[Order]: + raise NotImplementedError + + @abstractmethod + def new_order( + self, + size: float, + limit: Optional[float] = None, + stop: Optional[float] = None, + sl: Optional[float] = None, + tp: Optional[float] = None, + tag: object = None, + *, + trade: Optional[Trade] = None, + ): + raise NotImplementedError() + + \ No newline at end of file diff --git a/fx_backtest/_models.py b/fx_backtest/_models.py new file mode 100644 index 0000000..cbffb2e --- /dev/null +++ b/fx_backtest/_models.py @@ -0,0 +1,447 @@ + +from copy import copy +from math import copysign +from typing import Optional, Union +import numpy as np +import pandas as pd + +from fx_backtest._interfaces import IBroker + +__pdoc__ = { + "Strategy.__init__": False, + "Order.__init__": False, + "Position.__init__": False, + "Trade.__init__": False, +} + +class Position: + """ + Currently held asset position, available as + `backtesting.backtesting.Strategy.position` within + `backtesting.backtesting.Strategy.next`. + Can be used in boolean contexts, e.g. + + if self.position: + ... # we have a position, either long or short + """ + + def __init__(self, broker: IBroker): + self.__broker = broker + + def __bool__(self): + return self.size != 0 + + @property + def size(self) -> float: + """Position size in units of asset. Negative if position is short.""" + return sum(trade.size for trade in self.__broker.trades) + + @property + def pl(self) -> float: + """Profit (positive) or loss (negative) of the current position in cash units.""" + return sum(trade.pl for trade in self.__broker.trades) + + @property + def pl_pct(self) -> float: + """Profit (positive) or loss (negative) of the current position in percent.""" + weights = np.abs([trade.size for trade in self.__broker.trades]) + weights = weights / weights.sum() + pl_pcts = np.array([trade.pl_pct for trade in self.__broker.trades]) + return (pl_pcts * weights).sum() + + @property + def is_long(self) -> bool: + """True if the position is long (position size is positive).""" + return self.size > 0 + + @property + def is_short(self) -> bool: + """True if the position is short (position size is negative).""" + return self.size < 0 + + def close(self, portion: float = 1.0): + """ + Close portion of position by closing `portion` of each active trade. See `Trade.close`. + """ + for trade in self.__broker.trades: + trade.close(portion) + + def __repr__(self): + return f"" + + +class Order: + """ + Place new orders through `Strategy.buy()` and `Strategy.sell()`. + Query existing orders through `Strategy.orders`. + + When an order is executed or [filled], it results in a `Trade`. + + If you wish to modify aspects of a placed but not yet filled order, + cancel it and place a new one instead. + + All placed orders are [Good 'Til Canceled]. + + [filled]: https://www.investopedia.com/terms/f/fill.asp + [Good 'Til Canceled]: https://www.investopedia.com/terms/g/gtc.asp + """ + + def __init__( + self, + broker: IBroker, + size: float, + limit_price: Optional[float] = None, + stop_price: Optional[float] = None, + sl_price: Optional[float] = None, + tp_price: Optional[float] = None, + parent_trade: Optional["Trade"] = None, + tag: object = None, + ): + self.__broker = broker + assert size != 0 + self.__size = size + self.__limit_price = limit_price + self.__stop_price = stop_price + self.__sl_price = sl_price + self.__tp_price = tp_price + self.__parent_trade = parent_trade + self.__tag = tag + + def _replace(self, **kwargs): + for k, v in kwargs.items(): + setattr(self, f"_{self.__class__.__qualname__}__{k}", v) + return self + + def __repr__(self): + return "".format( + ", ".join( + f"{param}={round(value, 5)}" + for param, value in ( + ("size", self.__size), + ("limit", self.__limit_price), + ("stop", self.__stop_price), + ("sl", self.__sl_price), + ("tp", self.__tp_price), + ("contingent", self.is_contingent), + ("tag", self.__tag), + ) + if value is not None + ) + ) + + def cancel(self): + """Cancel the order.""" + self.__broker.orders.remove(self) + trade = self.__parent_trade + if trade: + if self is trade._sl_order: + trade._replace(sl_order=None) + elif self is trade._tp_order: + trade._replace(tp_order=None) + else: + # XXX: https://github.com/kernc/backtesting.py/issues/251#issuecomment-835634984 ??? + assert False + + # Fields getters + + @property + def size(self) -> float: + """ + Order size (negative for short orders). + + If size is a value between 0 and 1, it is interpreted as a fraction of current + available liquidity (cash plus `Position.pl` minus used margin). + A value greater than or equal to 1 indicates an absolute number of units. + """ + return self.__size + + @property + def limit(self) -> Optional[float]: + """ + Order limit price for [limit orders], or None for [market orders], + which are filled at next available price. + + [limit orders]: https://www.investopedia.com/terms/l/limitorder.asp + [market orders]: https://www.investopedia.com/terms/m/marketorder.asp + """ + return self.__limit_price + + @property + def stop(self) -> Optional[float]: + """ + Order stop price for [stop-limit/stop-market][_] order, + otherwise None if no stop was set, or the stop price has already been hit. + + [_]: https://www.investopedia.com/terms/s/stoporder.asp + """ + return self.__stop_price + + @property + def sl(self) -> Optional[float]: + """ + A stop-loss price at which, if set, a new contingent stop-market order + will be placed upon the `Trade` following this order's execution. + See also `Trade.sl`. + """ + return self.__sl_price + + @property + def tp(self) -> Optional[float]: + """ + A take-profit price at which, if set, a new contingent limit order + will be placed upon the `Trade` following this order's execution. + See also `Trade.tp`. + """ + return self.__tp_price + + @property + def parent_trade(self): + return self.__parent_trade + + @property + def tag(self): + """ + Arbitrary value (such as a string) which, if set, enables tracking + of this order and the associated `Trade` (see `Trade.tag`). + """ + return self.__tag + + __pdoc__["Order.parent_trade"] = False + + # Extra properties + + @property + def is_long(self): + """True if the order is long (order size is positive).""" + return self.__size > 0 + + @property + def is_short(self): + """True if the order is short (order size is negative).""" + return self.__size < 0 + + @property + def is_contingent(self): + """ + True for [contingent] orders, i.e. [OCO] stop-loss and take-profit bracket orders + placed upon an active trade. Remaining contingent orders are canceled when + their parent `Trade` is closed. + + You can modify contingent orders through `Trade.sl` and `Trade.tp`. + + [contingent]: https://www.investopedia.com/terms/c/contingentorder.asp + [OCO]: https://www.investopedia.com/terms/o/oco.asp + """ + return bool(self.__parent_trade) + + +class Trade: + """ + When an `Order` is filled, it results in an active `Trade`. + Find active trades in `Strategy.trades` and closed, settled trades in `Strategy.closed_trades`. + """ + + def __init__( + self, broker: IBroker, size: int, entry_price: float, entry_bar, tag + ): + self.__broker = broker + self.__size = size + self.__entry_price = entry_price + self.__exit_price: Optional[float] = None + self.__entry_bar: int = entry_bar + self.__exit_bar: Optional[int] = None + self.__sl_order: Optional[Order] = None + self.__tp_order: Optional[Order] = None + self.__tag = tag + + def __repr__(self): + return ( + f'' + ) + + def _replace(self, **kwargs): + for k, v in kwargs.items(): + setattr(self, f"_{self.__class__.__qualname__}__{k}", v) + return self + + def _copy(self, **kwargs): + return copy(self)._replace(**kwargs) + + def close(self, portion: float = 1.0): + """Place new `Order` to close `portion` of the trade at next market price.""" + assert 0 < portion <= 1, "portion must be a fraction between 0 and 1" + size = copysign(max(1, round(abs(self.__size) * portion)), -self.__size) + order = Order(self.__broker, size, parent_trade=self, tag=self.__tag) + self.__broker.orders.insert(0, order) + + # Fields getters + + @property + def size(self): + """Trade size (volume; negative for short trades).""" + return self.__size + + @property + def entry_price(self) -> float: + """Trade entry price.""" + return self.__entry_price + + @property + def exit_price(self) -> Optional[float]: + """Trade exit price (or None if the trade is still active).""" + return self.__exit_price + + @property + def entry_bar(self) -> int: + """Candlestick bar index of when the trade was entered.""" + return self.__entry_bar + + @property + def exit_bar(self) -> Optional[int]: + """ + Candlestick bar index of when the trade was exited + (or None if the trade is still active). + """ + return self.__exit_bar + + @property + def tag(self): + """ + A tag value inherited from the `Order` that opened + this trade. + + This can be used to track trades and apply conditional + logic / subgroup analysis. + + See also `Order.tag`. + """ + return self.__tag + + @property + def _sl_order(self): + return self.__sl_order + + @property + def _tp_order(self): + return self.__tp_order + + # Extra properties + + @property + def entry_time(self) -> Union[pd.Timestamp, int]: + """Datetime of when the trade was entered.""" + return self.__broker._data.index[self.__entry_bar] + + @property + def exit_time(self) -> Optional[Union[pd.Timestamp, int]]: + """Datetime of when the trade was exited.""" + if self.__exit_bar is None: + return None + return self.__broker._data.index[self.__exit_bar] + + @property + def is_long(self): + """True if the trade is long (trade size is positive).""" + return self.__size > 0 + + @property + def is_short(self): + """True if the trade is short (trade size is negative).""" + return not self.is_long + + @property + def pl(self): + """Trade profit (positive) or loss (negative) in cash units.""" + price = self.__exit_price or self.__broker.last_price + return self.__size * (price - self.__entry_price) + + @property + def pl_pct(self): + """Trade profit (positive) or loss (negative) in percent.""" + price = self.__exit_price or self.__broker.last_price + return copysign(1, self.__size) * (price / self.__entry_price - 1) + + @property + def value(self): + """Trade total value in cash (volume × price).""" + price = self.__exit_price or self.__broker.last_price + return abs(self.__size) * price + + # SL/TP management API + + @property + def sl(self): + """ + Stop-loss price at which to close the trade. + + This variable is writable. By assigning it a new price value, + you create or modify the existing SL order. + By assigning it `None`, you cancel it. + """ + return self.__sl_order and self.__sl_order.stop + + @sl.setter + def sl(self, price: float): + self.__set_contingent("sl", price) + + @property + def tp(self): + """ + Take-profit price at which to close the trade. + + This property is writable. By assigning it a new price value, + you create or modify the existing TP order. + By assigning it `None`, you cancel it. + """ + return self.__tp_order and self.__tp_order.limit + + @tp.setter + def tp(self, price: float): + self.__set_contingent("tp", price) + + def __set_contingent(self, type, price): + assert type in ("sl", "tp") + assert price is None or 0 < price < np.inf + attr = f"_{self.__class__.__qualname__}__{type}_order" + order: Order = getattr(self, attr) + if order: + order.cancel() + if price: + kwargs = {"stop": price} if type == "sl" else {"limit": price} + order = self.__broker.new_order( + -self.size, trade=self, tag=self.tag, **kwargs + ) + setattr(self, attr, order) + +class _Orders(tuple): + """ + TODO: remove this class. Only for deprecation. + """ + + def cancel(self): + """Cancel all non-contingent (i.e. SL/TP) orders.""" + for order in self: + if not order.is_contingent: + order.cancel() + + def __getattr__(self, item): + # TODO: Warn on deprecations from the previous version. Remove in the next. + removed_attrs = ( + "entry", + "set_entry", + "is_long", + "is_short", + "sl", + "tp", + "set_sl", + "set_tp", + ) + if item in removed_attrs: + raise AttributeError( + f'Strategy.orders.{"/.".join(removed_attrs)} were removed in' + "Backtesting 0.2.0. " + "Use `Order` API instead. See docs." + ) + raise AttributeError(f"'tuple' object has no attribute {item!r}") \ No newline at end of file diff --git a/fx_backtest/_plotting.py b/fx_backtest/_plotting.py new file mode 100644 index 0000000..a933f69 --- /dev/null +++ b/fx_backtest/_plotting.py @@ -0,0 +1,963 @@ +import os +import re +import sys +import warnings +from colorsys import hls_to_rgb, rgb_to_hls +from functools import partial +from itertools import combinations, cycle +from typing import Callable, List, Union + +import numpy as np +import pandas as pd +from bokeh.colors import RGB +from bokeh.colors.named import lime as BULL_COLOR +from bokeh.colors.named import tomato as BEAR_COLOR +from bokeh.models import ( # type: ignore + ColumnDataSource, + CrosshairTool, + CustomJS, + DatetimeTickFormatter, + HoverTool, + LinearColorMapper, + NumeralTickFormatter, + Range1d, + Span, + WheelZoomTool, +) +from bokeh.plotting import figure as _figure + +try: + from bokeh.models import CustomJSTickFormatter +except ImportError: # Bokeh < 3.0 + from bokeh.models import FuncTickFormatter as CustomJSTickFormatter # type: ignore + +from backtesting._util import _as_list, _data_period, _Indicator +from bokeh.io import output_file, output_notebook, show +from bokeh.io.state import curstate +from bokeh.layouts import gridplot +from bokeh.palettes import Category10 +from bokeh.transform import factor_cmap + +with open( + os.path.join(os.path.dirname(__file__), "autoscale_cb.js"), encoding="utf-8" +) as _f: + _AUTOSCALE_JS_CALLBACK = _f.read() + +IS_JUPYTER_NOTEBOOK = "JPY_PARENT_PID" in os.environ + +if IS_JUPYTER_NOTEBOOK: + warnings.warn( + "Jupyter Notebook detected. " + "Setting Bokeh output to notebook. " + "This may not work in Jupyter clients without JavaScript " + "support (e.g. PyCharm, Spyder IDE). " + "Reset with `backtesting.set_bokeh_output(notebook=False)`." + ) + output_notebook() + + +def set_bokeh_output(notebook=False): + """ + Set Bokeh to output either to a file or Jupyter notebook. + By default, Bokeh outputs to notebook if running from within + notebook was detected. + """ + global IS_JUPYTER_NOTEBOOK + IS_JUPYTER_NOTEBOOK = notebook + + +def _windos_safe_filename(filename): + if sys.platform.startswith("win"): + return re.sub(r"[^a-zA-Z0-9,_-]", "_", filename.replace("=", "-")) + return filename + + +def _bokeh_reset(filename=None): + curstate().reset() + if filename: + if not filename.endswith(".html"): + filename += ".html" + output_file(filename, title=filename) + elif IS_JUPYTER_NOTEBOOK: + curstate().output_notebook() + + +def colorgen(): + yield from cycle(Category10[10]) + + +def lightness(color, lightness=0.94): + rgb = np.array([color.r, color.g, color.b]) / 255 + h, _, s = rgb_to_hls(*rgb) + rgb = np.array(hls_to_rgb(h, lightness, s)) * 255.0 + return RGB(*rgb) + + +_MAX_CANDLES = 10_000 + + +def _maybe_resample_data(resample_rule, df, indicators, equity_data, trades): + if isinstance(resample_rule, str): + freq = resample_rule + else: + if resample_rule is False or len(df) <= _MAX_CANDLES: + return df, indicators, equity_data, trades + + freq_minutes = pd.Series( + { + "1T": 1, + "5T": 5, + "10T": 10, + "15T": 15, + "30T": 30, + "1H": 60, + "2H": 60 * 2, + "4H": 60 * 4, + "8H": 60 * 8, + "1D": 60 * 24, + "1W": 60 * 24 * 7, + "1M": np.inf, + } + ) + timespan = df.index[-1] - df.index[0] + require_minutes = (timespan / _MAX_CANDLES).total_seconds() // 60 + freq = freq_minutes.where(freq_minutes >= require_minutes).first_valid_index() + warnings.warn( + f"Data contains too many candlesticks to plot; downsampling to {freq!r}. " + "See `Backtest.plot(resample=...)`" + ) + + from .lib import _EQUITY_AGG, OHLCV_AGG, TRADES_AGG + + df = df.resample(freq, label="right").agg(OHLCV_AGG).dropna() + + indicators = [ + _Indicator( + i.df.resample(freq, label="right") + .mean() + .dropna() + .reindex(df.index) + .values.T, + **dict( + i._opts, + name=i.name, + # Replace saved index with the resampled one + index=df.index, + ), + ) + for i in indicators + ] + assert not indicators or indicators[0].df.index.equals(df.index) + + equity_data = ( + equity_data.resample(freq, label="right").agg(_EQUITY_AGG).dropna(how="all") + ) + assert equity_data.index.equals(df.index) + + def _weighted_returns(s, trades=trades): + df = trades.loc[s.index] + return ((df["Size"].abs() * df["ReturnPct"]) / df["Size"].abs().sum()).sum() + + def _group_trades(column): + def f(s, new_index=pd.Index(df.index.view(int)), bars=trades[column]): + if s.size: + # Via int64 because on pandas recently broken datetime + mean_time = int(bars.loc[s.index].view(int).mean()) + new_bar_idx = new_index.get_indexer([mean_time], method="nearest")[0] + return new_bar_idx + + return f + + if len(trades): # Avoid pandas "resampling on Int64 index" error + trades = ( + trades.assign(count=1) + .resample(freq, on="ExitTime", label="right") + .agg( + dict( + TRADES_AGG, + ReturnPct=_weighted_returns, + count="sum", + EntryBar=_group_trades("EntryTime"), + ExitBar=_group_trades("ExitTime"), + ) + ) + .dropna() + ) + + return df, indicators, equity_data, trades + + +def plot( + *, + results: pd.Series, + df: pd.DataFrame, + indicators: List[_Indicator], + filename="", + plot_width=None, + plot_equity=True, + plot_return=False, + plot_pl=True, + plot_volume=True, + plot_drawdown=False, + plot_trades=True, + smooth_equity=False, + relative_equity=True, + superimpose=True, + resample=True, + reverse_indicators=True, + show_legend=True, + open_browser=True, +): + """ + Like much of GUI code everywhere, this is a mess. + """ + # We need to reset global Bokeh state, otherwise subsequent runs of + # plot() contain some previous run's cruft data (was noticed when + # TestPlot.test_file_size() test was failing). + if not filename and not IS_JUPYTER_NOTEBOOK: + filename = _windos_safe_filename(str(results._strategy)) + _bokeh_reset(filename) + + COLORS = [BEAR_COLOR, BULL_COLOR] + BAR_WIDTH = 0.8 + + assert df.index.equals(results["_equity_curve"].index) + equity_data = results["_equity_curve"].copy(deep=False) + trades = results["_trades"] + + plot_volume = plot_volume and not df.Volume.isnull().all() + plot_equity = plot_equity and not trades.empty + plot_return = plot_return and not trades.empty + plot_pl = plot_pl and not trades.empty + is_datetime_index = isinstance(df.index, pd.DatetimeIndex) + + from .lib import OHLCV_AGG + + # ohlc df may contain many columns. We're only interested in, and pass on to Bokeh, these + df = df[list(OHLCV_AGG.keys())].copy(deep=False) + + # Limit data to max_candles + if is_datetime_index: + df, indicators, equity_data, trades = _maybe_resample_data( + resample, df, indicators, equity_data, trades + ) + + df.index.name = None # Provides source name @index + df["datetime"] = df.index # Save original, maybe datetime index + df = df.reset_index(drop=True) + equity_data = equity_data.reset_index(drop=True) + index = df.index + + new_bokeh_figure = partial( + _figure, + x_axis_type="linear", + width=plot_width, + height=400, + tools="xpan,xwheel_zoom,box_zoom,undo,redo,reset,save", + active_drag="xpan", + active_scroll="xwheel_zoom", + ) + + pad = (index[-1] - index[0]) / 20 + + _kwargs = ( + dict( + x_range=Range1d( + index[0], + index[-1], + min_interval=10, + bounds=(index[0] - pad, index[-1] + pad), + ) + ) + if index.size > 1 + else {} + ) + fig_ohlc = new_bokeh_figure(**_kwargs) + figs_above_ohlc, figs_below_ohlc = [], [] + + source = ColumnDataSource(df) + source.add((df.Close >= df.Open).values.astype(np.uint8).astype(str), "inc") + + trade_source = ColumnDataSource( + dict( + index=trades["ExitBar"], + datetime=trades["ExitTime"], + exit_price=trades["ExitPrice"], + size=trades["Size"], + tp=trades["TakeProfit"], + sl=trades["StopLoss"], + returns_positive=(trades["ReturnPct"] > 0).astype(int).astype(str), + ) + ) + + inc_cmap = factor_cmap("inc", COLORS, ["0", "1"]) + cmap = factor_cmap("returns_positive", COLORS, ["0", "1"]) + colors_darker = [lightness(BEAR_COLOR, 0.35), lightness(BULL_COLOR, 0.35)] + trades_cmap = factor_cmap("returns_positive", colors_darker, ["0", "1"]) + + if is_datetime_index: + fig_ohlc.xaxis.formatter = CustomJSTickFormatter( + args=dict( + axis=fig_ohlc.xaxis[0], + formatter=DatetimeTickFormatter(days="%a, %d %b", months="%m/%Y"), + source=source, + ), + code=""" +this.labels = this.labels || formatter.doFormat(ticks + .map(i => source.data.datetime[i]) + .filter(t => t !== undefined)); +return this.labels[index] || ""; + """, + ) + + NBSP = "\N{NBSP}" * 4 # noqa: E999 + ohlc_extreme_values = df[["High", "Low"]].copy(deep=False) + ohlc_tooltips = [ + ("x, y", NBSP.join(("$index", "$y{0,0.0[0000]}"))), + ( + "OHLC", + NBSP.join( + ( + "@Open{0,0.0[0000]}", + "@High{0,0.0[0000]}", + "@Low{0,0.0[0000]}", + "@Close{0,0.0[0000]}", + ) + ), + ), + ("Volume", "@Volume{0,0}"), + ] + + def new_indicator_figure(**kwargs): + kwargs.setdefault("height", 90) + fig = new_bokeh_figure( + x_range=fig_ohlc.x_range, + active_scroll="xwheel_zoom", + active_drag="xpan", + **kwargs, + ) + fig.xaxis.visible = False + fig.yaxis.minor_tick_line_color = None + return fig + + def set_tooltips(fig, tooltips=(), vline=True, renderers=()): + tooltips = list(tooltips) + renderers = list(renderers) + + if is_datetime_index: + formatters = {"@datetime": "datetime"} + tooltips = [("Date", "@datetime{%c}")] + tooltips + else: + formatters = {} + tooltips = [("#", "@index")] + tooltips + fig.add_tools( + HoverTool( + point_policy="follow_mouse", + renderers=renderers, + formatters=formatters, + tooltips=tooltips, + mode="vline" if vline else "mouse", + ) + ) + + def _plot_equity_section(is_return=False): + """Equity section""" + # Max DD Dur. line + equity = equity_data["Equity"].copy() + dd_end = equity_data["DrawdownDuration"].idxmax() + if np.isnan(dd_end): + dd_start = dd_end = equity.index[0] + else: + dd_start = equity[:dd_end].idxmax() + # If DD not extending into the future, get exact point of intersection with equity + if dd_end != equity.index[-1]: + dd_end = np.interp( + equity[dd_start], + (equity[dd_end - 1], equity[dd_end]), + (dd_end - 1, dd_end), + ) + + if smooth_equity: + interest_points = pd.Index( + [ + # Beginning and end + equity.index[0], + equity.index[-1], + # Peak equity and peak DD + equity.idxmax(), + equity_data["DrawdownPct"].idxmax(), + # Include max dd end points. Otherwise the MaxDD line looks amiss. + dd_start, + int(dd_end), + min(int(dd_end + 1), equity.size - 1), + ] + ) + select = pd.Index(trades["ExitBar"]).union(interest_points) + select = select.unique().dropna() + equity = equity.iloc[select].reindex(equity.index) + equity.interpolate(inplace=True) + + assert equity.index.equals(equity_data.index) + + if relative_equity: + equity /= equity.iloc[0] + if is_return: + equity -= equity.iloc[0] + + yaxis_label = "Return" if is_return else "Equity" + source_key = "eq_return" if is_return else "equity" + source.add(equity, source_key) + fig = new_indicator_figure( + y_axis_label=yaxis_label, **({} if plot_drawdown else dict(height=110)) + ) + + # High-watermark drawdown dents + fig.patch( + "index", + "equity_dd", + source=ColumnDataSource( + dict( + index=np.r_[index, index[::-1]], + equity_dd=np.r_[equity, equity.cummax()[::-1]], + ) + ), + fill_color="#ffffea", + line_color="#ffcb66", + ) + + # Equity line + r = fig.line("index", source_key, source=source, line_width=1.5, line_alpha=1) + if relative_equity: + tooltip_format = f"@{source_key}{{+0,0.[000]%}}" + tick_format = "0,0.[00]%" + legend_format = "{:,.0f}%" + else: + tooltip_format = f"@{source_key}{{$ 0,0}}" + tick_format = "$ 0.0 a" + legend_format = "${:,.0f}" + set_tooltips(fig, [(yaxis_label, tooltip_format)], renderers=[r]) + fig.yaxis.formatter = NumeralTickFormatter(format=tick_format) + + # Peaks + argmax = equity.idxmax() + fig.scatter( + argmax, + equity[argmax], + legend_label="Peak ({})".format( + legend_format.format(equity[argmax] * (100 if relative_equity else 1)) + ), + color="cyan", + size=8, + ) + fig.scatter( + index[-1], + equity.values[-1], + legend_label="Final ({})".format( + legend_format.format(equity.iloc[-1] * (100 if relative_equity else 1)) + ), + color="blue", + size=8, + ) + + if not plot_drawdown: + drawdown = equity_data["DrawdownPct"] + argmax = drawdown.idxmax() + fig.scatter( + argmax, + equity[argmax], + legend_label="Max Drawdown (-{:.1f}%)".format(100 * drawdown[argmax]), + color="red", + size=8, + ) + dd_timedelta_label = ( + df["datetime"].iloc[int(round(dd_end))] - df["datetime"].iloc[dd_start] + ) + fig.line( + [dd_start, dd_end], + equity.iloc[dd_start], + line_color="red", + line_width=2, + legend_label=f"Max Dd Dur. ({dd_timedelta_label})".replace( + " 00:00:00", "" + ).replace("(0 days ", "("), + ) + + figs_above_ohlc.append(fig) + + def _plot_drawdown_section(): + """Drawdown section""" + fig = new_indicator_figure(y_axis_label="Drawdown") + drawdown = equity_data["DrawdownPct"] + argmax = drawdown.idxmax() + source.add(drawdown, "drawdown") + r = fig.line("index", "drawdown", source=source, line_width=1.3) + fig.scatter( + argmax, + drawdown[argmax], + legend_label="Peak (-{:.1f}%)".format(100 * drawdown[argmax]), + color="red", + size=8, + ) + set_tooltips(fig, [("Drawdown", "@drawdown{-0.[0]%}")], renderers=[r]) + fig.yaxis.formatter = NumeralTickFormatter(format="-0.[0]%") + return fig + + def _plot_pl_section(): + """Profit/Loss markers section""" + fig = new_indicator_figure(y_axis_label="Profit / Loss") + fig.add_layout( + Span( + location=0, + dimension="width", + line_color="#666666", + line_dash="dashed", + line_width=1, + ) + ) + returns_long = np.where(trades["Size"] > 0, trades["ReturnPct"], np.nan) + returns_short = np.where(trades["Size"] < 0, trades["ReturnPct"], np.nan) + size = trades["Size"].abs() + size = np.interp(size, (size.min(), size.max()), (8, 20)) + trade_source.add(returns_long, "returns_long") + trade_source.add(returns_short, "returns_short") + trade_source.add(size, "marker_size") + # if 'TakeProfit' in trades: + # trade_source.add(trades['TakeProfit'], 'tp') + # if 'StopLoss' in trades: + # trade_source.add(trades['StopLoss'], 'sl') + if "count" in trades: + trade_source.add(trades["count"], "count") + r1 = fig.scatter( + "index", + "returns_long", + source=trade_source, + fill_color=cmap, + marker="triangle", + line_color="black", + size="marker_size", + ) + r2 = fig.scatter( + "index", + "returns_short", + source=trade_source, + fill_color=cmap, + marker="inverted_triangle", + line_color="black", + size="marker_size", + ) + tooltips = [("Size", "@size{0,0}")] + + if "TakeProfit" in trades: + tooltips.append(("TP", "@tp")) + if "StopLoss" in trades: + tooltips.append(("SL", "@sl")) + if "count" in trades: + tooltips.append(("Count", "@count{0,0}")) + set_tooltips( + fig, + tooltips + [("P/L", "@returns_long{+0.[000]%}")], + vline=False, + renderers=[r1], + ) + set_tooltips( + fig, + tooltips + [("P/L", "@returns_short{+0.[000]%}")], + vline=False, + renderers=[r2], + ) + fig.yaxis.formatter = NumeralTickFormatter(format="0.[00]%") + return fig + + def _plot_volume_section(): + """Volume section""" + fig = new_indicator_figure(y_axis_label="Volume") + fig.xaxis.formatter = fig_ohlc.xaxis[0].formatter + fig.xaxis.visible = True + fig_ohlc.xaxis.visible = False # Show only Volume's xaxis + r = fig.vbar("index", BAR_WIDTH, "Volume", source=source, color=inc_cmap) + set_tooltips(fig, [("Volume", "@Volume{0.00 a}")], renderers=[r]) + fig.yaxis.formatter = NumeralTickFormatter(format="0 a") + return fig + + def _plot_superimposed_ohlc(): + """Superimposed, downsampled vbars""" + time_resolution = pd.DatetimeIndex(df["datetime"]).resolution + resample_rule = ( + superimpose + if isinstance(superimpose, str) + else dict(day="M", hour="D", minute="H", second="T", millisecond="S").get( + time_resolution + ) + ) + if not resample_rule: + warnings.warn( + f"'Can't superimpose OHLC data with rule '{resample_rule}'" + f"(index datetime resolution: '{time_resolution}'). Skipping.", + stacklevel=4, + ) + return + + df2 = ( + df.assign(_width=1) + .set_index("datetime") + .resample(resample_rule, label="left") + .agg(dict(OHLCV_AGG, _width="count")) + ) + + # Check if resampling was downsampling; error on upsampling + orig_freq = _data_period(df["datetime"]) + resample_freq = _data_period(df2.index) + if resample_freq < orig_freq: + raise ValueError( + "Invalid value for `superimpose`: Upsampling not supported." + ) + if resample_freq == orig_freq: + warnings.warn( + "Superimposed OHLC plot matches the original plot. Skipping.", + stacklevel=4, + ) + return + + df2.index = df2["_width"].cumsum().shift(1).fillna(0) + df2.index += df2["_width"] / 2 - 0.5 + df2["_width"] -= 0.1 # Candles don't touch + + df2["inc"] = (df2.Close >= df2.Open).astype(int).astype(str) + df2.index.name = None + source2 = ColumnDataSource(df2) + fig_ohlc.segment( + "index", "High", "index", "Low", source=source2, color="#bbbbbb" + ) + colors_lighter = [lightness(BEAR_COLOR, 0.92), lightness(BULL_COLOR, 0.92)] + fig_ohlc.vbar( + "index", + "_width", + "Open", + "Close", + source=source2, + line_color=None, + fill_color=factor_cmap("inc", colors_lighter, ["0", "1"]), + ) + + def _plot_ohlc(): + """Main OHLC bars""" + fig_ohlc.segment("index", "High", "index", "Low", source=source, color="black") + r = fig_ohlc.vbar( + "index", + BAR_WIDTH, + "Open", + "Close", + source=source, + line_color="black", + fill_color=inc_cmap, + ) + return r + + def _plot_ohlc_trades(): + """Trade entry / exit markers on OHLC plot""" + trade_source.add( + trades[["EntryBar", "ExitBar"]].values.tolist(), "position_lines_xs" + ) + trade_source.add( + trades[["EntryPrice", "ExitPrice"]].values.tolist(), "position_lines_ys" + ) + fig_ohlc.multi_line( + xs="position_lines_xs", + ys="position_lines_ys", + source=trade_source, + line_color=trades_cmap, + legend_label=f"Trades ({len(trades)})", + line_width=8, + line_alpha=1, + line_dash="dotted", + ) + + def _plot_indicators(): + """Strategy indicators""" + + def _too_many_dims(value): + assert value.ndim >= 2 + if value.ndim > 2: + warnings.warn( + f"Can't plot indicators with >2D ('{value.name}')", stacklevel=5 + ) + return True + return False + + class LegendStr(str): + # The legend string is such a string that only matches + # itself if it's the exact same object. This ensures + # legend items are listed separately even when they have the + # same string contents. Otherwise, Bokeh would always consider + # equal strings as one and the same legend item. + def __eq__(self, other): + return self is other + + ohlc_colors = colorgen() + indicator_figs = [] + + for i, value in enumerate(indicators): + value = np.atleast_2d(value) + + # Use .get()! A user might have assigned a Strategy.data-evolved + # _Array without Strategy.I() + if not value._opts.get("plot") or _too_many_dims(value): + continue + + is_overlay = value._opts["overlay"] + is_scatter = value._opts["scatter"] + if is_overlay: + fig = fig_ohlc + else: + fig = new_indicator_figure() + indicator_figs.append(fig) + tooltips = [] + colors = value._opts["color"] + colors = ( + colors + and cycle(_as_list(colors)) + or (cycle([next(ohlc_colors)]) if is_overlay else colorgen()) + ) + legend_label = LegendStr(value.name) + for j, arr in enumerate(value, 1): + color = next(colors) + source_name = f"{legend_label}_{i}_{j}" + if arr.dtype == bool: + arr = arr.astype(int) + source.add(arr, source_name) + tooltips.append(f"@{{{source_name}}}{{0,0.0[0000]}}") + if is_overlay: + ohlc_extreme_values[source_name] = arr + if is_scatter: + fig.scatter( + "index", + source_name, + source=source, + legend_label=legend_label, + color=color, + line_color="black", + fill_alpha=0.8, + marker="circle", + radius=BAR_WIDTH / 2 * 1.5, + ) + else: + fig.line( + "index", + source_name, + source=source, + legend_label=legend_label, + line_color=color, + line_width=1.3, + ) + else: + if is_scatter: + r = fig.scatter( + "index", + source_name, + source=source, + legend_label=LegendStr(legend_label), + color=color, + marker="circle", + radius=BAR_WIDTH / 2 * 0.9, + ) + else: + r = fig.line( + "index", + source_name, + source=source, + legend_label=LegendStr(legend_label), + line_color=color, + line_width=1.3, + ) + # Add dashed centerline just because + mean = float(pd.Series(arr).mean()) + if not np.isnan(mean) and ( + abs(mean) < 0.1 + or round(abs(mean), 1) == 0.5 + or round(abs(mean), -1) in (50, 100, 200) + ): + fig.add_layout( + Span( + location=float(mean), + dimension="width", + line_color="#666666", + line_dash="dashed", + line_width=0.5, + ) + ) + if is_overlay: + ohlc_tooltips.append((legend_label, NBSP.join(tooltips))) + else: + set_tooltips( + fig, + [(legend_label, NBSP.join(tooltips))], + vline=True, + renderers=[r], + ) + # If the sole indicator line on this figure, + # have the legend only contain text without the glyph + if len(value) == 1: + fig.legend.glyph_width = 0 + return indicator_figs + + # Construct figure ... + + if plot_equity: + _plot_equity_section() + + if plot_return: + _plot_equity_section(is_return=True) + + if plot_drawdown: + figs_above_ohlc.append(_plot_drawdown_section()) + + if plot_pl: + figs_above_ohlc.append(_plot_pl_section()) + + if plot_volume: + fig_volume = _plot_volume_section() + figs_below_ohlc.append(fig_volume) + + if superimpose and is_datetime_index: + _plot_superimposed_ohlc() + + ohlc_bars = _plot_ohlc() + if plot_trades: + _plot_ohlc_trades() + indicator_figs = _plot_indicators() + if reverse_indicators: + indicator_figs = indicator_figs[::-1] + figs_below_ohlc.extend(indicator_figs) + + set_tooltips(fig_ohlc, ohlc_tooltips, vline=True, renderers=[ohlc_bars]) + + source.add(ohlc_extreme_values.min(1), "ohlc_low") + source.add(ohlc_extreme_values.max(1), "ohlc_high") + + custom_js_args = dict(ohlc_range=fig_ohlc.y_range, source=source) + if plot_volume: + custom_js_args.update(volume_range=fig_volume.y_range) + + fig_ohlc.x_range.js_on_change( + "end", + CustomJS(args=custom_js_args, code=_AUTOSCALE_JS_CALLBACK), # type: ignore + ) + + plots = figs_above_ohlc + [fig_ohlc] + figs_below_ohlc + linked_crosshair = CrosshairTool(dimensions="both") + + for f in plots: + if f.legend: + f.legend.visible = show_legend + f.legend.location = "top_left" + f.legend.border_line_width = 1 + f.legend.border_line_color = "#333333" + f.legend.padding = 5 + f.legend.spacing = 0 + f.legend.margin = 0 + f.legend.label_text_font_size = "8pt" + f.legend.click_policy = "hide" + f.min_border_left = 0 + f.min_border_top = 3 + f.min_border_bottom = 6 + f.min_border_right = 10 + f.outline_line_color = "#666666" + + f.add_tools(linked_crosshair) + wheelzoom_tool = next(wz for wz in f.tools if isinstance(wz, WheelZoomTool)) + wheelzoom_tool.maintain_focus = False # type: ignore + + kwargs = {} + if plot_width is None: + kwargs["sizing_mode"] = "stretch_width" + + fig = gridplot( + plots, + ncols=1, + toolbar_location="right", + toolbar_options=dict(logo=None), + merge_tools=True, + **kwargs, # type: ignore + ) + show(fig, browser=None if open_browser else "none") + return fig + + +def plot_heatmaps( + heatmap: pd.Series, + agg: Union[Callable, str], + ncols: int, + filename: str = "", + plot_width: int = 1200, + open_browser: bool = True, +): + if not ( + isinstance(heatmap, pd.Series) and isinstance(heatmap.index, pd.MultiIndex) + ): + raise ValueError( + "heatmap must be heatmap Series as returned by " + "`Backtest.optimize(..., return_heatmap=True)`" + ) + + _bokeh_reset(filename) + + param_combinations = combinations(heatmap.index.names, 2) + dfs = [ + heatmap.groupby(list(dims)).agg(agg).to_frame(name="_Value") + for dims in param_combinations + ] + plots = [] + cmap = LinearColorMapper( + palette="Viridis256", + low=min(df.min().min() for df in dfs), + high=max(df.max().max() for df in dfs), + nan_color="white", + ) + for df in dfs: + name1, name2 = df.index.names + level1 = df.index.levels[0].astype(str).tolist() + level2 = df.index.levels[1].astype(str).tolist() + df = df.reset_index() + df[name1] = df[name1].astype("str") + df[name2] = df[name2].astype("str") + + fig = _figure( + x_range=level1, + y_range=level2, + x_axis_label=name1, + y_axis_label=name2, + width=plot_width // ncols, + height=plot_width // ncols, + tools="box_zoom,reset,save", + tooltips=[ + (name1, "@" + name1), + (name2, "@" + name2), + ("Value", "@_Value{0.[000]}"), + ], + ) + fig.grid.grid_line_color = None + fig.axis.axis_line_color = None + fig.axis.major_tick_line_color = None + fig.axis.major_label_standoff = 0 + + fig.rect( + x=name1, + y=name2, + width=1, + height=1, + source=df, + line_color=None, + fill_color=dict(field="_Value", transform=cmap), + ) + plots.append(fig) + + fig = gridplot( + plots, # type: ignore + ncols=ncols, + toolbar_options=dict(logo=None), + toolbar_location="above", + merge_tools=True, + ) + + show(fig, browser=None if open_browser else "none") + return fig diff --git a/fx_backtest/_stats.py b/fx_backtest/_stats.py new file mode 100644 index 0000000..67d06e7 --- /dev/null +++ b/fx_backtest/_stats.py @@ -0,0 +1,185 @@ +from typing import TYPE_CHECKING, List, Union + +import numpy as np +import pandas as pd + +from ._util import _data_period + +if TYPE_CHECKING: + from .backtesting import Strategy, Trade + + +def compute_drawdown_duration_peaks(dd: pd.Series): + iloc = np.unique(np.r_[(dd == 0).values.nonzero()[0], len(dd) - 1]) # type: ignore + iloc = pd.Series(iloc, index=dd.index[iloc]) # type: ignore + df = iloc.to_frame("iloc").assign(prev=iloc.shift()) # type: ignore + df = df[df["iloc"] > df["prev"] + 1].astype(int) + + # If no drawdown since no trade, avoid below for pandas sake and return nan series + if not len(df): + return (dd.replace(0, np.nan),) * 2 + + df["duration"] = df["iloc"].map(dd.index.__getitem__) - df["prev"].map( + dd.index.__getitem__ + ) + df["peak_dd"] = df.apply( + lambda row: dd.iloc[row["prev"] : row["iloc"] + 1].max(), axis=1 + ) + df = df.reindex(dd.index) + return df["duration"], df["peak_dd"] + + +def geometric_mean(returns: pd.Series) -> float: + returns = returns.fillna(0) + 1 + if np.any(returns <= 0): + return 0 + return np.exp(np.log(returns).sum() / (len(returns) or np.nan)) - 1 + + +def compute_stats( + trades: Union[List["Trade"], pd.DataFrame], + equity: np.ndarray, + ohlc_data: pd.DataFrame, + strategy_instance: "Strategy", + risk_free_rate: float = 0, +) -> pd.Series: + assert -1 < risk_free_rate < 1 + + index = ohlc_data.index + dd = 1 - equity / np.maximum.accumulate(equity) + dd_dur, dd_peaks = compute_drawdown_duration_peaks(pd.Series(dd, index=index)) + + equity_df = pd.DataFrame( + {"Equity": equity, "DrawdownPct": dd, "DrawdownDuration": dd_dur}, index=index + ) + + if isinstance(trades, pd.DataFrame): + trades_df: pd.DataFrame = trades + else: + # Came straight from Backtest.run() + trades_df = pd.DataFrame( + { + "Size": [t.size for t in trades], + "EntryBar": [t.entry_bar for t in trades], + "ExitBar": [t.exit_bar for t in trades], + "EntryPrice": [t.entry_price for t in trades], + "ExitPrice": [t.exit_price for t in trades], + "PnL": [t.pl for t in trades], + "ReturnPct": [t.pl_pct for t in trades], + "EntryTime": [t.entry_time for t in trades], + "ExitTime": [t.exit_time for t in trades], + "Tag": [t.tag for t in trades], + "TakeProfit": [t.tp for t in trades], + "StopLoss": [t.sl for t in trades], + } + ) + trades_df["Duration"] = trades_df["ExitTime"] - trades_df["EntryTime"] + del trades + + pl = trades_df["PnL"] + returns = trades_df["ReturnPct"] + durations = trades_df["Duration"] + + def _round_timedelta(value, _period=_data_period(index)): + if not isinstance(value, pd.Timedelta): + return value + resolution = getattr(_period, "resolution_string", None) or _period.resolution + return value.ceil(resolution) + + s = pd.Series(dtype=object) + s.loc["Start"] = index[0] + s.loc["End"] = index[-1] + s.loc["Duration"] = s.End - s.Start + + have_position = np.repeat(0, len(index)) + for t in trades_df.itertuples(index=False): + have_position[t.EntryBar : t.ExitBar + 1] = 1 + + s.loc["Exposure Time [%]"] = ( + have_position.mean() * 100 + ) # In "n bars" time, not index time + s.loc["Equity Final [$]"] = equity[-1] + s.loc["Equity Peak [$]"] = equity.max() + s.loc["Return [%]"] = (equity[-1] - equity[0]) / equity[0] * 100 + c = ohlc_data.Close.values + s.loc["Buy & Hold Return [%]"] = (c[-1] - c[0]) / c[0] * 100 # long-only return + + gmean_day_return: float = 0 + day_returns = np.array(np.nan) + annual_trading_days = np.nan + if isinstance(index, pd.DatetimeIndex): + day_returns = equity_df["Equity"].resample("D").last().dropna().pct_change() + gmean_day_return = geometric_mean(day_returns) + annual_trading_days = float( + 365 + if index.dayofweek.to_series().between(5, 6).mean() > 2 / 7 * 0.6 + else 252 + ) + + # Annualized return and risk metrics are computed based on the (mostly correct) + # assumption that the returns are compounded. See: https://dx.doi.org/10.2139/ssrn.3054517 + # Our annualized return matches `empyrical.annual_return(day_returns)` whereas + # our risk doesn't; they use the simpler approach below. + annualized_return = (1 + gmean_day_return) ** annual_trading_days - 1 + s.loc["Return (Ann.) [%]"] = annualized_return * 100 + s.loc["Volatility (Ann.) [%]"] = ( + np.sqrt( + ( + day_returns.var(ddof=int(bool(day_returns.shape))) + + (1 + gmean_day_return) ** 2 + ) + ** annual_trading_days + - (1 + gmean_day_return) ** (2 * annual_trading_days) + ) + * 100 + ) # noqa: E501 + # s.loc['Return (Ann.) [%]'] = gmean_day_return * annual_trading_days * 100 + # s.loc['Risk (Ann.) [%]'] = day_returns.std(ddof=1) * np.sqrt(annual_trading_days) * 100 + + # Our Sharpe mismatches `empyrical.sharpe_ratio()` because they use arithmetic mean return + # and simple standard deviation + s.loc["Sharpe Ratio"] = (s.loc["Return (Ann.) [%]"] - risk_free_rate) / ( + s.loc["Volatility (Ann.) [%]"] or np.nan + ) # noqa: E501 + # Our Sortino mismatches `empyrical.sortino_ratio()` because they use arithmetic mean return + s.loc["Sortino Ratio"] = (annualized_return - risk_free_rate) / ( + np.sqrt(np.mean(day_returns.clip(-np.inf, 0) ** 2)) + * np.sqrt(annual_trading_days) + ) # noqa: E501 + max_dd = -np.nan_to_num(dd.max()) + s.loc["Calmar Ratio"] = annualized_return / (-max_dd or np.nan) + s.loc["Max. Drawdown [%]"] = max_dd * 100 + s.loc["Avg. Drawdown [%]"] = -dd_peaks.mean() * 100 + s.loc["Max. Drawdown Duration"] = _round_timedelta(dd_dur.max()) + s.loc["Avg. Drawdown Duration"] = _round_timedelta(dd_dur.mean()) + s.loc["# Trades"] = n_trades = len(trades_df) + win_rate = np.nan if not n_trades else (pl > 0).mean() + s.loc["Win Rate [%]"] = win_rate * 100 + s.loc["Best Trade [%]"] = returns.max() * 100 + s.loc["Worst Trade [%]"] = returns.min() * 100 + mean_return = geometric_mean(returns) + s.loc["Avg. Trade [%]"] = mean_return * 100 + s.loc["Max. Trade Duration"] = _round_timedelta(durations.max()) + s.loc["Avg. Trade Duration"] = _round_timedelta(durations.mean()) + s.loc["Profit Factor"] = returns[returns > 0].sum() / ( + abs(returns[returns < 0].sum()) or np.nan + ) # noqa: E501 + s.loc["Expectancy [%]"] = returns.mean() * 100 + s.loc["SQN"] = np.sqrt(n_trades) * pl.mean() / (pl.std() or np.nan) + s.loc["Kelly Criterion"] = win_rate - (1 - win_rate) / ( + pl[pl > 0].mean() / -pl[pl < 0].mean() + ) + + s.loc["_strategy"] = strategy_instance + s.loc["_equity_curve"] = equity_df + s.loc["_trades"] = trades_df + + s = _Stats(s) + return s + + +class _Stats(pd.Series): + def __repr__(self): + # Prevent expansion due to _equity and _trades dfs + with pd.option_context("max_colwidth", 20): + return super().__repr__() diff --git a/fx_backtest/_util.py b/fx_backtest/_util.py new file mode 100644 index 0000000..6350e1f --- /dev/null +++ b/fx_backtest/_util.py @@ -0,0 +1,207 @@ +import warnings +from numbers import Number +from typing import Dict, List, Optional, Sequence, Union, cast + +import numpy as np +import pandas as pd + + +def try_(lazy_func, default=None, exception=Exception): + try: + return lazy_func() + except exception: + return default + + +def _as_str(value) -> str: + if isinstance(value, (Number, str)): + return str(value) + if isinstance(value, pd.DataFrame): + return "df" + name = str(getattr(value, "name", "") or "") + if name in ("Open", "High", "Low", "Close", "Volume"): + return name[:1] + if callable(value): + name = getattr(value, "__name__", value.__class__.__name__).replace( + "", "λ" + ) + if len(name) > 10: + name = name[:9] + "…" + return name + + +def _as_list(value) -> List: + if isinstance(value, Sequence) and not isinstance(value, str): + return list(value) + return [value] + + +def _data_period(index) -> Union[pd.Timedelta, Number]: + """Return data index period as pd.Timedelta""" + values = pd.Series(index[-100:]) + return values.diff().dropna().median() + + +class _Array(np.ndarray): + """ + ndarray extended to supply .name and other arbitrary properties + in ._opts dict. + """ + + def __new__(cls, array, *, name=None, **kwargs): + obj = np.asarray(array).view(cls) + obj.name = name or array.name + obj._opts = kwargs + return obj + + def __array_finalize__(self, obj): + if obj is not None: + self.name = getattr(obj, "name", "") + self._opts = getattr(obj, "_opts", {}) + + # Make sure properties name and _opts are carried over + # when (un-)pickling. + def __reduce__(self): + value = super().__reduce__() + return value[:2] + (value[2] + (self.__dict__,),) + + def __setstate__(self, state): + self.__dict__.update(state[-1]) + super().__setstate__(state[:-1]) + + def __bool__(self): + try: + return bool(self[-1]) + except IndexError: + return super().__bool__() + + def __float__(self): + try: + return float(self[-1]) + except IndexError: + return super().__float__() + + def to_series(self): + warnings.warn( + "`.to_series()` is deprecated. For pd.Series conversion, use accessor `.s`" + ) + return self.s + + @property + def s(self) -> pd.Series: + values = np.atleast_2d(self) + index = self._opts["index"][: values.shape[1]] + return pd.Series(values[0], index=index, name=self.name) + + @property + def df(self) -> pd.DataFrame: + values = np.atleast_2d(np.asarray(self)) + index = self._opts["index"][: values.shape[1]] + df = pd.DataFrame(values.T, index=index, columns=[self.name] * len(values)) + return df + + +class _Indicator(_Array): + pass + + +class _Data: + """ + A data array accessor. Provides access to OHLCV "columns" + as a standard `pd.DataFrame` would, except it's not a DataFrame + and the returned "series" are _not_ `pd.Series` but `np.ndarray` + for performance reasons. + """ + + def __init__(self, df: pd.DataFrame): + self.__df = df + self.__i = len(df) + self.__pip: Optional[float] = None + self.__cache: Dict[str, _Array] = {} + self.__arrays: Dict[str, _Array] = {} + self._update() + + def __getitem__(self, item): + return self.__get_array(item) + + def __getattr__(self, item): + try: + return self.__get_array(item) + except KeyError: + raise AttributeError(f"Column '{item}' not in data") from None + + def _set_length(self, i): + self.__i = i + self.__cache.clear() + + def _update(self): + index = self.__df.index.copy() + self.__arrays = { + col: _Array(arr, index=index) for col, arr in self.__df.items() + } + # Leave index as Series because pd.Timestamp nicer API to work with + self.__arrays["__index"] = index + + def __repr__(self): + i = min(self.__i, len(self.__df)) - 1 + index = self.__arrays["__index"][i] + items = ", ".join(f"{k}={v}" for k, v in self.__df.iloc[i].items()) + return f"" + + def __len__(self): + return self.__i + + @property + def df(self) -> pd.DataFrame: + return self.__df.iloc[: self.__i] if self.__i < len(self.__df) else self.__df + + @property + def pip(self) -> float: + if self.__pip is None: + self.__pip = float( + 10 + ** -np.median( + [ + len(s.partition(".")[-1]) + for s in self.__arrays["Close"].astype(str) + ] + ) + ) + return self.__pip + + def __get_array(self, key) -> _Array: + arr = self.__cache.get(key) + if arr is None: + arr = self.__cache[key] = cast(_Array, self.__arrays[key][: self.__i]) + return arr + + @property + def Open(self) -> _Array: + return self.__get_array("Open") + + @property + def High(self) -> _Array: + return self.__get_array("High") + + @property + def Low(self) -> _Array: + return self.__get_array("Low") + + @property + def Close(self) -> _Array: + return self.__get_array("Close") + + @property + def Volume(self) -> _Array: + return self.__get_array("Volume") + + @property + def index(self): + return self.__get_array("__index") + + # Make pickling in Backtest.optimize() work with our catch-all __getattr__ + def __getstate__(self): + return self.__dict__ + + def __setstate__(self, state): + self.__dict__ = state diff --git a/fx_backtest/_version.py b/fx_backtest/_version.py new file mode 100644 index 0000000..2e41576 --- /dev/null +++ b/fx_backtest/_version.py @@ -0,0 +1,17 @@ +# file generated by setuptools_scm +# don't change, don't track in version control +TYPE_CHECKING = False +if TYPE_CHECKING: + from typing import Tuple, Union + + VERSION_TUPLE = Tuple[Union[int, str], ...] +else: + VERSION_TUPLE = object + +version: str +__version__: str +__version_tuple__: VERSION_TUPLE +version_tuple: VERSION_TUPLE + +__version__ = version = "0.1.dev279+g0ce24d8.d20240114" +__version_tuple__ = version_tuple = (0, 1, "dev279", "g0ce24d8.d20240114") diff --git a/fx_backtest/autoscale_cb.js b/fx_backtest/autoscale_cb.js new file mode 100644 index 0000000..da888ec --- /dev/null +++ b/fx_backtest/autoscale_cb.js @@ -0,0 +1,35 @@ +if (!window._bt_scale_range) { + window._bt_scale_range = function (range, min, max, pad) { + "use strict"; + if (min !== Infinity && max !== -Infinity) { + pad = pad ? (max - min) * .03 : 0; + range.start = min - pad; + range.end = max + pad; + } else console.error('backtesting: scale range error:', min, max, range); + }; +} + +clearTimeout(window._bt_autoscale_timeout); + +window._bt_autoscale_timeout = setTimeout(function () { + /** + * @variable cb_obj `fig_ohlc.x_range`. + * @variable source `ColumnDataSource` + * @variable ohlc_range `fig_ohlc.y_range`. + * @variable volume_range `fig_volume.y_range`. + */ + "use strict"; + + let i = Math.max(Math.floor(cb_obj.start), 0), + j = Math.min(Math.ceil(cb_obj.end), source.data['ohlc_high'].length); + + let max = Math.max.apply(null, source.data['ohlc_high'].slice(i, j)), + min = Math.min.apply(null, source.data['ohlc_low'].slice(i, j)); + _bt_scale_range(ohlc_range, min, max, true); + + if (volume_range) { + max = Math.max.apply(null, source.data['Volume'].slice(i, j)); + _bt_scale_range(volume_range, 0, max * 1.03, false); + } + +}, 50); diff --git a/fx_backtest/backtesting.py b/fx_backtest/backtesting.py new file mode 100644 index 0000000..c290a95 --- /dev/null +++ b/fx_backtest/backtesting.py @@ -0,0 +1,1447 @@ +""" +Core framework data structures. +Objects from this module can also be imported from the top-level +module directly, e.g. + + from fx_backtest import Backtest, Strategy +""" + +import multiprocessing as mp +import os +import sys +import warnings +from abc import ABCMeta, abstractmethod +from concurrent.futures import ProcessPoolExecutor, as_completed +from functools import lru_cache, partial +from itertools import chain, compress, product, repeat +from math import copysign +from numbers import Number +from typing import Callable, Dict, List, Optional, Sequence, Tuple, Type, Union + +import numpy as np +import pandas as pd +from numpy.random import default_rng +from tqdm.auto import tqdm as _tqdm +_tqdm = partial(_tqdm, leave=False) + + +from fx_backtest._plotting import plot # noqa: I001 +from fx_backtest._stats import compute_stats +from fx_backtest._util import _as_str, _Data, _Indicator, try_ +from fx_backtest._models import Position, Order, Trade, _Orders +from fx_backtest._exceptions import _OutOfMoneyError + +__pdoc__ = { + "Strategy.__init__": False, + "Order.__init__": False, + "Position.__init__": False, + "Trade.__init__": False, +} + +class Strategy(metaclass=ABCMeta): + """ + A trading strategy base class. Extend this class and + override methods + `backtesting.backtesting.Strategy.init` and + `backtesting.backtesting.Strategy.next` to define + your own strategy. + """ + + def __init__(self, broker, data, params): + self._indicators = [] + self._broker: _Broker = broker + self._data: _Data = data + self._params = self._check_params(params) + + def __repr__(self): + return "" + + def __str__(self): + params = ",".join( + f"{i[0]}={i[1]}" + for i in zip(self._params.keys(), map(_as_str, self._params.values())) + ) + if params: + params = "(" + params + ")" + return f"{self.__class__.__name__}{params}" + + def _check_params(self, params): + for k, v in params.items(): + if not hasattr(self, k): + raise AttributeError( + f"Strategy '{self.__class__.__name__}' is missing parameter '{k}'." + "Strategy class should define parameters as class variables before they " + "can be optimized or run with." + ) + setattr(self, k, v) + return params + + def I( # noqa: E743 + self, + func: Callable, + *args, + name=None, + plot=True, + overlay=None, + color=None, + scatter=False, + **kwargs, + ) -> np.ndarray: + """ + Declare an indicator. An indicator is just an array of values, + but one that is revealed gradually in + `backtesting.backtesting.Strategy.next` much like + `backtesting.backtesting.Strategy.data` is. + Returns `np.ndarray` of indicator values. + + `func` is a function that returns the indicator array(s) of + same length as `backtesting.backtesting.Strategy.data`. + + In the plot legend, the indicator is labeled with + function name, unless `name` overrides it. + + If `plot` is `True`, the indicator is plotted on the resulting + `backtesting.backtesting.Backtest.plot`. + + If `overlay` is `True`, the indicator is plotted overlaying the + price candlestick chart (suitable e.g. for moving averages). + If `False`, the indicator is plotted standalone below the + candlestick chart. By default, a heuristic is used which decides + correctly most of the time. + + `color` can be string hex RGB triplet or X11 color name. + By default, the next available color is assigned. + + If `scatter` is `True`, the plotted indicator marker will be a + circle instead of a connected line segment (default). + + Additional `*args` and `**kwargs` are passed to `func` and can + be used for parameters. + + For example, using simple moving average function from TA-Lib: + + def init(): + self.sma = self.I(ta.SMA, self.data.Close, self.n_sma) + """ + if name is None: + params = ",".join(filter(None, map(_as_str, chain(args, kwargs.values())))) + func_name = _as_str(func) + name = f"{func_name}({params})" if params else f"{func_name}" + else: + name = name.format( + *map(_as_str, args), + **dict(zip(kwargs.keys(), map(_as_str, kwargs.values()))), + ) + + try: + value = func(*args, **kwargs) + except Exception as e: + raise RuntimeError(f'Indicator "{name}" error') from e + + if isinstance(value, pd.DataFrame): + value = value.values.T + + if value is not None: + value = try_(lambda: np.asarray(value, order="C"), None) + is_arraylike = bool(value is not None and value.shape) + + # Optionally flip the array if the user returned e.g. `df.values` + if is_arraylike and np.argmax(value.shape) == 0: + value = value.T + + if ( + not is_arraylike + or not 1 <= value.ndim <= 2 + or value.shape[-1] != len(self._data.Close) + ): + raise ValueError( + "Indicators must return (optionally a tuple of) numpy.arrays of same " + f'length as `data` (data shape: {self._data.Close.shape}; indicator "{name}" ' + f'shape: {getattr(value, "shape", "")}, returned value: {value})' + ) + + if plot and overlay is None and np.issubdtype(value.dtype, np.number): + x = value / self._data.Close + # By default, overlay if strong majority of indicator values + # is within 30% of Close + with np.errstate(invalid="ignore"): + overlay = ((x < 1.4) & (x > 0.6)).mean() > 0.6 + + value = _Indicator( + value, + name=name, + plot=plot, + overlay=overlay, + color=color, + scatter=scatter, + # _Indicator.s Series accessor uses this: + index=self.data.index, + ) + self._indicators.append(value) + return value + + @abstractmethod + def init(self): + """ + Initialize the strategy. + Override this method. + Declare indicators (with `backtesting.backtesting.Strategy.I`). + Precompute what needs to be precomputed or can be precomputed + in a vectorized fashion before the strategy starts. + + If you extend composable strategies from `backtesting.lib`, + make sure to call: + + super().init() + """ + + @abstractmethod + def next(self): + """ + Main strategy runtime method, called as each new + `backtesting.backtesting.Strategy.data` + instance (row; full candlestick bar) becomes available. + This is the main method where strategy decisions + upon data precomputed in `backtesting.backtesting.Strategy.init` + take place. + + If you extend composable strategies from `backtesting.lib`, + make sure to call: + + super().next() + """ + + class __FULL_EQUITY(float): # noqa: N801 + def __repr__(self): + return ".9999" + + _FULL_EQUITY = __FULL_EQUITY(1 - sys.float_info.epsilon) + + def buy( + self, + *, + size: float = _FULL_EQUITY, + limit: Optional[float] = None, + stop: Optional[float] = None, + sl: Optional[float] = None, + tp: Optional[float] = None, + tag: object = None, + ): + """ + Place a new long order. For explanation of parameters, see `Order` and its properties. + + See `Position.close()` and `Trade.close()` for closing existing positions. + + See also `Strategy.sell()`. + """ + assert ( + 0 < size < 1 or round(size) == size + ), "size must be a positive fraction of equity, or a positive whole number of units" + return self._broker.new_order(size, limit, stop, sl, tp, tag) + + def sell( + self, + *, + size: float = _FULL_EQUITY, + limit: Optional[float] = None, + stop: Optional[float] = None, + sl: Optional[float] = None, + tp: Optional[float] = None, + tag: object = None, + ): + """ + Place a new short order. For explanation of parameters, see `Order` and its properties. + + See also `Strategy.buy()`. + + .. note:: + If you merely want to close an existing long position, + use `Position.close()` or `Trade.close()`. + """ + assert ( + 0 < size < 1 or round(size) == size + ), "size must be a positive fraction of equity, or a positive whole number of units" + return self._broker.new_order(-size, limit, stop, sl, tp, tag) + + @property + def equity(self) -> float: + """Current account equity (cash plus assets).""" + return self._broker.equity + + @property + def data(self) -> _Data: + """ + Price data, roughly as passed into + `backtesting.backtesting.Backtest.__init__`, + but with two significant exceptions: + + * `data` is _not_ a DataFrame, but a custom structure + that serves customized numpy arrays for reasons of performance + and convenience. Besides OHLCV columns, `.index` and length, + it offers `.pip` property, the smallest price unit of change. + * Within `backtesting.backtesting.Strategy.init`, `data` arrays + are available in full length, as passed into + `backtesting.backtesting.Backtest.__init__` + (for precomputing indicators and such). However, within + `backtesting.backtesting.Strategy.next`, `data` arrays are + only as long as the current iteration, simulating gradual + price point revelation. In each call of + `backtesting.backtesting.Strategy.next` (iteratively called by + `backtesting.backtesting.Backtest` internally), + the last array value (e.g. `data.Close[-1]`) + is always the _most recent_ value. + * If you need data arrays (e.g. `data.Close`) to be indexed + **Pandas series**, you can call their `.s` accessor + (e.g. `data.Close.s`). If you need the whole of data + as a **DataFrame**, use `.df` accessor (i.e. `data.df`). + """ + return self._data + + @property + def position(self) -> Position: + """Instance of `backtesting.backtesting.Position`.""" + return self._broker.position + + @property + def orders(self) -> Tuple[Order, ...]: + """List of orders (see `Order`) waiting for execution.""" + return _Orders(self._broker.orders) + + @property + def trades(self) -> Tuple[Trade, ...]: + """List of active trades (see `Trade`).""" + return tuple(self._broker.trades) + + @property + def closed_trades(self) -> Tuple[Trade, ...]: + """List of settled trades (see `Trade`).""" + return tuple(self._broker.closed_trades) + +class BacktestStrategy(Strategy): + + def init(self): + super().init() + self._indicator_attrs = { + attr: indicator + for attr, indicator in self.__dict__.items() + if isinstance(indicator, _Indicator) + }.items() + + def next(self): + for attr, indicator in self._indicator_attrs: + # Slice indicator on the last dimension (case of 2d indicator) + setattr(self, attr, indicator[..., : len(self.data)]) + super().next() + +class _Broker: + def __init__( + self, + *, + data, + cash, + commission, + margin, + trade_on_close, + hedging, + exclusive_orders, + index, + ): + assert 0 < cash, f"cash should be >0, is {cash}" + assert -0.1 <= commission < 0.1, ( + "commission should be between -10% " + f"(e.g. market-maker's rebates) and 10% (fees), is {commission}" + ) + assert 0 < margin <= 1, f"margin should be between 0 and 1, is {margin}" + self._data: _Data = data + self._cash = cash + self._commission = commission + self._leverage = 1 / margin + self._trade_on_close = trade_on_close + self._hedging = hedging + self._exclusive_orders = exclusive_orders + + self._equity = np.tile(np.nan, len(index)) + self._orders: List[Order] = [] + self._trades: List[Trade] = [] + self.position = Position(self) + self.closed_trades: List[Trade] = [] + + def __repr__(self): + return f"" + + @property + def trades(self) -> List[Trade]: + return self._trades + + @property + def orders(self) -> List[Order]: + return self._orders + + def new_order( + self, + size: float, + limit: Optional[float] = None, + stop: Optional[float] = None, + sl: Optional[float] = None, + tp: Optional[float] = None, + tag: object = None, + *, + trade: Optional[Trade] = None, + ): + """ + Argument size indicates whether the order is long or short + """ + size = float(size) + stop = stop and float(stop) + limit = limit and float(limit) + sl = sl and float(sl) + tp = tp and float(tp) + + is_long = size > 0 + adjusted_price = self._adjusted_price(size) + + if is_long: + if not (sl or -np.inf) < (limit or stop or adjusted_price) < (tp or np.inf): + raise ValueError( + "Long orders require: " + f"SL ({sl}) < LIMIT ({limit or stop or adjusted_price}) < TP ({tp})" + ) + else: + if not (tp or -np.inf) < (limit or stop or adjusted_price) < (sl or np.inf): + raise ValueError( + "Short orders require: " + f"TP ({tp}) < LIMIT ({limit or stop or adjusted_price}) < SL ({sl})" + ) + + order = Order(self, size, limit, stop, sl, tp, trade, tag) + # Put the new order in the order queue, + # inserting SL/TP/trade-closing orders in-front + if trade: + self.orders.insert(0, order) + else: + # If exclusive orders (each new order auto-closes previous orders/position), + # cancel all non-contingent orders and close all open trades beforehand + if self._exclusive_orders: + for o in self.orders: + if not o.is_contingent: + o.cancel() + for t in self.trades: + t.close() + + self.orders.append(order) + + return order + + @property + def last_price(self) -> float: + """Price at the last (current) close.""" + return self._data.Close[-1] + + def _adjusted_price(self, size=None, price=None) -> float: + """ + Long/short `price`, adjusted for commisions. + In long positions, the adjusted price is a fraction higher, and vice versa. + """ + return (price or self.last_price) * (1 + copysign(self._commission, size)) + + @property + def equity(self) -> float: + return self._cash + sum(trade.pl for trade in self.trades) + + @property + def margin_available(self) -> float: + # From https://github.com/QuantConnect/Lean/pull/3768 + margin_used = sum(trade.value / self._leverage for trade in self.trades) + return max(0, self.equity - margin_used) + + def next(self): + i = self._i = len(self._data) - 1 + self._process_orders() + + # Log account equity for the equity curve + equity = self.equity + self._equity[i] = equity + + # If equity is negative, set all to 0 and stop the simulation + if equity <= 0: + assert self.margin_available <= 0 + for trade in self.trades: + self._close_trade(trade, self._data.Close[-1], i) + self._cash = 0 + self._equity[i:] = 0 + raise _OutOfMoneyError + + def _process_orders(self): + data = self._data + open, high, low = data.Open[-1], data.High[-1], data.Low[-1] + prev_close = data.Close[-2] + reprocess_orders = False + + # Process orders + for order in list(self.orders): + # Related SL/TP order was already removed + if order not in self.orders: + continue + + # Check if stop condition was hit + stop_price = order.stop + if stop_price: + is_stop_hit = ( + (high > stop_price) if order.is_long else (low < stop_price) + ) + if not is_stop_hit: + continue + + # > When the stop price is reached, a stop order becomes a market/limit order. + # https://www.sec.gov/fast-answers/answersstopordhtm.html + order._replace(stop_price=None) + + # Determine purchase price. + # Check if limit order can be filled. + if order.limit: + is_limit_hit = ( + low < order.limit if order.is_long else high > order.limit + ) + # When stop and limit are hit within the same bar, we pessimistically + # assume limit was hit before the stop (i.e. "before it counts") + is_limit_hit_before_stop = is_limit_hit and ( + order.limit < (stop_price or -np.inf) + if order.is_long + else order.limit > (stop_price or np.inf) + ) + if not is_limit_hit or is_limit_hit_before_stop: + continue + + # stop_price, if set, was hit within this bar + price = ( + min(stop_price or open, order.limit) + if order.is_long + else max(stop_price or open, order.limit) + ) + else: + # Market-if-touched / market order + price = prev_close if self._trade_on_close else open + price = ( + max(price, stop_price or -np.inf) + if order.is_long + else min(price, stop_price or np.inf) + ) + + # Determine entry/exit bar index + is_market_order = not order.limit and not stop_price + time_index = ( + (self._i - 1) if is_market_order and self._trade_on_close else self._i + ) + + # If order is a SL/TP order, it should close an existing trade it was contingent upon + if order.parent_trade: + trade = order.parent_trade + _prev_size = trade.size + # If order.size is "greater" than trade.size, this order is a trade.close() + # order and part of the trade was already closed beforehand + size = copysign(min(abs(_prev_size), abs(order.size)), order.size) + # If this trade isn't already closed (e.g. on multiple `trade.close(.5)` calls) + if trade in self.trades: + self._reduce_trade(trade, price, size, time_index) + assert order.size != -_prev_size or trade not in self.trades + if order in (trade._sl_order, trade._tp_order): + assert order.size == -trade.size + assert order not in self.orders # Removed when trade was closed + else: + # It's a trade.close() order, now done + assert abs(_prev_size) >= abs(size) >= 1 + self.orders.remove(order) + continue + + # Else this is a stand-alone trade + + # Adjust price to include commission (or bid-ask spread). + # In long positions, the adjusted price is a fraction higher, and vice versa. + adjusted_price = self._adjusted_price(order.size, price) + + # If order size was specified proportionally, + # precompute true size in units, accounting for margin and spread/commissions + size = order.size + if -1 < size < 1: + size = copysign( + int( + (self.margin_available * self._leverage * abs(size)) + // adjusted_price + ), + size, + ) + # Not enough cash/margin even for a single unit + if not size: + self.orders.remove(order) + continue + assert size == round(size) + need_size = int(size) + + if not self._hedging: + # Fill position by FIFO closing/reducing existing opposite-facing trades. + # Existing trades are closed at unadjusted price, because the adjustment + # was already made when buying. + for trade in list(self.trades): + if trade.is_long == order.is_long: + continue + assert trade.size * order.size < 0 + + # Order size greater than this opposite-directed existing trade, + # so it will be closed completely + if abs(need_size) >= abs(trade.size): + self._close_trade(trade, price, time_index) + need_size += trade.size + else: + # The existing trade is larger than the new order, + # so it will only be closed partially + self._reduce_trade(trade, price, need_size, time_index) + need_size = 0 + + if not need_size: + break + + # If we don't have enough liquidity to cover for the order, cancel it + if abs(need_size) * adjusted_price > self.margin_available * self._leverage: + self.orders.remove(order) + continue + + # Open a new trade + if need_size: + self._open_trade( + adjusted_price, need_size, order.sl, order.tp, time_index, order.tag + ) + + # We need to reprocess the SL/TP orders newly added to the queue. + # This allows e.g. SL hitting in the same bar the order was open. + # See https://github.com/kernc/backtesting.py/issues/119 + if order.sl or order.tp: + if is_market_order: + reprocess_orders = True + elif ( + low <= (order.sl or -np.inf) <= high + or low <= (order.tp or -np.inf) <= high + ): + warnings.warn( + f"({data.index[-1]}) A contingent SL/TP order would execute in the " + "same bar its parent stop/limit order was turned into a trade. " + "Since we can't assert the precise intra-candle " + "price movement, the affected SL/TP order will instead be executed on " + "the next (matching) price/bar, making the result (of this trade) " + "somewhat dubious. " + "See https://github.com/kernc/backtesting.py/issues/119", + UserWarning, + ) + + # Order processed + self.orders.remove(order) + + if reprocess_orders: + self._process_orders() + + def _reduce_trade(self, trade: Trade, price: float, size: float, time_index: int): + assert trade.size * size < 0 + assert abs(trade.size) >= abs(size) + + size_left = trade.size + size + assert size_left * trade.size >= 0 + if not size_left: + close_trade = trade + else: + # Reduce existing trade ... + trade._replace(size=size_left) + if trade._sl_order: + trade._sl_order._replace(size=-trade.size) + if trade._tp_order: + trade._tp_order._replace(size=-trade.size) + + # ... by closing a reduced copy of it + close_trade = trade._copy(size=-size, sl_order=None, tp_order=None) + self.trades.append(close_trade) + + self._close_trade(close_trade, price, time_index) + + def _close_trade(self, trade: Trade, price: float, time_index: int): + self.trades.remove(trade) + if trade._sl_order: + self.orders.remove(trade._sl_order) + if trade._tp_order: + self.orders.remove(trade._tp_order) + + self.closed_trades.append(trade._replace(exit_price=price, exit_bar=time_index)) + self._cash += trade.pl + + def _open_trade( + self, + price: float, + size: int, + sl: Optional[float], + tp: Optional[float], + time_index: int, + tag, + ): + trade = Trade(self, size, price, time_index, tag) + self.trades.append(trade) + # Create SL/TP (bracket) orders. + # Make sure SL order is created first so it gets adversarially processed before TP order + # in case of an ambiguous tie (both hit within a single bar). + # Note, sl/tp orders are inserted at the front of the list, thus order reversed. + if tp: + trade.tp = tp + if sl: + trade.sl = sl + + +class Backtest: + """ + Backtest a particular (parameterized) strategy + on particular data. + + Upon initialization, call method + `backtesting.backtesting.Backtest.run` to run a backtest + instance, or `backtesting.backtesting.Backtest.optimize` to + optimize it. + """ + + def __init__( + self, + data: pd.DataFrame, + strategy: Type[Strategy], + *, + cash: float = 10_000, + commission: float = 0.0, + margin: float = 1.0, + trade_on_close=False, + hedging=False, + exclusive_orders=False, + ): + """ + Initialize a backtest. Requires data and a strategy to test. + + `data` is a `pd.DataFrame` with columns: + `Open`, `High`, `Low`, `Close`, and (optionally) `Volume`. + If any columns are missing, set them to what you have available, + e.g. + + df['Open'] = df['High'] = df['Low'] = df['Close'] + + The passed data frame can contain additional columns that + can be used by the strategy (e.g. sentiment info). + DataFrame index can be either a datetime index (timestamps) + or a monotonic range index (i.e. a sequence of periods). + + `strategy` is a `backtesting.backtesting.Strategy` + _subclass_ (not an instance). + + `cash` is the initial cash to start with. + + `commission` is the commission ratio. E.g. if your broker's commission + is 1% of trade value, set commission to `0.01`. Note, if you wish to + account for bid-ask spread, you can approximate doing so by increasing + the commission, e.g. set it to `0.0002` for commission-less forex + trading where the average spread is roughly 0.2‰ of asking price. + + `margin` is the required margin (ratio) of a leveraged account. + No difference is made between initial and maintenance margins. + To run the backtest using e.g. 50:1 leverge that your broker allows, + set margin to `0.02` (1 / leverage). + + If `trade_on_close` is `True`, market orders will be filled + with respect to the current bar's closing price instead of the + next bar's open. + + If `hedging` is `True`, allow trades in both directions simultaneously. + If `False`, the opposite-facing orders first close existing trades in + a [FIFO] manner. + + If `exclusive_orders` is `True`, each new order auto-closes the previous + trade/position, making at most a single trade (long or short) in effect + at each time. + + [FIFO]: https://www.investopedia.com/terms/n/nfa-compliance-rule-2-43b.asp + """ + + if not (isinstance(strategy, type) and issubclass(strategy, Strategy)): + raise TypeError("`strategy` must be a Strategy sub-type") + if not isinstance(data, pd.DataFrame): + raise TypeError("`data` must be a pandas.DataFrame with columns") + if not isinstance(commission, Number): + raise TypeError( + "`commission` must be a float value, percent of " "entry order price" + ) + + data = data.copy(deep=False) + + # Convert index to datetime index + if ( + not isinstance(data.index, pd.DatetimeIndex) + and not isinstance(data.index, pd.RangeIndex) + and + # Numeric index with most large numbers + ( + data.index.is_numeric() + and (data.index > pd.Timestamp("1975").timestamp()).mean() > 0.8 + ) + ): + try: + data.index = pd.to_datetime(data.index, infer_datetime_format=True) + except ValueError: + pass + + if "Volume" not in data: + data["Volume"] = np.nan + + if len(data) == 0: + raise ValueError("OHLC `data` is empty") + if ( + len(data.columns.intersection({"Open", "High", "Low", "Close", "Volume"})) + != 5 + ): + raise ValueError( + "`data` must be a pandas.DataFrame with columns " + "'Open', 'High', 'Low', 'Close', and (optionally) 'Volume'" + ) + if data[["Open", "High", "Low", "Close"]].isnull().values.any(): + raise ValueError( + "Some OHLC values are missing (NaN). " + "Please strip those lines with `df.dropna()` or " + "fill them in with `df.interpolate()` or whatever." + ) + if np.any(data["Close"] > cash): + warnings.warn( + "Some prices are larger than initial cash value. Note that fractional " + "trading is not supported. If you want to trade Bitcoin, " + "increase initial cash, or trade μBTC or satoshis instead (GH-134).", + stacklevel=2, + ) + if not data.index.is_monotonic_increasing: + warnings.warn( + "Data index is not sorted in ascending order. Sorting.", stacklevel=2 + ) + data = data.sort_index() + if not isinstance(data.index, pd.DatetimeIndex): + warnings.warn( + "Data index is not datetime. Assuming simple periods, " + "but `pd.DateTimeIndex` is advised.", + stacklevel=2, + ) + + self._data: pd.DataFrame = data + self._broker = partial( + _Broker, + cash=cash, + commission=commission, + margin=margin, + trade_on_close=trade_on_close, + hedging=hedging, + exclusive_orders=exclusive_orders, + index=data.index, + ) + self._strategy = strategy + self._results: Optional[pd.Series] = None + + def run(self, **kwargs) -> pd.Series: + """ + Run the backtest. Returns `pd.Series` with results and statistics. + + Keyword arguments are interpreted as strategy parameters. + + >>> Backtest(GOOG, SmaCross).run() + Start 2004-08-19 00:00:00 + End 2013-03-01 00:00:00 + Duration 3116 days 00:00:00 + Exposure Time [%] 93.9944 + Equity Final [$] 51959.9 + Equity Peak [$] 75787.4 + Return [%] 419.599 + Buy & Hold Return [%] 703.458 + Return (Ann.) [%] 21.328 + Volatility (Ann.) [%] 36.5383 + Sharpe Ratio 0.583718 + Sortino Ratio 1.09239 + Calmar Ratio 0.444518 + Max. Drawdown [%] -47.9801 + Avg. Drawdown [%] -5.92585 + Max. Drawdown Duration 584 days 00:00:00 + Avg. Drawdown Duration 41 days 00:00:00 + # Trades 65 + Win Rate [%] 46.1538 + Best Trade [%] 53.596 + Worst Trade [%] -18.3989 + Avg. Trade [%] 2.35371 + Max. Trade Duration 183 days 00:00:00 + Avg. Trade Duration 46 days 00:00:00 + Profit Factor 2.08802 + Expectancy [%] 8.79171 + SQN 0.916893 + Kelly Criterion 0.6134 + _strategy SmaCross + _equity_curve Eq... + _trades Size EntryB... + dtype: object + + .. warning:: + You may obtain different results for different strategy parameters. + E.g. if you use 50- and 200-bar SMA, the trading simulation will + begin on bar 201. The actual length of delay is equal to the lookback + period of the `Strategy.I` indicator which lags the most. + Obviously, this can affect results. + """ + data = _Data(self._data.copy(deep=False)) + broker: _Broker = self._broker(data=data) + strategy: Strategy = self._strategy(broker, data, kwargs) + + strategy.init() + data._update() # Strategy.init might have changed/added to data.df + + # Indicators used in Strategy.next() + # indicator_attrs = { + # attr: indicator + # for attr, indicator in strategy.__dict__.items() + # if isinstance(indicator, _Indicator) + # }.items() + + # Skip first few candles where indicators are still "warming up" + # +1 to have at least two entries available + start = 1 + max( + ( + np.isnan(indicator.astype(float)).argmin(axis=-1).max() + for _, indicator in strategy._indicator_attrs + ), + default=0, + ) + + # Disable "invalid value encountered in ..." warnings. Comparison + # np.nan >= 3 is not invalid; it's False. + with np.errstate(invalid="ignore"): + + for i in range(start, len(self._data)): + # Prepare data and indicators for `next` call + data._set_length(i + 1) + + # Handle orders processing and broker stuff + try: + broker.next() + except _OutOfMoneyError: + break + + # Next tick, a moment before bar close + strategy.next() + else: + # Close any remaining open trades so they produce some stats + for trade in broker.trades: + trade.close() + + # Re-run broker one last time to handle orders placed in the last strategy + # iteration. Use the same OHLC values as in the last broker iteration. + if start < len(self._data): + try_(broker.next, exception=_OutOfMoneyError) + + # Set data back to full length + # for future `indicator._opts['data'].index` calls to work + data._set_length(len(self._data)) + + equity = pd.Series(broker._equity).bfill().fillna(broker._cash).values + self._results = compute_stats( + trades=broker.closed_trades, + equity=equity, + ohlc_data=self._data, + risk_free_rate=0.0, + strategy_instance=strategy, + ) + + return self._results + + def optimize( + self, + *, + maximize: Union[str, Callable[[pd.Series], float]] = "SQN", + method: str = "grid", + max_tries: Optional[Union[int, float]] = None, + constraint: Optional[Callable[[dict], bool]] = None, + return_heatmap: bool = False, + return_optimization: bool = False, + random_state: Optional[int] = None, + **kwargs, + ) -> Union[ + pd.Series, Tuple[pd.Series, pd.Series], Tuple[pd.Series, pd.Series, dict] + ]: + """ + Optimize strategy parameters to an optimal combination. + Returns result `pd.Series` of the best run. + + `maximize` is a string key from the + `backtesting.backtesting.Backtest.run`-returned results series, + or a function that accepts this series object and returns a number; + the higher the better. By default, the method maximizes + Van Tharp's [System Quality Number](https://google.com/search?q=System+Quality+Number). + + `method` is the optimization method. Currently two methods are supported: + + * `"grid"` which does an exhaustive (or randomized) search over the + cartesian product of parameter combinations, and + * `"skopt"` which finds close-to-optimal strategy parameters using + [model-based optimization], making at most `max_tries` evaluations. + + [model-based optimization]: \ + https://scikit-optimize.github.io/stable/auto_examples/bayesian-optimization.html + + `max_tries` is the maximal number of strategy runs to perform. + If `method="grid"`, this results in randomized grid search. + If `max_tries` is a floating value between (0, 1], this sets the + number of runs to approximately that fraction of full grid space. + Alternatively, if integer, it denotes the absolute maximum number + of evaluations. If unspecified (default), grid search is exhaustive, + whereas for `method="skopt"`, `max_tries` is set to 200. + + `constraint` is a function that accepts a dict-like object of + parameters (with values) and returns `True` when the combination + is admissible to test with. By default, any parameters combination + is considered admissible. + + If `return_heatmap` is `True`, besides returning the result + series, an additional `pd.Series` is returned with a multiindex + of all admissible parameter combinations, which can be further + inspected or projected onto 2D to plot a heatmap + (see `backtesting.lib.plot_heatmaps()`). + + If `return_optimization` is True and `method = 'skopt'`, + in addition to result series (and maybe heatmap), return raw + [`scipy.optimize.OptimizeResult`][OptimizeResult] for further + inspection, e.g. with [scikit-optimize]\ + [plotting tools]. + + [OptimizeResult]: \ + https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.OptimizeResult.html + [scikit-optimize]: https://scikit-optimize.github.io + [plotting tools]: https://scikit-optimize.github.io/stable/modules/plots.html + + If you want reproducible optimization results, set `random_state` + to a fixed integer random seed. + + Additional keyword arguments represent strategy arguments with + list-like collections of possible values. For example, the following + code finds and returns the "best" of the 7 admissible (of the + 9 possible) parameter combinations: + + backtest.optimize(sma1=[5, 10, 15], sma2=[10, 20, 40], + constraint=lambda p: p.sma1 < p.sma2) + + .. TODO:: + Improve multiprocessing/parallel execution on Windos with start method 'spawn'. + """ + if not kwargs: + raise ValueError("Need some strategy parameters to optimize") + + maximize_key = None + if isinstance(maximize, str): + maximize_key = str(maximize) + stats = self._results if self._results is not None else self.run() + if maximize not in stats: + raise ValueError( + "`maximize`, if str, must match a key in pd.Series " + "result of backtest.run()" + ) + + def maximize(stats: pd.Series, _key=maximize): + return stats[_key] + + elif not callable(maximize): + raise TypeError( + "`maximize` must be str (a field of backtest.run() result " + "Series) or a function that accepts result Series " + "and returns a number; the higher the better" + ) + assert callable(maximize), maximize + + have_constraint = bool(constraint) + if constraint is None: + + def constraint(_): + return True + + elif not callable(constraint): + raise TypeError( + "`constraint` must be a function that accepts a dict " + "of strategy parameters and returns a bool whether " + "the combination of parameters is admissible or not" + ) + assert callable(constraint), constraint + + if return_optimization and method != "skopt": + raise ValueError("return_optimization=True only valid if method='skopt'") + + def _tuple(x): + return x if isinstance(x, Sequence) and not isinstance(x, str) else (x,) + + for k, v in kwargs.items(): + if len(_tuple(v)) == 0: + raise ValueError( + f"Optimization variable '{k}' is passed no " + f"optimization values: {k}={v}" + ) + + class AttrDict(dict): + def __getattr__(self, item): + return self[item] + + def _grid_size(): + size = int(np.prod([len(_tuple(v)) for v in kwargs.values()])) + if size < 10_000 and have_constraint: + size = sum( + 1 + for p in product( + *(zip(repeat(k), _tuple(v)) for k, v in kwargs.items()) + ) + if constraint(AttrDict(p)) + ) + return size + + def _optimize_grid() -> Union[pd.Series, Tuple[pd.Series, pd.Series]]: + rand = default_rng(random_state).random + grid_frac = ( + 1 + if max_tries is None + else max_tries if 0 < max_tries <= 1 else max_tries / _grid_size() + ) + param_combos = [ + dict(params) # back to dict so it pickles + for params in ( + AttrDict(params) + for params in product( + *(zip(repeat(k), _tuple(v)) for k, v in kwargs.items()) + ) + ) + if constraint(params) and rand() <= grid_frac # type: ignore + ] + if not param_combos: + raise ValueError("No admissible parameter combinations to test") + + if len(param_combos) > 300: + warnings.warn( + f"Searching for best of {len(param_combos)} configurations.", + stacklevel=2, + ) + + heatmap = pd.Series( + np.nan, + name=maximize_key, + index=pd.MultiIndex.from_tuples( + [p.values() for p in param_combos], + names=next(iter(param_combos)).keys(), + ), + ) + + def _batch(seq): + n = np.clip(int(len(seq) // (os.cpu_count() or 1)), 1, 300) + for i in range(0, len(seq), n): + yield seq[i : i + n] + + # Save necessary objects into "global" state; pass into concurrent executor + # (and thus pickle) nothing but two numbers; receive nothing but numbers. + # With start method "fork", children processes will inherit parent address space + # in a copy-on-write manner, achieving better performance/RAM benefit. + backtest_uuid = np.random.random() + param_batches = list(_batch(param_combos)) + Backtest._mp_backtests[backtest_uuid] = (self, param_batches, maximize) # type: ignore + try: + # If multiprocessing start method is 'fork' (i.e. on POSIX), use + # a pool of processes to compute results in parallel. + # Otherwise (i.e. on Windos), sequential computation will be "faster". + if mp.get_start_method(allow_none=False) == "fork": + with ProcessPoolExecutor() as executor: + futures = [ + executor.submit(Backtest._mp_task, backtest_uuid, i) + for i in range(len(param_batches)) + ] + for future in _tqdm( + as_completed(futures), + total=len(futures), + desc="Backtest.optimize", + ): + batch_index, values = future.result() + for value, params in zip( + values, param_batches[batch_index] + ): + heatmap[tuple(params.values())] = value + else: + if os.name == "posix": + warnings.warn( + "For multiprocessing support in `Backtest.optimize()` " + "set multiprocessing start method to 'fork'." + ) + for batch_index in _tqdm(range(len(param_batches))): + _, values = Backtest._mp_task(backtest_uuid, batch_index) + for value, params in zip(values, param_batches[batch_index]): + heatmap[tuple(params.values())] = value + finally: + del Backtest._mp_backtests[backtest_uuid] + + best_params = heatmap.idxmax() + + if pd.isnull(best_params): + # No trade was made in any of the runs. Just make a random + # run so we get some, if empty, results + stats = self.run(**param_combos[0]) + else: + stats = self.run(**dict(zip(heatmap.index.names, best_params))) + + if return_heatmap: + return stats, heatmap + return stats + + def _optimize_skopt() -> Union[ + pd.Series, + Tuple[pd.Series, pd.Series], + Tuple[pd.Series, pd.Series, dict], + ]: + try: + from skopt import forest_minimize + from skopt.callbacks import DeltaXStopper + from skopt.learning import ExtraTreesRegressor + from skopt.space import Categorical, Integer, Real + from skopt.utils import use_named_args + except ImportError: + raise ImportError( + "Need package 'scikit-optimize' for method='skopt'. " + "pip install scikit-optimize" + ) from None + + nonlocal max_tries + max_tries = ( + 200 + if max_tries is None + else ( + max(1, int(max_tries * _grid_size())) + if 0 < max_tries <= 1 + else max_tries + ) + ) + + dimensions = [] + for key, values in kwargs.items(): + values = np.asarray(values) + if values.dtype.kind in "mM": # timedelta, datetime64 + # these dtypes are unsupported in skopt, so convert to raw int + # TODO: save dtype and convert back later + values = values.astype(int) + + if values.dtype.kind in "iumM": + dimensions.append( + Integer(low=values.min(), high=values.max(), name=key) + ) + elif values.dtype.kind == "f": + dimensions.append( + Real(low=values.min(), high=values.max(), name=key) + ) + else: + dimensions.append( + Categorical(values.tolist(), name=key, transform="onehot") + ) + + # Avoid recomputing re-evaluations: + # "The objective has been evaluated at this point before." + # https://github.com/scikit-optimize/scikit-optimize/issues/302 + memoized_run = lru_cache()(lambda tup: self.run(**dict(tup))) + + # np.inf/np.nan breaks sklearn, np.finfo(float).max breaks skopt.plots.plot_objective + INVALID = 1e300 + progress = iter( + _tqdm(repeat(None), total=max_tries, desc="Backtest.optimize") + ) + + @use_named_args(dimensions=dimensions) + def objective_function(**params): + next(progress) + # Check constraints + # TODO: Adjust after https://github.com/scikit-optimize/scikit-optimize/pull/971 + if not constraint(AttrDict(params)): + return INVALID + res = memoized_run(tuple(params.items())) + value = -maximize(res) + if np.isnan(value): + return INVALID + return value + + with warnings.catch_warnings(): + warnings.filterwarnings( + "ignore", "The objective has been evaluated at this point before." + ) + + res = forest_minimize( + func=objective_function, + dimensions=dimensions, + n_calls=max_tries, + base_estimator=ExtraTreesRegressor( + n_estimators=20, min_samples_leaf=2 + ), + acq_func="LCB", + kappa=3, + n_initial_points=min(max_tries, 20 + 3 * len(kwargs)), + initial_point_generator="lhs", # 'sobel' requires n_initial_points ~ 2**N + callback=DeltaXStopper(9e-7), + random_state=random_state, + ) + + stats = self.run(**dict(zip(kwargs.keys(), res.x))) + output = [stats] + + if return_heatmap: + heatmap = pd.Series( + dict(zip(map(tuple, res.x_iters), -res.func_vals)), + name=maximize_key, + ) + heatmap.index.names = kwargs.keys() + heatmap = heatmap[heatmap != -INVALID] + heatmap.sort_index(inplace=True) + output.append(heatmap) + + if return_optimization: + valid = res.func_vals != INVALID + res.x_iters = list(compress(res.x_iters, valid)) + res.func_vals = res.func_vals[valid] + output.append(res) + + return stats if len(output) == 1 else tuple(output) + + if method == "grid": + output = _optimize_grid() + elif method == "skopt": + output = _optimize_skopt() + else: + raise ValueError(f"Method should be 'grid' or 'skopt', not {method!r}") + return output + + @staticmethod + def _mp_task(backtest_uuid, batch_index): + bt, param_batches, maximize_func = Backtest._mp_backtests[backtest_uuid] + return batch_index, [ + maximize_func(stats) if stats["# Trades"] else np.nan + for stats in (bt.run(**params) for params in param_batches[batch_index]) + ] + + _mp_backtests: Dict[float, Tuple["Backtest", List, Callable]] = {} + + def plot( + self, + *, + results: pd.Series = None, + filename=None, + plot_width=None, + plot_equity=True, + plot_return=False, + plot_pl=True, + plot_volume=True, + plot_drawdown=False, + plot_trades=True, + smooth_equity=False, + relative_equity=True, + superimpose: Union[bool, str] = True, + resample=True, + reverse_indicators=False, + show_legend=True, + open_browser=True, + ): + """ + Plot the progression of the last backtest run. + + If `results` is provided, it should be a particular result + `pd.Series` such as returned by + `backtesting.backtesting.Backtest.run` or + `backtesting.backtesting.Backtest.optimize`, otherwise the last + run's results are used. + + `filename` is the path to save the interactive HTML plot to. + By default, a strategy/parameter-dependent file is created in the + current working directory. + + `plot_width` is the width of the plot in pixels. If None (default), + the plot is made to span 100% of browser width. The height is + currently non-adjustable. + + If `plot_equity` is `True`, the resulting plot will contain + an equity (initial cash plus assets) graph section. This is the same + as `plot_return` plus initial 100%. + + If `plot_return` is `True`, the resulting plot will contain + a cumulative return graph section. This is the same + as `plot_equity` minus initial 100%. + + If `plot_pl` is `True`, the resulting plot will contain + a profit/loss (P/L) indicator section. + + If `plot_volume` is `True`, the resulting plot will contain + a trade volume section. + + If `plot_drawdown` is `True`, the resulting plot will contain + a separate drawdown graph section. + + If `plot_trades` is `True`, the stretches between trade entries + and trade exits are marked by hash-marked tractor beams. + + If `smooth_equity` is `True`, the equity graph will be + interpolated between fixed points at trade closing times, + unaffected by any interim asset volatility. + + If `relative_equity` is `True`, scale and label equity graph axis + with return percent, not absolute cash-equivalent values. + + If `superimpose` is `True`, superimpose larger-timeframe candlesticks + over the original candlestick chart. Default downsampling rule is: + monthly for daily data, daily for hourly data, hourly for minute data, + and minute for (sub-)second data. + `superimpose` can also be a valid [Pandas offset string], + such as `'5T'` or `'5min'`, in which case this frequency will be + used to superimpose. + Note, this only works for data with a datetime index. + + If `resample` is `True`, the OHLC data is resampled in a way that + makes the upper number of candles for Bokeh to plot limited to 10_000. + This may, in situations of overabundant data, + improve plot's interactive performance and avoid browser's + `Javascript Error: Maximum call stack size exceeded` or similar. + Equity & dropdown curves and individual trades data is, + likewise, [reasonably _aggregated_][TRADES_AGG]. + `resample` can also be a [Pandas offset string], + such as `'5T'` or `'5min'`, in which case this frequency will be + used to resample, overriding above numeric limitation. + Note, all this only works for data with a datetime index. + + If `reverse_indicators` is `True`, the indicators below the OHLC chart + are plotted in reverse order of declaration. + + [Pandas offset string]: \ + https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#dateoffset-objects + + [TRADES_AGG]: lib.html#backtesting.lib.TRADES_AGG + + If `show_legend` is `True`, the resulting plot graphs will contain + labeled legends. + + If `open_browser` is `True`, the resulting `filename` will be + opened in the default web browser. + """ + if results is None: + if self._results is None: + raise RuntimeError("First issue `backtest.run()` to obtain results.") + results = self._results + + return plot( + results=results, + df=self._data, + indicators=results._strategy._indicators, + filename=filename, + plot_width=plot_width, + plot_equity=plot_equity, + plot_return=plot_return, + plot_pl=plot_pl, + plot_volume=plot_volume, + plot_drawdown=plot_drawdown, + plot_trades=plot_trades, + smooth_equity=smooth_equity, + relative_equity=relative_equity, + superimpose=superimpose, + resample=resample, + reverse_indicators=reverse_indicators, + show_legend=show_legend, + open_browser=open_browser, + ) diff --git a/fx_backtest/lib.py b/fx_backtest/lib.py new file mode 100644 index 0000000..15c228a --- /dev/null +++ b/fx_backtest/lib.py @@ -0,0 +1,558 @@ +""" +Collection of common building blocks, helper auxiliary functions and +composable strategy classes for reuse. + +Intended for simple missing-link procedures, not reinventing +of better-suited, state-of-the-art, fast libraries, +such as TA-Lib, Tulipy, PyAlgoTrade, NumPy, SciPy ... + +Please raise ideas for additions to this collection on the [issue tracker]. + +[issue tracker]: https://github.com/kernc/backtesting.py +""" + +from collections import OrderedDict +from inspect import currentframe +from itertools import compress +from numbers import Number +from typing import Callable, Generator, Optional, Sequence, Union + +import numpy as np +import pandas as pd + +from ._plotting import plot_heatmaps as _plot_heatmaps +from ._stats import compute_stats as _compute_stats +from ._util import _Array, _as_str +from .backtesting import Strategy + +__pdoc__ = {} + + +OHLCV_AGG = OrderedDict( + ( + ("Open", "first"), + ("High", "max"), + ("Low", "min"), + ("Close", "last"), + ("Volume", "sum"), + ) +) +"""Dictionary of rules for aggregating resampled OHLCV data frames, +e.g. + + df.resample('4H', label='right').agg(OHLCV_AGG).dropna() +""" + +TRADES_AGG = OrderedDict( + ( + ("Size", "sum"), + ("EntryBar", "first"), + ("ExitBar", "last"), + ("EntryPrice", "mean"), + ("ExitPrice", "mean"), + ("PnL", "sum"), + ("ReturnPct", "mean"), + ("EntryTime", "first"), + ("ExitTime", "last"), + ("TakeProfit", "mean"), + ("StopLoss", "mean"), + ("Duration", "sum"), + ) +) +"""Dictionary of rules for aggregating resampled trades data, +e.g. + + stats['_trades'].resample('1D', on='ExitTime', + label='right').agg(TRADES_AGG) +""" + +_EQUITY_AGG = { + "Equity": "last", + "DrawdownPct": "max", + "DrawdownDuration": "max", +} + + +def barssince(condition: Sequence[bool], default=np.inf) -> int: + """ + Return the number of bars since `condition` sequence was last `True`, + or if never, return `default`. + + >>> barssince(self.data.Close > self.data.Open) + 3 + """ + return next(compress(range(len(condition)), reversed(condition)), default) + + +def cross(series1: Sequence, series2: Sequence) -> bool: + """ + Return `True` if `series1` and `series2` just crossed + (above or below) each other. + + >>> cross(self.data.Close, self.sma) + True + + """ + return crossover(series1, series2) or crossover(series2, series1) + + +def crossover(series1: Sequence, series2: Sequence) -> bool: + """ + Return `True` if `series1` just crossed over (above) + `series2`. + + >>> crossover(self.data.Close, self.sma) + True + """ + series1 = ( + series1.values + if isinstance(series1, pd.Series) + else (series1, series1) if isinstance(series1, Number) else series1 + ) + series2 = ( + series2.values + if isinstance(series2, pd.Series) + else (series2, series2) if isinstance(series2, Number) else series2 + ) + try: + return series1[-2] < series2[-2] and series1[-1] > series2[-1] + except IndexError: + return False + + +def plot_heatmaps( + heatmap: pd.Series, + agg: Union[str, Callable] = "max", + *, + ncols: int = 3, + plot_width: int = 1200, + filename: str = "", + open_browser: bool = True, +): + """ + Plots a grid of heatmaps, one for every pair of parameters in `heatmap`. + + `heatmap` is a Series as returned by + `backtesting.backtesting.Backtest.optimize` when its parameter + `return_heatmap=True`. + + When projecting the n-dimensional heatmap onto 2D, the values are + aggregated by 'max' function by default. This can be tweaked + with `agg` parameter, which accepts any argument pandas knows + how to aggregate by. + + .. todo:: + Lay heatmaps out lower-triangular instead of in a simple grid. + Like [`skopt.plots.plot_objective()`][plot_objective] does. + + [plot_objective]: \ + https://scikit-optimize.github.io/stable/modules/plots.html#plot-objective + """ + return _plot_heatmaps(heatmap, agg, ncols, filename, plot_width, open_browser) + + +def quantile(series: Sequence, quantile: Union[None, float] = None): + """ + If `quantile` is `None`, return the quantile _rank_ of the last + value of `series` wrt former series values. + + If `quantile` is a value between 0 and 1, return the _value_ of + `series` at this quantile. If used to working with percentiles, just + divide your percentile amount with 100 to obtain quantiles. + + >>> quantile(self.data.Close[-20:], .1) + 162.130 + >>> quantile(self.data.Close) + 0.13 + """ + if quantile is None: + try: + last, series = series[-1], series[:-1] + return np.mean(series < last) + except IndexError: + return np.nan + assert 0 <= quantile <= 1, "quantile must be within [0, 1]" + return np.nanpercentile(series, quantile * 100) + + +def compute_stats( + *, + stats: pd.Series, + data: pd.DataFrame, + trades: pd.DataFrame = None, + risk_free_rate: float = 0.0, +) -> pd.Series: + """ + (Re-)compute strategy performance metrics. + + `stats` is the statistics series as returned by `backtesting.backtesting.Backtest.run()`. + `data` is OHLC data as passed to the `backtesting.backtesting.Backtest` + the `stats` were obtained in. + `trades` can be a dataframe subset of `stats._trades` (e.g. only long trades). + You can also tune `risk_free_rate`, used in calculation of Sharpe and Sortino ratios. + + >>> stats = Backtest(GOOG, MyStrategy).run() + >>> only_long_trades = stats._trades[stats._trades.Size > 0] + >>> long_stats = compute_stats(stats=stats, trades=only_long_trades, + ... data=GOOG, risk_free_rate=.02) + """ + equity = stats._equity_curve.Equity + if trades is None: + trades = stats._trades + else: + # XXX: Is this buggy? + equity = equity.copy() + equity[:] = stats._equity_curve.Equity.iloc[0] + for t in trades.itertuples(index=False): + equity.iloc[t.EntryBar :] += t.PnL + return _compute_stats( + trades=trades, + equity=equity, + ohlc_data=data, + risk_free_rate=risk_free_rate, + strategy_instance=stats._strategy, + ) + + +def resample_apply( + rule: str, + func: Optional[Callable[..., Sequence]], + series: Union[pd.Series, pd.DataFrame, _Array], + *args, + agg: Optional[Union[str, dict]] = None, + **kwargs, +): + """ + Apply `func` (such as an indicator) to `series`, resampled to + a time frame specified by `rule`. When called from inside + `backtesting.backtesting.Strategy.init`, + the result (returned) series will be automatically wrapped in + `backtesting.backtesting.Strategy.I` + wrapper method. + + `rule` is a valid [Pandas offset string] indicating + a time frame to resample `series` to. + + [Pandas offset string]: \ +http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases + + `func` is the indicator function to apply on the resampled series. + + `series` is a data series (or array), such as any of the + `backtesting.backtesting.Strategy.data` series. Due to pandas + resampling limitations, this only works when input series + has a datetime index. + + `agg` is the aggregation function to use on resampled groups of data. + Valid values are anything accepted by `pandas/resample/.agg()`. + Default value for dataframe input is `OHLCV_AGG` dictionary. + Default value for series input is the appropriate entry from `OHLCV_AGG` + if series has a matching name, or otherwise the value `"last"`, + which is suitable for closing prices, + but you might prefer another (e.g. `"max"` for peaks, or similar). + + Finally, any `*args` and `**kwargs` that are not already eaten by + implicit `backtesting.backtesting.Strategy.I` call + are passed to `func`. + + For example, if we have a typical moving average function + `SMA(values, lookback_period)`, _hourly_ data source, and need to + apply the moving average MA(10) on a _daily_ time frame, + but don't want to plot the resulting indicator, we can do: + + class System(Strategy): + def init(self): + self.sma = resample_apply( + 'D', SMA, self.data.Close, 10, plot=False) + + The above short snippet is roughly equivalent to: + + class System(Strategy): + def init(self): + # Strategy exposes `self.data` as raw NumPy arrays. + # Let's convert closing prices back to pandas Series. + close = self.data.Close.s + + # Resample to daily resolution. Aggregate groups + # using their last value (i.e. closing price at the end + # of the day). Notice `label='right'`. If it were set to + # 'left' (default), the strategy would exhibit + # look-ahead bias. + daily = close.resample('D', label='right').agg('last') + + # We apply SMA(10) to daily close prices, + # then reindex it back to original hourly index, + # forward-filling the missing values in each day. + # We make a separate function that returns the final + # indicator array. + def SMA(series, n): + from backtesting.test import SMA + return SMA(series, n).reindex(close.index).ffill() + + # The result equivalent to the short example above: + self.sma = self.I(SMA, daily, 10, plot=False) + + """ + if func is None: + + def func(x, *_, **__): + return x + + if not isinstance(series, (pd.Series, pd.DataFrame)): + assert isinstance(series, _Array), ( + "resample_apply() takes either a `pd.Series`, `pd.DataFrame`, " + "or a `Strategy.data.*` array" + ) + series = series.s + + if agg is None: + agg = OHLCV_AGG.get(getattr(series, "name", ""), "last") + if isinstance(series, pd.DataFrame): + agg = {column: OHLCV_AGG.get(column, "last") for column in series.columns} + + resampled = series.resample(rule, label="right").agg(agg).dropna() + resampled.name = _as_str(series) + "[" + rule + "]" + + # Check first few stack frames if we are being called from + # inside Strategy.init, and if so, extract Strategy.I wrapper. + frame, level = currentframe(), 0 + while frame and level <= 3: + frame = frame.f_back + level += 1 + if isinstance(frame.f_locals.get("self"), Strategy): # type: ignore + strategy_I = frame.f_locals["self"].I # type: ignore + break + else: + + def strategy_I(func, *args, **kwargs): # noqa: F811 + return func(*args, **kwargs) + + def wrap_func(resampled, *args, **kwargs): + result = func(resampled, *args, **kwargs) + if not isinstance(result, pd.DataFrame) and not isinstance(result, pd.Series): + result = np.asarray(result) + if result.ndim == 1: + result = pd.Series(result, name=resampled.name) + elif result.ndim == 2: + result = pd.DataFrame(result.T) + # Resample back to data index + if not isinstance(result.index, pd.DatetimeIndex): + result.index = resampled.index + result = result.reindex( + index=series.index.union(resampled.index), method="ffill" + ).reindex(series.index) + return result + + wrap_func.__name__ = func.__name__ + + array = strategy_I(wrap_func, resampled, *args, **kwargs) + return array + + +def random_ohlc_data( + example_data: pd.DataFrame, *, frac=1.0, random_state: Optional[int] = None +) -> Generator[pd.DataFrame, None, None]: + """ + OHLC data generator. The generated OHLC data has basic + [descriptive statistics](https://en.wikipedia.org/wiki/Descriptive_statistics) + similar to the provided `example_data`. + + `frac` is a fraction of data to sample (with replacement). Values greater + than 1 result in oversampling. + + Such random data can be effectively used for stress testing trading + strategy robustness, Monte Carlo simulations, significance testing, etc. + + >>> from backtesting.test import EURUSD + >>> ohlc_generator = random_ohlc_data(EURUSD) + >>> next(ohlc_generator) # returns new random data + ... + >>> next(ohlc_generator) # returns new random data + ... + """ + + def shuffle(x): + return x.sample(frac=frac, replace=frac > 1, random_state=random_state) + + if len(example_data.columns.intersection({"Open", "High", "Low", "Close"})) != 4: + raise ValueError( + "`data` must be a pandas.DataFrame with columns " + "'Open', 'High', 'Low', 'Close'" + ) + while True: + df = shuffle(example_data) + df.index = example_data.index + padding = df.Close - df.Open.shift(-1) + gaps = shuffle(example_data.Open.shift(-1) - example_data.Close) + deltas = (padding + gaps).shift(1).fillna(0).cumsum() + for key in ("Open", "High", "Low", "Close"): + df[key] += deltas + yield df + + +class SignalStrategy(Strategy): + """ + A simple helper strategy that operates on position entry/exit signals. + This makes the backtest of the strategy simulate a [vectorized backtest]. + See [tutorials] for usage examples. + + [vectorized backtest]: https://www.google.com/search?q=vectorized+backtest + [tutorials]: index.html#tutorials + + To use this helper strategy, subclass it, override its + `backtesting.backtesting.Strategy.init` method, + and set the signal vector by calling + `backtesting.lib.SignalStrategy.set_signal` method from within it. + + class ExampleStrategy(SignalStrategy): + def init(self): + super().init() + self.set_signal(sma1 > sma2, sma1 < sma2) + + Remember to call `super().init()` and `super().next()` in your + overridden methods. + """ + + __entry_signal = (0,) + __exit_signal = (False,) + + def set_signal( + self, + entry_size: Sequence[float], + exit_portion: Optional[Sequence[float]] = None, + *, + plot: bool = True, + ): + """ + Set entry/exit signal vectors (arrays). + + A long entry signal is considered present wherever `entry_size` + is greater than zero, and a short signal wherever `entry_size` + is less than zero, following `backtesting.backtesting.Order.size` semantics. + + If `exit_portion` is provided, a nonzero value closes portion the position + (see `backtesting.backtesting.Trade.close()`) in the respective direction + (positive values close long trades, negative short). + + If `plot` is `True`, the signal entry/exit indicators are plotted when + `backtesting.backtesting.Backtest.plot` is called. + """ + self.__entry_signal = self.I( # type: ignore + lambda: pd.Series(entry_size, dtype=float).replace(0, np.nan), + name="entry size", + plot=plot, + overlay=False, + scatter=True, + color="black", + ) + + if exit_portion is not None: + self.__exit_signal = self.I( # type: ignore + lambda: pd.Series(exit_portion, dtype=float).replace(0, np.nan), + name="exit portion", + plot=plot, + overlay=False, + scatter=True, + color="black", + ) + + def next(self): + super().next() + + exit_portion = self.__exit_signal[-1] + if exit_portion > 0: + for trade in self.trades: + if trade.is_long: + trade.close(exit_portion) + elif exit_portion < 0: + for trade in self.trades: + if trade.is_short: + trade.close(-exit_portion) + + entry_size = self.__entry_signal[-1] + if entry_size > 0: + self.buy(size=entry_size) + elif entry_size < 0: + self.sell(size=-entry_size) + + +class TrailingStrategy(Strategy): + """ + A strategy with automatic trailing stop-loss, trailing the current + price at distance of some multiple of average true range (ATR). Call + `TrailingStrategy.set_trailing_sl()` to set said multiple + (`6` by default). See [tutorials] for usage examples. + + [tutorials]: index.html#tutorials + + Remember to call `super().init()` and `super().next()` in your + overridden methods. + """ + + __n_atr = 6.0 + __atr = None + + def init(self): + super().init() + self.set_atr_periods() + + def set_atr_periods(self, periods: int = 100): + """ + Set the lookback period for computing ATR. The default value + of 100 ensures a _stable_ ATR. + """ + hi, lo, c_prev = ( + self.data.High, + self.data.Low, + pd.Series(self.data.Close).shift(1), + ) + tr = np.max([hi - lo, (c_prev - hi).abs(), (c_prev - lo).abs()], axis=0) + atr = pd.Series(tr).rolling(periods).mean().bfill().values + self.__atr = atr + + def set_trailing_sl(self, n_atr: float = 6): + """ + Sets the future trailing stop-loss as some multiple (`n_atr`) + average true bar ranges away from the current price. + """ + self.__n_atr = n_atr + + def next(self): + super().next() + # Can't use index=-1 because self.__atr is not an Indicator type + index = len(self.data) - 1 + for trade in self.trades: + if trade.is_long: + trade.sl = max( + trade.sl or -np.inf, + self.data.Close[index] - self.__atr[index] * self.__n_atr, + ) + else: + trade.sl = min( + trade.sl or np.inf, + self.data.Close[index] + self.__atr[index] * self.__n_atr, + ) + + +# Prevent pdoc3 documenting __init__ signature of Strategy subclasses +for cls in list(globals().values()): + if isinstance(cls, type) and issubclass(cls, Strategy): + __pdoc__[f"{cls.__name__}.__init__"] = False + + +# NOTE: Don't put anything below this __all__ list + +__all__ = [ + getattr(v, "__name__", k) + for k, v in globals().items() # export + if ( + ( + callable(v) + and v.__module__ == __name__ # callables from this module + or k.isupper() + ) # or CONSTANTS + and not getattr(v, "__name__", k).startswith("_") + ) +] # neither marked internal + +# NOTE: Don't put anything below here. See above. diff --git a/fx_backtest/main.py b/fx_backtest/main.py index 5da3fee..022c39c 100644 --- a/fx_backtest/main.py +++ b/fx_backtest/main.py @@ -1,21 +1,20 @@ import pandas as pd -from backtesting import Backtest from fx_strategy.strategy import SlopeMomentum +from fx_backtest.backtesting import Backtest, BacktestStrategy -def calculate_stop_loss(cash, pair, price, risk=0.01): - pass - - -with open("/home/kyle/Tick_Data/ohlc/2024/January/GBPUSD-2024-01_5Min.csv") as fh: +with open("/home/kyle/Tick_Data/ohlc/2024/February/EURUSD-2024-02_5Min.csv") as fh: data = pd.read_csv(fh, parse_dates=["Timestamp"]) - data.rename(columns={"open": "Open", "high": "High", "low": "Low", "close": "Close"}, inplace=True) + data.rename( + columns={"open": "Open", "high": "High", "low": "Low", "close": "Close"}, + inplace=True, + ) data = data.dropna() bt = Backtest( - data, SlopeMomentum, commission=0.000, exclusive_orders=False, margin=0.02 + data, BacktestStrategy, commission=0.000, exclusive_orders=False, margin=0.02 ) -stats = bt.run() +stats = bt.run(_klass=SlopeMomentum) bt.plot() print(stats) diff --git a/.bandit b/fx_backtest/py.typed similarity index 100% rename from .bandit rename to fx_backtest/py.typed diff --git a/makefiles/local.mk b/makefiles/local.mk index ba00ce9..ccfb797 100644 --- a/makefiles/local.mk +++ b/makefiles/local.mk @@ -2,7 +2,7 @@ bandit-local: ##@lint Run bandit bandit-local: files ?= ${SERVICE} bandit-local: - ${POETRY} run bandit -r ${files} + ${POETRY} run bandit -r ${files} -c pyproject.toml .PHONY: black-local black-local: ##@lint Run black diff --git a/poetry.lock b/poetry.lock index d07042d..c088f06 100644 --- a/poetry.lock +++ b/poetry.lock @@ -92,13 +92,13 @@ uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "bokeh" -version = "3.4.1" +version = "3.4.2" description = "Interactive plots and applications in the browser from Python" optional = false python-versions = ">=3.9" files = [ - {file = "bokeh-3.4.1-py3-none-any.whl", 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21:00:00,1.19574,1.19586,1.19472,1.19474,690 +2018-01-10 22:00:00,1.19479,1.19532,1.19461,1.19494,580 +2018-01-10 23:00:00,1.19494,1.19592,1.19492,1.19562,402 +2018-01-11 00:00:00,1.19561,1.19604,1.19474,1.19604,1545 +2018-01-11 01:00:00,1.19604,1.19629,1.19542,1.19597,1556 +2018-01-11 02:00:00,1.19595,1.19692,1.19566,1.19668,814 +2018-01-11 03:00:00,1.19665,1.19706,1.19453,1.19536,2059 +2018-01-11 04:00:00,1.19534,1.19548,1.19414,1.1947,1169 +2018-01-11 05:00:00,1.1947,1.19541,1.19412,1.19521,1048 +2018-01-11 06:00:00,1.19521,1.19521,1.19365,1.19424,1048 +2018-01-11 07:00:00,1.19424,1.19499,1.19297,1.194,2273 +2018-01-11 08:00:00,1.19398,1.19418,1.19295,1.19378,2339 +2018-01-11 09:00:00,1.19377,1.19495,1.19331,1.19477,2210 +2018-01-11 10:00:00,1.19478,1.19518,1.1939,1.19466,1864 +2018-01-11 11:00:00,1.1947,1.19508,1.19406,1.19435,1468 +2018-01-11 12:00:00,1.19437,1.2013,1.19364,1.20044,9176 +2018-01-11 13:00:00,1.20048,1.20353,1.20026,1.20314,9406 +2018-01-11 14:00:00,1.20312,1.20489,1.2031,1.2048,4285 +2018-01-11 15:00:00,1.2048,1.20592,1.20394,1.20492,4332 +2018-01-11 16:00:00,1.20496,1.20496,1.2032,1.20343,2620 +2018-01-11 17:00:00,1.20342,1.2041,1.20313,1.20378,1605 +2018-01-11 18:00:00,1.20384,1.20476,1.20304,1.2037,1974 +2018-01-11 19:00:00,1.20368,1.20456,1.2034,1.20387,1036 +2018-01-11 20:00:00,1.20382,1.20398,1.20276,1.20311,796 +2018-01-11 21:00:00,1.2031,1.2035,1.20282,1.2032,811 +2018-01-11 22:00:00,1.20332,1.20408,1.20315,1.20386,854 +2018-01-11 23:00:00,1.20384,1.2044,1.20308,1.20431,918 +2018-01-12 00:00:00,1.20436,1.20669,1.20417,1.20586,2966 +2018-01-12 01:00:00,1.20584,1.20616,1.20432,1.20455,1378 +2018-01-12 02:00:00,1.20452,1.20508,1.2042,1.20471,844 +2018-01-12 03:00:00,1.20473,1.20532,1.20458,1.20516,680 +2018-01-12 04:00:00,1.20512,1.2055,1.20458,1.20536,669 +2018-01-12 05:00:00,1.2054,1.20573,1.20403,1.20444,685 +2018-01-12 06:00:00,1.20442,1.20526,1.20424,1.20482,934 +2018-01-12 07:00:00,1.20477,1.2076,1.20454,1.20626,3649 +2018-01-12 08:00:00,1.20628,1.21208,1.2052,1.21114,6783 +2018-01-12 09:00:00,1.21115,1.21368,1.21109,1.21253,5139 +2018-01-12 10:00:00,1.21258,1.21293,1.21148,1.21187,2153 +2018-01-12 11:00:00,1.21188,1.21358,1.21188,1.21246,2167 +2018-01-12 12:00:00,1.21251,1.21382,1.21228,1.21331,2179 +2018-01-12 13:00:00,1.21332,1.21493,1.2112,1.21202,9629 +2018-01-12 14:00:00,1.21203,1.21492,1.21112,1.21382,5906 +2018-01-12 15:00:00,1.21382,1.21553,1.2133,1.21482,4987 +2018-01-12 16:00:00,1.21482,1.21557,1.2122,1.21302,5546 +2018-01-12 17:00:00,1.21305,1.21371,1.21242,1.21344,2483 +2018-01-12 18:00:00,1.21346,1.21668,1.2133,1.21627,3430 +2018-01-12 19:00:00,1.21624,1.21846,1.21608,1.21809,3402 +2018-01-12 20:00:00,1.21812,1.21884,1.21768,1.21872,1389 +2018-01-12 21:00:00,1.21878,1.22193,1.2187,1.21968,3851 +2018-01-14 22:00:00,1.21935,1.22089,1.21931,1.22036,1308 +2018-01-14 23:00:00,1.22034,1.22124,1.21909,1.21919,1835 +2018-01-15 00:00:00,1.21918,1.21988,1.21878,1.21909,2576 +2018-01-15 01:00:00,1.21906,1.22088,1.21892,1.21986,3016 +2018-01-15 02:00:00,1.21986,1.22082,1.21924,1.21947,2009 +2018-01-15 03:00:00,1.21942,1.22046,1.2193,1.22001,1561 +2018-01-15 04:00:00,1.21997,1.22113,1.21962,1.22102,1346 +2018-01-15 05:00:00,1.221,1.224,1.2208,1.22228,4610 +2018-01-15 06:00:00,1.22228,1.22301,1.22076,1.22087,3372 +2018-01-15 07:00:00,1.22086,1.22202,1.22012,1.22117,3001 +2018-01-15 08:00:00,1.22114,1.22348,1.22096,1.22309,2685 +2018-01-15 09:00:00,1.22308,1.22698,1.22288,1.22604,3836 +2018-01-15 10:00:00,1.226,1.22968,1.22576,1.22744,4236 +2018-01-15 11:00:00,1.22743,1.22824,1.22522,1.22554,2561 +2018-01-15 12:00:00,1.22554,1.22725,1.22513,1.22696,1797 +2018-01-15 13:00:00,1.22701,1.22865,1.22654,1.2283,2509 +2018-01-15 14:00:00,1.2283,1.22912,1.22598,1.2262,2560 +2018-01-15 15:00:00,1.22618,1.22714,1.22546,1.22598,2237 +2018-01-15 16:00:00,1.22598,1.22938,1.22592,1.2266,4140 +2018-01-15 17:00:00,1.22664,1.22878,1.22664,1.22719,1097 +2018-01-15 18:00:00,1.22725,1.22769,1.2268,1.22728,960 +2018-01-15 19:00:00,1.22726,1.22746,1.22633,1.22688,1299 +2018-01-15 20:00:00,1.22694,1.22784,1.22633,1.22694,2467 +2018-01-15 21:00:00,1.22693,1.22699,1.22632,1.22636,1104 +2018-01-15 22:00:00,1.22655,1.22678,1.22622,1.2265,423 +2018-01-15 23:00:00,1.22656,1.22753,1.22615,1.22668,1185 +2018-01-16 00:00:00,1.2267,1.22698,1.22604,1.2262,1375 +2018-01-16 01:00:00,1.22622,1.22659,1.22477,1.22655,1908 +2018-01-16 02:00:00,1.22651,1.22798,1.22588,1.22678,2016 +2018-01-16 03:00:00,1.22672,1.22696,1.22555,1.22573,1179 +2018-01-16 04:00:00,1.22574,1.22705,1.22574,1.2267,1051 +2018-01-16 05:00:00,1.22668,1.227,1.22616,1.2263,768 +2018-01-16 06:00:00,1.2263,1.22832,1.22581,1.22674,2357 +2018-01-16 07:00:00,1.22674,1.22682,1.22156,1.22466,10486 +2018-01-16 08:00:00,1.22465,1.22678,1.22227,1.2236,4599 +2018-01-16 09:00:00,1.22356,1.2241,1.22222,1.22332,3188 +2018-01-16 10:00:00,1.22334,1.22389,1.22018,1.22132,5283 +2018-01-16 11:00:00,1.22137,1.2224,1.22048,1.22158,1978 +2018-01-16 12:00:00,1.22156,1.22406,1.22146,1.22324,2043 +2018-01-16 13:00:00,1.22322,1.22357,1.22123,1.2218,2566 +2018-01-16 14:00:00,1.22182,1.22184,1.21952,1.22092,4724 +2018-01-16 15:00:00,1.2209,1.22344,1.2207,1.22296,3636 +2018-01-16 16:00:00,1.22296,1.22486,1.2225,1.22446,2873 +2018-01-16 17:00:00,1.22443,1.22456,1.22335,1.22437,2068 +2018-01-16 18:00:00,1.22441,1.22695,1.22432,1.22674,1976 +2018-01-16 19:00:00,1.22674,1.2281,1.22634,1.22716,2354 +2018-01-16 20:00:00,1.22716,1.22744,1.22649,1.22664,1327 +2018-01-16 21:00:00,1.2266,1.22665,1.22544,1.22607,720 +2018-01-16 22:00:00,1.22591,1.22642,1.2254,1.22562,1113 +2018-01-16 23:00:00,1.22564,1.22774,1.22564,1.22708,1207 +2018-01-17 00:00:00,1.22705,1.2323,1.22638,1.23034,6019 +2018-01-17 01:00:00,1.2304,1.2306,1.22852,1.22911,4049 +2018-01-17 02:00:00,1.22907,1.22972,1.22674,1.22684,2513 +2018-01-17 03:00:00,1.22688,1.22755,1.2259,1.22672,2314 +2018-01-17 04:00:00,1.22672,1.22702,1.22486,1.22494,2208 +2018-01-17 05:00:00,1.22496,1.22542,1.2237,1.22439,2581 +2018-01-17 06:00:00,1.22439,1.22514,1.22148,1.22201,3325 +2018-01-17 07:00:00,1.22203,1.22353,1.22084,1.22172,5452 +2018-01-17 08:00:00,1.22174,1.22442,1.22112,1.22268,5240 +2018-01-17 09:00:00,1.22264,1.22439,1.22166,1.22366,3126 +2018-01-17 10:00:00,1.22372,1.22503,1.22324,1.22344,2907 +2018-01-17 11:00:00,1.22343,1.2237,1.22055,1.2207,2521 +2018-01-17 12:00:00,1.22069,1.22144,1.2201,1.22095,2195 +2018-01-17 13:00:00,1.22096,1.22232,1.21964,1.22194,3596 +2018-01-17 14:00:00,1.2219,1.22298,1.22128,1.22216,3855 +2018-01-17 15:00:00,1.22216,1.22456,1.22161,1.22428,4933 +2018-01-17 16:00:00,1.22427,1.22447,1.22256,1.22288,3177 +2018-01-17 17:00:00,1.22285,1.22536,1.22272,1.2252,2059 +2018-01-17 18:00:00,1.22518,1.2288,1.22501,1.22768,3954 +2018-01-17 19:00:00,1.22766,1.22766,1.22357,1.22376,3769 +2018-01-17 20:00:00,1.22371,1.22385,1.22089,1.22131,4593 +2018-01-17 21:00:00,1.22133,1.2218,1.21776,1.21854,3194 +2018-01-17 22:00:00,1.21872,1.21922,1.21656,1.21656,2343 +2018-01-17 23:00:00,1.21653,1.21883,1.21653,1.21803,1293 +2018-01-18 00:00:00,1.21809,1.22046,1.2179,1.21901,4246 +2018-01-18 01:00:00,1.21906,1.21974,1.218,1.2193,2496 +2018-01-18 02:00:00,1.21925,1.22016,1.21908,1.21943,2011 +2018-01-18 03:00:00,1.21942,1.21949,1.21735,1.21798,1840 +2018-01-18 04:00:00,1.21794,1.21968,1.21788,1.21948,1616 +2018-01-18 05:00:00,1.21954,1.2209,1.21942,1.2207,2315 +2018-01-18 06:00:00,1.2207,1.22097,1.21962,1.2207,2156 +2018-01-18 07:00:00,1.22076,1.22124,1.21864,1.22064,3502 +2018-01-18 08:00:00,1.22064,1.22178,1.2202,1.2204,2946 +2018-01-18 09:00:00,1.2204,1.2218,1.21961,1.22144,2226 +2018-01-18 10:00:00,1.22146,1.22295,1.22126,1.22279,2055 +2018-01-18 11:00:00,1.2228,1.22472,1.22274,1.224,2420 +2018-01-18 12:00:00,1.22397,1.22528,1.22339,1.22394,2502 +2018-01-18 13:00:00,1.22394,1.22503,1.2227,1.22489,2964 +2018-01-18 14:00:00,1.2249,1.2265,1.22419,1.22606,3310 +2018-01-18 15:00:00,1.22607,1.22607,1.22308,1.22392,4079 +2018-01-18 16:00:00,1.2239,1.22546,1.22269,1.22382,5483 +2018-01-18 17:00:00,1.22386,1.22556,1.22208,1.22283,3083 +2018-01-18 18:00:00,1.22283,1.22359,1.22199,1.2226,2458 +2018-01-18 19:00:00,1.22266,1.22448,1.22248,1.22434,1672 +2018-01-18 20:00:00,1.22434,1.22475,1.22264,1.22386,2202 +2018-01-18 21:00:00,1.22386,1.22436,1.22368,1.2239,1060 +2018-01-18 22:00:00,1.2237,1.22444,1.22334,1.22409,885 +2018-01-18 23:00:00,1.22412,1.22466,1.22322,1.2234,1274 +2018-01-19 00:00:00,1.2234,1.22542,1.22324,1.22368,3295 +2018-01-19 01:00:00,1.22366,1.22457,1.2232,1.22436,2560 +2018-01-19 02:00:00,1.22442,1.22564,1.22404,1.22448,2669 +2018-01-19 03:00:00,1.22454,1.22704,1.22436,1.22667,2546 +2018-01-19 04:00:00,1.22666,1.2267,1.22596,1.22625,1310 +2018-01-19 05:00:00,1.2263,1.22638,1.22536,1.2261,929 +2018-01-19 06:00:00,1.2261,1.22684,1.22576,1.22593,1916 +2018-01-19 07:00:00,1.22588,1.22796,1.22514,1.22718,3556 +2018-01-19 08:00:00,1.22713,1.22852,1.22624,1.22832,3888 +2018-01-19 09:00:00,1.22831,1.22954,1.22649,1.22816,3843 +2018-01-19 10:00:00,1.22815,1.22842,1.22666,1.22742,2912 +2018-01-19 11:00:00,1.22744,1.22774,1.22561,1.22731,2346 +2018-01-19 12:00:00,1.22726,1.22726,1.22532,1.22572,2070 +2018-01-19 13:00:00,1.22578,1.22696,1.22392,1.22435,6699 +2018-01-19 14:00:00,1.22431,1.22529,1.22304,1.22503,4743 +2018-01-19 15:00:00,1.22503,1.22576,1.22183,1.22208,5010 +2018-01-19 16:00:00,1.22211,1.22392,1.22206,1.22372,2674 +2018-01-19 17:00:00,1.22372,1.22436,1.22311,1.22328,1890 +2018-01-19 18:00:00,1.22328,1.22328,1.22191,1.22324,1563 +2018-01-19 19:00:00,1.22326,1.22386,1.22316,1.22328,1412 +2018-01-19 20:00:00,1.22328,1.22347,1.22204,1.22212,1174 +2018-01-19 21:00:00,1.2221,1.22338,1.22152,1.22211,2661 +2018-01-21 22:00:00,1.22716,1.22743,1.22552,1.22591,1121 +2018-01-21 23:00:00,1.22594,1.22602,1.22342,1.22562,2248 +2018-01-22 00:00:00,1.22562,1.22574,1.22413,1.22442,2370 +2018-01-22 01:00:00,1.2244,1.22448,1.22253,1.2229,3227 +2018-01-22 02:00:00,1.22287,1.22377,1.22265,1.22366,1885 +2018-01-22 03:00:00,1.22362,1.22376,1.22248,1.2229,1073 +2018-01-22 04:00:00,1.22288,1.223,1.22165,1.2224,1641 +2018-01-22 05:00:00,1.22237,1.2233,1.22174,1.22319,1445 +2018-01-22 06:00:00,1.22316,1.22342,1.22141,1.22161,2125 +2018-01-22 07:00:00,1.22162,1.22427,1.22156,1.22374,3147 +2018-01-22 08:00:00,1.2238,1.225,1.22355,1.22418,2631 +2018-01-22 09:00:00,1.22422,1.2256,1.2242,1.22495,1695 +2018-01-22 10:00:00,1.22498,1.22671,1.22478,1.22621,1932 +2018-01-22 11:00:00,1.22624,1.2263,1.22513,1.22552,1431 +2018-01-22 12:00:00,1.2255,1.22567,1.2239,1.22414,1314 +2018-01-22 13:00:00,1.22414,1.22519,1.22336,1.22494,1691 +2018-01-22 14:00:00,1.22498,1.22587,1.22384,1.22402,2521 +2018-01-22 15:00:00,1.22404,1.22608,1.22386,1.22537,2677 +2018-01-22 16:00:00,1.22535,1.22549,1.2228,1.2228,2934 +2018-01-22 17:00:00,1.22281,1.22448,1.2224,1.22438,2860 +2018-01-22 18:00:00,1.22438,1.2251,1.22392,1.22494,1295 +2018-01-22 19:00:00,1.22498,1.22614,1.22478,1.22584,1325 +2018-01-22 20:00:00,1.22586,1.22606,1.22546,1.22588,1002 +2018-01-22 21:00:00,1.22588,1.2263,1.2257,1.22614,564 +2018-01-22 22:00:00,1.22614,1.22648,1.22571,1.226,967 +2018-01-22 23:00:00,1.22598,1.22603,1.22555,1.22564,1299 +2018-01-23 00:00:00,1.22562,1.22732,1.22556,1.22674,1313 +2018-01-23 01:00:00,1.22672,1.22756,1.22626,1.22664,1515 +2018-01-23 02:00:00,1.22662,1.22674,1.22512,1.22615,1250 +2018-01-23 03:00:00,1.22611,1.22759,1.22548,1.22578,4124 +2018-01-23 04:00:00,1.22573,1.22651,1.22551,1.22596,1189 +2018-01-23 05:00:00,1.22598,1.22608,1.22515,1.22581,1066 +2018-01-23 06:00:00,1.22581,1.2271,1.22443,1.22482,3058 +2018-01-23 07:00:00,1.2248,1.22565,1.22384,1.22512,3427 +2018-01-23 08:00:00,1.22514,1.2253,1.2223,1.22386,3903 +2018-01-23 09:00:00,1.22382,1.22456,1.22312,1.22376,2345 +2018-01-23 10:00:00,1.22374,1.22546,1.22374,1.22465,2376 +2018-01-23 11:00:00,1.22468,1.22576,1.22364,1.22364,2334 +2018-01-23 12:00:00,1.22366,1.22538,1.22338,1.22494,2294 +2018-01-23 13:00:00,1.22496,1.22651,1.22458,1.22586,2634 +2018-01-23 14:00:00,1.2259,1.22833,1.22516,1.22784,3708 +2018-01-23 15:00:00,1.22786,1.23062,1.22768,1.2293,5201 +2018-01-23 16:00:00,1.22929,1.22947,1.22706,1.22763,3521 +2018-01-23 17:00:00,1.22758,1.22902,1.22753,1.2279,2019 +2018-01-23 18:00:00,1.22791,1.22896,1.2276,1.22808,1890 +2018-01-23 19:00:00,1.22806,1.22956,1.228,1.22956,1611 +2018-01-23 20:00:00,1.22955,1.2297,1.22883,1.22938,825 +2018-01-23 21:00:00,1.22934,1.22998,1.22928,1.2299,746 +2018-01-23 22:00:00,1.23004,1.23004,1.22959,1.22974,305 +2018-01-23 23:00:00,1.22968,1.23158,1.2294,1.23092,1693 +2018-01-24 00:00:00,1.23092,1.2313,1.22914,1.23003,2169 +2018-01-24 01:00:00,1.22997,1.23121,1.22932,1.2307,2212 +2018-01-24 02:00:00,1.2307,1.23184,1.23016,1.231,3715 +2018-01-24 03:00:00,1.23098,1.23164,1.23015,1.23143,1687 +2018-01-24 04:00:00,1.23146,1.23356,1.23146,1.23214,2807 +2018-01-24 05:00:00,1.23212,1.23255,1.2314,1.23249,1368 +2018-01-24 06:00:00,1.23246,1.23291,1.23067,1.23092,3173 +2018-01-24 07:00:00,1.23092,1.23198,1.23026,1.23124,3455 +2018-01-24 08:00:00,1.23125,1.23449,1.23114,1.23404,5805 +2018-01-24 09:00:00,1.23404,1.23563,1.23367,1.23369,5641 +2018-01-24 10:00:00,1.23368,1.23482,1.23341,1.23374,3304 +2018-01-24 11:00:00,1.23374,1.2349,1.23296,1.234,3164 +2018-01-24 12:00:00,1.23401,1.23458,1.23305,1.23384,2801 +2018-01-24 13:00:00,1.23384,1.23679,1.23384,1.23658,7281 +2018-01-24 14:00:00,1.23654,1.23966,1.2363,1.23925,5598 +2018-01-24 15:00:00,1.23927,1.24022,1.23802,1.23808,5367 +2018-01-24 16:00:00,1.23814,1.23972,1.23766,1.23897,4256 +2018-01-24 17:00:00,1.23893,1.23963,1.23824,1.23915,2432 +2018-01-24 18:00:00,1.23917,1.24149,1.23902,1.24126,3465 +2018-01-24 19:00:00,1.24122,1.24154,1.23978,1.24048,2544 +2018-01-24 20:00:00,1.24047,1.24062,1.23946,1.2399,1624 +2018-01-24 21:00:00,1.2399,1.24101,1.23978,1.2408,1573 +2018-01-24 22:00:00,1.24104,1.24109,1.24006,1.2405,1216 +2018-01-24 23:00:00,1.24048,1.24049,1.23902,1.2393,1043 +2018-01-25 00:00:00,1.23926,1.24002,1.23845,1.23985,2900 +2018-01-25 01:00:00,1.23986,1.2411,1.23894,1.24104,2965 +2018-01-25 02:00:00,1.24102,1.24282,1.24056,1.24231,4617 +2018-01-25 03:00:00,1.2423,1.24401,1.24202,1.24314,5198 +2018-01-25 04:00:00,1.24312,1.24392,1.24258,1.24364,2532 +2018-01-25 05:00:00,1.24362,1.24487,1.2426,1.2448,2441 +2018-01-25 06:00:00,1.2448,1.24596,1.24228,1.24357,5894 +2018-01-25 07:00:00,1.24352,1.24422,1.2409,1.24194,12088 +2018-01-25 08:00:00,1.24191,1.24195,1.2389,1.23968,7607 +2018-01-25 09:00:00,1.2397,1.24332,1.2397,1.24318,4369 +2018-01-25 10:00:00,1.24316,1.24324,1.2408,1.24134,3774 +2018-01-25 11:00:00,1.24133,1.24212,1.23987,1.24034,2468 +2018-01-25 12:00:00,1.2403,1.24159,1.23972,1.24044,3963 +2018-01-25 13:00:00,1.24045,1.24984,1.24022,1.24972,24445 +2018-01-25 14:00:00,1.24973,1.25374,1.24623,1.24899,21503 +2018-01-25 15:00:00,1.24898,1.25301,1.2484,1.25039,10393 +2018-01-25 16:00:00,1.25041,1.25069,1.24838,1.24871,4975 +2018-01-25 17:00:00,1.24866,1.24922,1.24774,1.24922,3503 +2018-01-25 18:00:00,1.24923,1.25065,1.24734,1.24844,5107 +2018-01-25 19:00:00,1.24846,1.24875,1.23642,1.23904,31054 +2018-01-25 20:00:00,1.23905,1.24312,1.23884,1.24065,9978 +2018-01-25 21:00:00,1.2407,1.2423,1.23874,1.2398,3213 +2018-01-25 22:00:00,1.2394,1.24014,1.23699,1.2373,1307 +2018-01-25 23:00:00,1.23718,1.23959,1.23716,1.23912,2730 +2018-01-26 00:00:00,1.23914,1.24108,1.2386,1.2406,3564 +2018-01-26 01:00:00,1.24058,1.24332,1.24033,1.24306,4653 +2018-01-26 02:00:00,1.24304,1.24304,1.24123,1.24272,4517 +2018-01-26 03:00:00,1.24272,1.24318,1.24224,1.24294,2188 +2018-01-26 04:00:00,1.24294,1.24315,1.24204,1.24213,999 +2018-01-26 05:00:00,1.24212,1.24326,1.24131,1.24313,1688 +2018-01-26 06:00:00,1.24312,1.24526,1.24284,1.24508,4061 +2018-01-26 07:00:00,1.24508,1.2494,1.24477,1.24745,7990 +2018-01-26 08:00:00,1.2475,1.24908,1.2452,1.24668,6098 +2018-01-26 09:00:00,1.2467,1.24678,1.2452,1.24556,4570 +2018-01-26 10:00:00,1.24558,1.24671,1.24423,1.2459,4104 +2018-01-26 11:00:00,1.24594,1.24652,1.24298,1.24386,4397 +2018-01-26 12:00:00,1.24382,1.24502,1.24344,1.24408,4107 +2018-01-26 13:00:00,1.24408,1.24576,1.24207,1.24286,7873 +2018-01-26 14:00:00,1.24287,1.24478,1.24127,1.24412,9288 +2018-01-26 15:00:00,1.24416,1.24458,1.24155,1.2433,6780 +2018-01-26 16:00:00,1.2433,1.24374,1.24077,1.24216,6574 +2018-01-26 17:00:00,1.24216,1.2442,1.2416,1.24388,4712 +2018-01-26 18:00:00,1.24387,1.24505,1.24334,1.24446,2989 +2018-01-26 19:00:00,1.24447,1.2448,1.24176,1.24208,7796 +2018-01-26 20:00:00,1.24207,1.24235,1.24059,1.24196,2627 +2018-01-26 21:00:00,1.24196,1.24321,1.24174,1.24296,2200 +2018-01-28 22:00:00,1.2428,1.2428,1.24134,1.24164,755 +2018-01-28 23:00:00,1.24164,1.24311,1.24161,1.2431,1552 +2018-01-29 00:00:00,1.24304,1.24324,1.24207,1.2421,2431 +2018-01-29 01:00:00,1.24212,1.2422,1.23956,1.23968,4632 +2018-01-29 02:00:00,1.23967,1.24014,1.23852,1.23997,3975 +2018-01-29 03:00:00,1.23996,1.24195,1.23982,1.24152,3504 +2018-01-29 04:00:00,1.24156,1.24221,1.24117,1.2413,1067 +2018-01-29 05:00:00,1.24135,1.24191,1.24054,1.24142,2235 +2018-01-29 06:00:00,1.24142,1.2427,1.24046,1.24158,3341 +2018-01-29 07:00:00,1.24158,1.24292,1.23944,1.24018,5236 +2018-01-29 08:00:00,1.2402,1.24096,1.23884,1.24071,4379 +2018-01-29 09:00:00,1.24073,1.24166,1.23942,1.24119,3991 +2018-01-29 10:00:00,1.24124,1.2428,1.24037,1.24037,3256 +2018-01-29 11:00:00,1.24032,1.24044,1.23912,1.23934,2338 +2018-01-29 12:00:00,1.2393,1.24043,1.23772,1.23846,2968 +2018-01-29 13:00:00,1.23842,1.23893,1.2359,1.23647,4045 +2018-01-29 14:00:00,1.23648,1.23714,1.23452,1.23517,4145 +2018-01-29 15:00:00,1.23518,1.23742,1.23498,1.23563,4324 +2018-01-29 16:00:00,1.23563,1.2368,1.2337,1.23522,7734 +2018-01-29 17:00:00,1.23523,1.2373,1.23448,1.23718,3241 +2018-01-29 18:00:00,1.23719,1.23802,1.2369,1.23781,2005 +2018-01-29 19:00:00,1.2378,1.23902,1.23734,1.23888,2067 +2018-01-29 20:00:00,1.23888,1.23899,1.2381,1.23825,1450 +2018-01-29 21:00:00,1.2382,1.23838,1.2378,1.23827,620 +2018-01-29 22:00:00,1.2381,1.23861,1.23778,1.23823,1043 +2018-01-29 23:00:00,1.23826,1.23866,1.23784,1.23808,1004 +2018-01-30 00:00:00,1.23809,1.23863,1.23684,1.23763,2660 +2018-01-30 01:00:00,1.23766,1.23884,1.23729,1.2385,2669 +2018-01-30 02:00:00,1.2385,1.2385,1.23601,1.23694,3793 +2018-01-30 03:00:00,1.23698,1.23837,1.23664,1.23785,2606 +2018-01-30 04:00:00,1.23784,1.23866,1.2371,1.23717,3131 +2018-01-30 05:00:00,1.23718,1.23763,1.23601,1.2364,2048 +2018-01-30 06:00:00,1.23635,1.23656,1.2347,1.23484,2557 +2018-01-30 07:00:00,1.23481,1.23705,1.2348,1.23555,3429 +2018-01-30 08:00:00,1.23554,1.23848,1.23349,1.23824,5082 +2018-01-30 09:00:00,1.23822,1.24076,1.23772,1.23986,6087 +2018-01-30 10:00:00,1.23988,1.24242,1.23947,1.24126,4784 +2018-01-30 11:00:00,1.24126,1.24414,1.24087,1.24396,3446 +2018-01-30 12:00:00,1.2439,1.24395,1.24178,1.24264,3480 +2018-01-30 13:00:00,1.2427,1.24482,1.24034,1.24454,4536 +2018-01-30 14:00:00,1.24454,1.24543,1.24312,1.24418,5943 +2018-01-30 15:00:00,1.2442,1.2443,1.2403,1.24103,6573 +2018-01-30 16:00:00,1.24102,1.24205,1.23838,1.23907,5325 +2018-01-30 17:00:00,1.23908,1.24079,1.2386,1.24052,2888 +2018-01-30 18:00:00,1.24056,1.24066,1.2384,1.23956,2694 +2018-01-30 19:00:00,1.2396,1.24058,1.23894,1.24056,2370 +2018-01-30 20:00:00,1.24056,1.24062,1.23939,1.23942,1114 +2018-01-30 21:00:00,1.2394,1.24036,1.2394,1.24024,594 +2018-01-30 22:00:00,1.24028,1.24058,1.2401,1.24052,739 +2018-01-30 23:00:00,1.24046,1.24135,1.23962,1.24085,1263 +2018-01-31 00:00:00,1.24082,1.24248,1.24066,1.24177,3571 +2018-01-31 01:00:00,1.24176,1.24208,1.24019,1.24147,4426 +2018-01-31 02:00:00,1.24146,1.24152,1.23988,1.2414,4356 +2018-01-31 03:00:00,1.24142,1.24338,1.2414,1.24236,4803 +2018-01-31 04:00:00,1.24238,1.24279,1.24152,1.24196,3012 +2018-01-31 05:00:00,1.24198,1.2438,1.24178,1.24372,2586 +2018-01-31 06:00:00,1.24372,1.24504,1.24334,1.24494,3378 +2018-01-31 07:00:00,1.24488,1.24628,1.24347,1.24444,5822 +2018-01-31 08:00:00,1.24444,1.2451,1.24251,1.24376,4251 +2018-01-31 09:00:00,1.24373,1.24561,1.24332,1.24512,4786 +2018-01-31 10:00:00,1.24512,1.24601,1.24394,1.24442,4322 +2018-01-31 11:00:00,1.24442,1.24561,1.24412,1.24546,2263 +2018-01-31 12:00:00,1.24544,1.24602,1.24458,1.24595,2336 +2018-01-31 13:00:00,1.24598,1.24728,1.24482,1.2465,5219 +2018-01-31 14:00:00,1.2465,1.2466,1.2445,1.24586,3988 +2018-01-31 15:00:00,1.24586,1.24748,1.24528,1.24564,5840 +2018-01-31 16:00:00,1.2457,1.24634,1.2424,1.24272,5895 +2018-01-31 17:00:00,1.24276,1.2437,1.24068,1.2415,3282 +2018-01-31 18:00:00,1.24154,1.24232,1.24089,1.24183,3171 +2018-01-31 19:00:00,1.24187,1.24384,1.2387,1.24112,17390 +2018-01-31 20:00:00,1.24112,1.2424,1.2402,1.2415,5015 +2018-01-31 21:00:00,1.2415,1.24176,1.24096,1.24138,882 +2018-01-31 22:00:00,1.24098,1.24148,1.24046,1.24122,1411 +2018-01-31 23:00:00,1.24128,1.24226,1.24122,1.24166,876 +2018-02-01 00:00:00,1.24169,1.24289,1.24165,1.2421,1831 +2018-02-01 01:00:00,1.2421,1.24266,1.24056,1.24192,2936 +2018-02-01 02:00:00,1.2419,1.2428,1.2415,1.24175,1625 +2018-02-01 03:00:00,1.24176,1.2426,1.24145,1.24246,1265 +2018-02-01 04:00:00,1.24246,1.24286,1.2417,1.24218,1063 +2018-02-01 05:00:00,1.24216,1.24282,1.24186,1.24211,1094 +2018-02-01 06:00:00,1.24208,1.24224,1.23934,1.23938,3482 +2018-02-01 07:00:00,1.23942,1.24046,1.23849,1.24029,5339 +2018-02-01 08:00:00,1.24028,1.24394,1.24021,1.24284,5876 +2018-02-01 09:00:00,1.24279,1.245,1.24278,1.24463,4987 +2018-02-01 10:00:00,1.2446,1.24512,1.24286,1.243,3100 +2018-02-01 11:00:00,1.24302,1.24382,1.24246,1.24379,2997 +2018-02-01 12:00:00,1.24374,1.24602,1.24324,1.24539,4027 +2018-02-01 13:00:00,1.24541,1.24622,1.24444,1.24496,5012 +2018-02-01 14:00:00,1.24495,1.24536,1.2437,1.24425,4274 +2018-02-01 15:00:00,1.24423,1.24745,1.24316,1.24696,7045 +2018-02-01 16:00:00,1.24696,1.2489,1.24624,1.24812,6037 +2018-02-01 17:00:00,1.24812,1.24984,1.24749,1.24784,4718 +2018-02-01 18:00:00,1.24787,1.24954,1.24776,1.24938,2794 +2018-02-01 19:00:00,1.24933,1.25067,1.24836,1.2503,4106 +2018-02-01 20:00:00,1.25031,1.25233,1.25012,1.2515,5909 +2018-02-01 21:00:00,1.25144,1.25182,1.25046,1.25079,1983 +2018-02-01 22:00:00,1.25135,1.25135,1.25028,1.25056,1161 +2018-02-01 23:00:00,1.25057,1.25158,1.25052,1.25106,1294 +2018-02-02 00:00:00,1.25108,1.25126,1.24978,1.25072,1626 +2018-02-02 01:00:00,1.25066,1.25149,1.2492,1.24994,5434 +2018-02-02 02:00:00,1.24995,1.25044,1.2489,1.2494,2742 +2018-02-02 03:00:00,1.24934,1.25006,1.24924,1.25001,1737 +2018-02-02 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+2013-02-20,805.3,808.97,791.79,792.46,2764200 +2013-02-21,798,805.45,791.22,795.53,3506400 +2013-02-22,799.26,801.25,793.8,799.71,2053900 +2013-02-25,802.3,808.41,790.49,790.77,2303900 +2013-02-26,795,795.95,784.4,790.13,2202500 +2013-02-27,794.8,804.75,791.11,799.78,2026100 +2013-02-28,801.1,806.99,801.03,801.2,2265800 +2013-03-01,797.8,807.14,796.15,806.19,2175400 diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py index e69de29..3109573 100644 --- a/tests/unit/__init__.py +++ b/tests/unit/__init__.py @@ -0,0 +1,28 @@ +"""Data and utilities for testing.""" + +import pandas as pd + + +def _read_file(filename): + from os.path import dirname, join + + return pd.read_csv( + join(dirname(__file__), filename), + index_col=0, + parse_dates=True, + infer_datetime_format=True, + ) + + +GOOG = _read_file("GOOG.csv") +"""DataFrame of daily NASDAQ:GOOG (Google/Alphabet) stock price data from 2004 to 2013.""" + +EURUSD = _read_file("EURUSD.csv") +"""DataFrame of hourly EUR/USD forex data from April 2017 to February 2018.""" + + +def SMA(arr: pd.Series, n: int) -> pd.Series: + """ + Returns `n`-period simple moving average of array `arr`. + """ + return pd.Series(arr).rolling(n).mean() diff --git a/tests/unit/__main__.py b/tests/unit/__main__.py new file mode 100644 index 0000000..88a4fb9 --- /dev/null +++ b/tests/unit/__main__.py @@ -0,0 +1,7 @@ +import sys +import unittest + +suite = unittest.defaultTestLoader.discover("backtesting.test", pattern="_test*.py") +if __name__ == "__main__": + result = unittest.TextTestRunner(verbosity=2).run(suite) + sys.exit(not result.wasSuccessful()) diff --git a/tests/unit/test_backtest.py b/tests/unit/test_backtest.py new file mode 100644 index 0000000..7077712 --- /dev/null +++ b/tests/unit/test_backtest.py @@ -0,0 +1,1055 @@ +import inspect +import os +import sys +import time +import unittest +import warnings +from concurrent.futures.process import ProcessPoolExecutor +from contextlib import contextmanager +from glob import glob +from runpy import run_path +from tempfile import NamedTemporaryFile, gettempdir +from unittest import TestCase +from unittest.mock import patch + +import numpy as np +import pandas as pd +from fx_backtest import Backtest, Strategy +from fx_backtest._stats import compute_drawdown_duration_peaks +from fx_backtest._util import _Array, _as_str, _Indicator, try_ +from fx_backtest.lib import ( + OHLCV_AGG, + SignalStrategy, + TrailingStrategy, + barssince, + compute_stats, + cross, + crossover, + plot_heatmaps, + quantile, + random_ohlc_data, + resample_apply, +) +from . import EURUSD, GOOG, SMA +from pandas.testing import assert_frame_equal + +SHORT_DATA = GOOG.iloc[:20] # Short data for fast tests with no indicator lag + + +@contextmanager +def _tempfile(): + with NamedTemporaryFile(suffix=".html") as f: + if sys.platform.startswith("win"): + f.close() + yield f.name + + +@contextmanager +def chdir(path): + cwd = os.getcwd() + os.chdir(path) + try: + yield + finally: + os.chdir(cwd) + + +class SmaCross(Strategy): + # NOTE: These values are also used on the website! + fast = 10 + slow = 30 + + def init(self): + self.sma1 = self.I(SMA, self.data.Close, self.fast) + self.sma2 = self.I(SMA, self.data.Close, self.slow) + + def next(self): + if crossover(self.sma1, self.sma2): + self.position.close() + self.buy() + elif crossover(self.sma2, self.sma1): + self.position.close() + self.sell() + + +class TestBacktest(TestCase): + def test_run(self): + bt = Backtest(EURUSD, SmaCross) + bt.run() + + def test_run_invalid_param(self): + bt = Backtest(GOOG, SmaCross) + self.assertRaises(AttributeError, bt.run, foo=3) + + def test_run_speed(self): + bt = Backtest(GOOG, SmaCross) + start = time.process_time() + bt.run() + end = time.process_time() + self.assertLess(end - start, 0.3) + + def test_data_missing_columns(self): + df = GOOG.copy(deep=False) + del df["Open"] + with self.assertRaises(ValueError): + Backtest(df, SmaCross).run() + + def test_data_nan_columns(self): + df = GOOG.copy() + df["Open"] = np.nan + with self.assertRaises(ValueError): + Backtest(df, SmaCross).run() + + def test_data_extra_columns(self): + df = GOOG.copy(deep=False) + df["P/E"] = np.arange(len(df)) + df["MCap"] = np.arange(len(df)) + + class S(Strategy): + def init(self): + assert len(self.data.MCap) == len(self.data.Close) + assert len(self.data["P/E"]) == len(self.data.Close) + + def next(self): + assert len(self.data.MCap) == len(self.data.Close) + assert len(self.data["P/E"]) == len(self.data.Close) + + Backtest(df, S).run() + + def test_data_invalid(self): + with self.assertRaises(TypeError): + Backtest(GOOG.index, SmaCross).run() + with self.assertRaises(ValueError): + Backtest(GOOG.iloc[:0], SmaCross).run() + + def test_assertions(self): + class Assertive(Strategy): + def init(self): + self.sma = self.I(SMA, self.data.Close, 10) + self.remains_indicator = ( + np.r_[2] * np.cumsum(self.sma * 5 + 1) * np.r_[2] + ) + + self.transpose_invalid = self.I( + lambda: np.column_stack((self.data.Open, self.data.Close)) + ) + + resampled = resample_apply("W", SMA, self.data.Close, 3) + resampled_ind = resample_apply("W", SMA, self.sma, 3) + assert np.unique(resampled[-5:]).size == 1 + assert np.unique(resampled[-6:]).size == 2 + assert resampled in self._indicators, "Strategy.I not called" + assert resampled_ind in self._indicators, "Strategy.I not called" + + assert 1 == try_(lambda: self.data.X, 1, AttributeError) + assert 1 == try_(lambda: self.data["X"], 1, KeyError) + + assert self.data.pip == 0.01 + + assert float(self.data.Close) == self.data.Close[-1] + + def next(self, _FEW_DAYS=pd.Timedelta("3 days")): # noqa: N803 + assert self.equity >= 0 + + assert isinstance(self.sma, _Indicator) + assert isinstance(self.remains_indicator, _Indicator) + assert self.remains_indicator.name + assert isinstance(self.remains_indicator._opts, dict) + + assert not np.isnan(self.data.Open[-1]) + assert not np.isnan(self.data.High[-1]) + assert not np.isnan(self.data.Low[-1]) + assert not np.isnan(self.data.Close[-1]) + assert not np.isnan(self.data.Volume[-1]) + assert not np.isnan(self.sma[-1]) + assert self.data.index[-1] + + self.position + self.position.size + self.position.pl + self.position.pl_pct + self.position.is_long + + if crossover(self.sma, self.data.Close): + self.orders.cancel() # cancels only non-contingent + price = self.data.Close[-1] + sl, tp = 1.05 * price, 0.9 * price + + n_orders = len(self.orders) + self.sell(size=0.21, limit=price, stop=price, sl=sl, tp=tp) + assert len(self.orders) == n_orders + 1 + + order = self.orders[-1] + assert order.limit == price + assert order.stop == price + assert order.size == -0.21 + assert order.sl == sl + assert order.tp == tp + assert not order.is_contingent + + elif self.position: + assert not self.position.is_long + assert self.position.is_short + assert self.position.pl + assert self.position.pl_pct + assert self.position.size < 0 + + trade = self.trades[0] + if ( + self.data.index[-1] - self.data.index[trade.entry_bar] + > _FEW_DAYS + ): + assert not trade.is_long + assert trade.is_short + assert trade.size < 0 + assert trade.entry_bar > 0 + assert isinstance(trade.entry_time, pd.Timestamp) + assert trade.exit_bar is None + assert trade.exit_time is None + assert trade.entry_price > 0 + assert trade.exit_price is None + assert trade.pl / 1 + assert trade.pl_pct / 1 + assert trade.value > 0 + assert trade.sl + assert trade.tp + # Close multiple times + self.position.close(0.5) + self.position.close(0.5) + self.position.close(0.5) + self.position.close() + self.position.close() + + bt = Backtest(GOOG, Assertive) + with self.assertWarns(UserWarning): + stats = bt.run() + self.assertEqual(stats["# Trades"], 145) + + def test_broker_params(self): + bt = Backtest( + GOOG.iloc[:100], + SmaCross, + cash=1000, + commission=0.01, + margin=0.1, + trade_on_close=True, + ) + bt.run() + + def test_dont_overwrite_data(self): + df = EURUSD.copy() + bt = Backtest(df, SmaCross) + bt.run() + bt.optimize(fast=4, slow=[6, 8]) + bt.plot(plot_drawdown=True, open_browser=False) + self.assertTrue(df.equals(EURUSD)) + + def test_strategy_abstract(self): + class MyStrategy(Strategy): + pass + + self.assertRaises(TypeError, MyStrategy, None, None) + + def test_strategy_str(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + self.assertEqual(str(bt.run()._strategy), SmaCross.__name__) + self.assertEqual( + str(bt.run(fast=11)._strategy), SmaCross.__name__ + "(fast=11)" + ) + + def test_compute_drawdown(self): + dd = pd.Series([0, 1, 7, 0, 4, 0, 0]) + durations, peaks = compute_drawdown_duration_peaks(dd) + np.testing.assert_array_equal( + durations, pd.Series([3, 2], index=[3, 5]).reindex(dd.index) + ) + np.testing.assert_array_equal( + peaks, pd.Series([7, 4], index=[3, 5]).reindex(dd.index) + ) + + def test_compute_stats(self): + stats = Backtest(GOOG, SmaCross).run() + expected = pd.Series( + { + # NOTE: These values are also used on the website! + "# Trades": 66, + "Avg. Drawdown Duration": pd.Timedelta("41 days 00:00:00"), + "Avg. Drawdown [%]": -5.925851581948801, + "Avg. Trade Duration": pd.Timedelta("46 days 00:00:00"), + "Avg. Trade [%]": 2.531715975158555, + "Best Trade [%]": 53.59595229490424, + "Buy & Hold Return [%]": 703.4582419772772, + "Calmar Ratio": 0.4414380935608377, + "Duration": pd.Timedelta("3116 days 00:00:00"), + "End": pd.Timestamp("2013-03-01 00:00:00"), + "Equity Final [$]": 51422.98999999996, + "Equity Peak [$]": 75787.44, + "Expectancy [%]": 3.2748078066748834, + "Exposure Time [%]": 96.74115456238361, + "Max. Drawdown Duration": pd.Timedelta("584 days 00:00:00"), + "Max. Drawdown [%]": -47.98012705007589, + "Max. Trade Duration": pd.Timedelta("183 days 00:00:00"), + "Profit Factor": 2.167945974262033, + "Return (Ann.) [%]": 21.180255813792282, + "Return [%]": 414.2298999999996, + "Volatility (Ann.) [%]": 36.49390889140787, + "SQN": 1.0766187356697705, + "Kelly Criterion": 0.1518705127029717, + "Sharpe Ratio": 0.5803778344714113, + "Sortino Ratio": 1.0847880675854096, + "Start": pd.Timestamp("2004-08-19 00:00:00"), + "Win Rate [%]": 46.96969696969697, + "Worst Trade [%]": -18.39887353835481, + } + ) + + def almost_equal(a, b): + try: + return np.isclose(a, b, rtol=1.0e-8) + except TypeError: + return a == b + + diff = { + key: print(key) or value # noqa: T201 + for key, value in stats.filter(regex="^[^_]").items() + if not almost_equal(value, expected[key]) + } + self.assertDictEqual(diff, {}) + + self.assertSequenceEqual( + sorted(stats["_equity_curve"].columns), + sorted(["Equity", "DrawdownPct", "DrawdownDuration"]), + ) + + self.assertEqual(len(stats["_trades"]), 66) + + self.assertSequenceEqual( + sorted(stats["_trades"].columns), + sorted( + [ + "Size", + "EntryBar", + "ExitBar", + "EntryPrice", + "ExitPrice", + "PnL", + "ReturnPct", + "EntryTime", + "ExitTime", + "Duration", + "StopLoss", + "Tag", + "TakeProfit" + ] + ), + ) + + def test_compute_stats_bordercase(self): + + class SingleTrade(Strategy): + def init(self): + self._done = False + + def next(self): + if not self._done: + self.buy() + self._done = True + if self.position: + self.position.close() + + class SinglePosition(Strategy): + def init(self): + pass + + def next(self): + if not self.position: + self.buy() + + class NoTrade(Strategy): + def init(self): + pass + + def next(self): + pass + + for strategy in (SmaCross, SingleTrade, SinglePosition, NoTrade): + with self.subTest(strategy=strategy.__name__): + stats = Backtest(GOOG.iloc[:100], strategy).run() + + self.assertFalse(np.isnan(stats["Equity Final [$]"])) + self.assertFalse(stats["_equity_curve"]["Equity"].isnull().any()) + self.assertEqual(stats["_strategy"].__class__, strategy) + + def test_trade_enter_hit_sl_on_same_day(self): + the_day = pd.Timestamp("2012-10-17 00:00:00") + + class S(Strategy): + def init(self): + pass + + def next(self): + if self.data.index[-1] == the_day: + self.buy(sl=720) + + self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].ExitPrice, 720) + + class S(S): + def next(self): + if self.data.index[-1] == the_day: + self.buy(stop=758, sl=720) + + with self.assertWarns(UserWarning): + self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].ExitPrice, 705.58) + + def test_stop_price_between_sl_tp(self): + class S(Strategy): + def init(self): + pass + + def next(self): + if self.data.index[-1] == pd.Timestamp("2004-09-09 00:00:00"): + self.buy(stop=104, sl=103, tp=110) + + with self.assertWarns(UserWarning): + self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].EntryPrice, 104) + + def test_position_close_portion(self): + class SmaCross(Strategy): + def init(self): + self.sma1 = self.I(SMA, self.data.Close, 10) + self.sma2 = self.I(SMA, self.data.Close, 20) + + def next(self): + if not self.position and crossover(self.sma1, self.sma2): + self.buy(size=10) + if self.position and crossover(self.sma2, self.sma1): + self.position.close(portion=0.5) + + bt = Backtest(GOOG, SmaCross, commission=0.002) + bt.run() + + def test_close_orders_from_last_strategy_iteration(self): + class S(Strategy): + def init(self): + pass + + def next(self): + if not self.position: + self.buy() + elif len(self.data) == len(SHORT_DATA): + self.position.close() + + self.assertFalse(Backtest(SHORT_DATA, S).run()._trades.empty) + + def test_check_adjusted_price_when_placing_order(self): + class S(Strategy): + def init(self): + pass + + def next(self): + self.buy(tp=self.data.Close * 1.01) + + self.assertRaises(ValueError, Backtest(SHORT_DATA, S, commission=0.02).run) + + +class TestStrategy(TestCase): + def _Backtest(self, strategy_coroutine, **kwargs): + class S(Strategy): + def init(self): + self.step = strategy_coroutine(self) + + def next(self): + try_(self.step.__next__, None, StopIteration) + + return Backtest(SHORT_DATA, S, **kwargs) + + def test_position(self): + def coroutine(self): + yield self.buy() + + assert self.position + assert self.position.is_long + assert not self.position.is_short + assert self.position.size > 0 + assert self.position.pl + assert self.position.pl_pct + + yield self.position.close() + + assert not self.position + assert not self.position.is_long + assert not self.position.is_short + assert not self.position.size + assert not self.position.pl + assert not self.position.pl_pct + + self._Backtest(coroutine).run() + + def test_broker_hedging(self): + def coroutine(self): + yield self.buy(size=2) + + assert len(self.trades) == 1 + yield self.sell(size=1) + + assert len(self.trades) == 2 + + self._Backtest(coroutine, hedging=True).run() + + def test_broker_exclusive_orders(self): + def coroutine(self): + yield self.buy(size=2) + + assert len(self.trades) == 1 + yield self.sell(size=3) + + assert len(self.trades) == 1 + assert self.trades[0].size == -3 + + self._Backtest(coroutine, exclusive_orders=True).run() + + def test_trade_multiple_close(self): + def coroutine(self): + yield self.buy() + + assert self.trades + self.trades[-1].close(1) + self.trades[-1].close(0.1) + yield + + self._Backtest(coroutine).run() + + def test_close_trade_leaves_needsize_0(self): + def coroutine(self): + self.buy(size=1) + self.buy(size=1) + yield + if self.position: + self.sell(size=1) + + self._Backtest(coroutine).run() + + def test_stop_limit_order_price_is_stop_price(self): + def coroutine(self): + self.buy(stop=112, limit=113, size=1) + self.sell(stop=107, limit=105, size=1) + yield + + stats = self._Backtest(coroutine).run() + self.assertListEqual( + stats._trades.filter(like="Price").stack().tolist(), [112, 107] + ) + + def test_autoclose_trades_on_finish(self): + def coroutine(self): + yield self.buy() + + stats = self._Backtest(coroutine).run() + self.assertEqual(len(stats._trades), 1) + + def test_order_tag(self): + def coroutine(self): + yield self.buy(size=2, tag=1) + yield self.sell(size=1, tag="s") + yield self.sell(size=1) + + yield self.buy(tag=2) + yield self.position.close() + + stats = self._Backtest(coroutine).run() + self.assertEqual(list(stats._trades.Tag), [1, 1, 2]) + + +class TestOptimize(TestCase): + def test_optimize(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + OPT_PARAMS = {"fast": range(2, 5, 2), "slow": [2, 5, 7, 9]} + + self.assertRaises(ValueError, bt.optimize) + self.assertRaises(ValueError, bt.optimize, maximize="missing key", **OPT_PARAMS) + self.assertRaises(ValueError, bt.optimize, maximize="missing key", **OPT_PARAMS) + self.assertRaises(TypeError, bt.optimize, maximize=15, **OPT_PARAMS) + self.assertRaises(TypeError, bt.optimize, constraint=15, **OPT_PARAMS) + self.assertRaises( + ValueError, bt.optimize, constraint=lambda d: False, **OPT_PARAMS + ) + self.assertRaises( + ValueError, bt.optimize, return_optimization=True, **OPT_PARAMS + ) + + res = bt.optimize(**OPT_PARAMS) + self.assertIsInstance(res, pd.Series) + + default_maximize = ( + inspect.signature(Backtest.optimize).parameters["maximize"].default + ) + res2 = bt.optimize(**OPT_PARAMS, maximize=lambda s: s[default_maximize]) + self.assertDictEqual( + res.filter(regex="^[^_]").fillna(-1).to_dict(), + res2.filter(regex="^[^_]").fillna(-1).to_dict(), + ) + + res3, heatmap = bt.optimize( + **OPT_PARAMS, return_heatmap=True, constraint=lambda d: d.slow > 2 * d.fast + ) + self.assertIsInstance(heatmap, pd.Series) + self.assertEqual(len(heatmap), 4) + self.assertEqual(heatmap.name, default_maximize) + + with _tempfile() as f: + bt.plot(filename=f, open_browser=False) + + def test_method_skopt(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + res, heatmap, skopt_results = bt.optimize( + fast=range(2, 20), + slow=np.arange(2, 20, dtype=object), + constraint=lambda p: p.fast < p.slow, + max_tries=30, + method="skopt", + return_optimization=True, + return_heatmap=True, + random_state=2, + ) + self.assertIsInstance(res, pd.Series) + self.assertIsInstance(heatmap, pd.Series) + self.assertGreater(heatmap.max(), 1.1) + self.assertGreater(heatmap.min(), -2) + self.assertEqual(-skopt_results.fun, heatmap.max()) + self.assertEqual( + heatmap.index.tolist(), heatmap.dropna().index.unique().tolist() + ) + + def test_max_tries(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + OPT_PARAMS = {"fast": range(2, 10, 2), "slow": [2, 5, 7, 9]} + for method, max_tries, random_state in ( + ("grid", 5, 0), + ("grid", 0.3, 0), + ("skopt", 7, 0), + ("skopt", 0.45, 0), + ): + with self.subTest( + method=method, max_tries=max_tries, random_state=random_state + ): + _, heatmap = bt.optimize( + max_tries=max_tries, + method=method, + random_state=random_state, + return_heatmap=True, + **OPT_PARAMS + ) + self.assertEqual(len(heatmap), 6) + + def test_nowrite_df(self): + # Test we don't write into passed data df by default. + # Important for copy-on-write in Backtest.optimize() + df = EURUSD.astype(float) + _df = df.copy(deep=True) + assert _df.equals(df) + + class S(SmaCross): + def init(self): + super().init() + assert _df.equals(self.data.df) + + bt = Backtest(df, S) + _ = bt.run() + assert _df.equals(bt._data) + + def test_multiprocessing_windows_spawn(self): + df = GOOG.iloc[:100] + kw = {"fast": [10]} + + stats1 = Backtest(df, SmaCross).optimize(**kw) + with patch("multiprocessing.get_start_method", lambda **_: "spawn"): + with self.assertWarns(UserWarning) as cm: + stats2 = Backtest(df, SmaCross).optimize(**kw) + + self.assertIn("multiprocessing support", cm.warning.args[0]) + assert stats1.filter(["^_"]).equals(stats2.filter(["^_"])), (stats1, stats2) + + def test_optimize_invalid_param(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + self.assertRaises(AttributeError, bt.optimize, foo=range(3)) + self.assertRaises(ValueError, bt.optimize, fast=[]) + + def test_optimize_no_trades(self): + bt = Backtest(GOOG, SmaCross) + stats = bt.optimize(fast=[3], slow=[3]) + self.assertTrue(stats.isnull().any()) + + def test_optimize_speed(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + start = time.process_time() + bt.optimize(fast=(2, 5, 7), slow=[10, 15, 20, 30]) + end = time.process_time() + self.assertLess(end - start, 0.2) + + +class TestPlot(TestCase): + def test_plot_before_run(self): + bt = Backtest(GOOG, SmaCross) + self.assertRaises(RuntimeError, bt.plot) + + def test_file_size(self): + bt = Backtest(GOOG, SmaCross) + bt.run() + with _tempfile() as f: + bt.plot(filename=f[: -len(".html")], open_browser=False) + self.assertLess(os.path.getsize(f), 500000) + + def test_params(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + bt.run() + with _tempfile() as f: + for p in dict( + plot_volume=False, # noqa: C408 + plot_equity=False, + plot_return=True, + plot_pl=False, + plot_drawdown=True, + plot_trades=False, + superimpose=False, + resample="1W", + smooth_equity=False, + relative_equity=False, + reverse_indicators=True, + show_legend=False, + ).items(): + with self.subTest(param=p[0]): + bt.plot(**dict([p]), filename=f, open_browser=False) + + def test_hide_legend(self): + bt = Backtest(GOOG.iloc[:100], SmaCross) + bt.run() + with _tempfile() as f: + bt.plot(filename=f, show_legend=False) + # Give browser time to open before tempfile is removed + time.sleep(5) + + def test_resolutions(self): + with _tempfile() as f: + for rule in "LSTHDWM": + with self.subTest(rule=rule): + df = ( + EURUSD.iloc[:2] + .resample(rule) + .agg(OHLCV_AGG) + .dropna() + .iloc[:1100] + ) + bt = Backtest(df, SmaCross) + bt.run() + bt.plot(filename=f, open_browser=False) + + def test_range_axis(self): + df = GOOG.iloc[:100].reset_index(drop=True) + + # Warm-up. CPython bug bpo-29620. + try: + with self.assertWarns(UserWarning): + Backtest(df, SmaCross) + except RuntimeError: + pass + + with self.assertWarns(UserWarning): + bt = Backtest(df, SmaCross) + bt.run() + with _tempfile() as f: + bt.plot(filename=f, open_browser=False) + + def test_preview(self): + class Strategy(SmaCross): + def init(self): + super().init() + + def ok(x): + return x + + self.a = self.I(SMA, self.data.Open, 5, overlay=False, name="ok") + self.b = self.I(ok, np.random.random(len(self.data.Open))) + + bt = Backtest(GOOG, Strategy) + bt.run() + with _tempfile() as f: + bt.plot(filename=f, plot_drawdown=True, smooth_equity=True) + # Give browser time to open before tempfile is removed + time.sleep(5) + + def test_wellknown(self): + class S(Strategy): + def init(self): + pass + + def next(self): + date = self.data.index[-1] + if date == pd.Timestamp("Thu 19 Oct 2006"): + self.buy(stop=484, limit=466, size=100) + elif date == pd.Timestamp("Thu 30 Oct 2007"): + self.position.close() + elif date == pd.Timestamp("Tue 11 Nov 2008"): + self.sell( + stop=self.data.Low, limit=324.90, size=200 # High from 14 Nov + ) + + bt = Backtest(GOOG, S, margin=0.1) + stats = bt.run() + trades = stats["_trades"] + + self.assertAlmostEqual(stats["Equity Peak [$]"], 46961) + self.assertEqual(stats["Equity Final [$]"], 0) + self.assertEqual(len(trades), 2) + assert trades[["EntryTime", "ExitTime"]].equals( + pd.DataFrame( + { + "EntryTime": pd.to_datetime(["2006-11-01", "2008-11-14"]), + "ExitTime": pd.to_datetime(["2007-10-31", "2009-09-21"]), + } + ) + ) + assert trades["PnL"].round().equals(pd.Series([23469.0, -34420.0])) + + with _tempfile() as f: + bt.plot(filename=f, plot_drawdown=True, smooth_equity=False) + # Give browser time to open before tempfile is removed + time.sleep(1) + + def test_resample(self): + bt = Backtest(GOOG, SmaCross) + bt.run() + import fx_backtest._plotting + + with _tempfile() as f, patch.object( + fx_backtest._plotting, "_MAX_CANDLES", 10 + ), self.assertWarns(UserWarning): + bt.plot(filename=f, resample=True) + # Give browser time to open before tempfile is removed + time.sleep(1) + + def test_indicator_color(self): + class S(Strategy): + def init(self): + a = self.I(SMA, self.data.Close, 5, overlay=True, color="red") + b = self.I(SMA, self.data.Close, 10, overlay=False, color="blue") + self.I(lambda: (a, b), overlay=False, color=("green", "orange")) + + def next(self): + pass + + bt = Backtest(GOOG, S) + bt.run() + with _tempfile() as f: + bt.plot( + filename=f, + plot_drawdown=False, + plot_equity=False, + plot_pl=False, + plot_volume=False, + open_browser=False, + ) + + def test_indicator_scatter(self): + class S(Strategy): + def init(self): + self.I(SMA, self.data.Close, 5, overlay=True, scatter=True) + self.I(SMA, self.data.Close, 10, overlay=False, scatter=True) + + def next(self): + pass + + bt = Backtest(GOOG, S) + bt.run() + with _tempfile() as f: + bt.plot( + filename=f, + plot_drawdown=False, + plot_equity=False, + plot_pl=False, + plot_volume=False, + open_browser=False, + ) + + +class TestLib(TestCase): + def test_barssince(self): + self.assertEqual(barssince(np.r_[1, 0, 0]), 2) + self.assertEqual(barssince(np.r_[0, 0, 0]), np.inf) + self.assertEqual(barssince(np.r_[0, 0, 0], 0), 0) + + def test_cross(self): + self.assertTrue(cross([0, 1], [1, 0])) + self.assertTrue(cross([1, 0], [0, 1])) + self.assertFalse(cross([1, 0], [1, 0])) + + def test_crossover(self): + self.assertTrue(crossover([0, 1], [1, 0])) + self.assertTrue(crossover([0, 1], 0.5)) + self.assertTrue(crossover([0, 1], pd.Series([0.5, 0.5], index=[5, 6]))) + self.assertFalse(crossover([1, 0], [1, 0])) + self.assertFalse(crossover([0], [1])) + + def test_quantile(self): + self.assertEqual(quantile(np.r_[1, 3, 2], 0.5), 2) + self.assertEqual(quantile(np.r_[1, 3, 2]), 0.5) + + def test_resample_apply(self): + res = resample_apply("D", SMA, EURUSD.Close, 10) + self.assertEqual(res.name, "C[D]") + self.assertEqual(res.count() / res.size, 0.9634) + np.testing.assert_almost_equal( + res.iloc[-48:].unique().tolist(), [1.242643, 1.242381, 1.242275], decimal=6 + ) + + def resets_index(*args): + return pd.Series(SMA(*args).values) + + res2 = resample_apply("D", resets_index, EURUSD.Close, 10) + self.assertTrue((res.dropna() == res2.dropna()).all()) + self.assertTrue((res.index == res2.index).all()) + + res3 = resample_apply("D", None, EURUSD) + self.assertIn("Volume", res3) + + res3 = resample_apply("D", lambda df: (df.Close, df.Close), EURUSD) + self.assertIsInstance(res3, pd.DataFrame) + + def test_plot_heatmaps(self): + bt = Backtest(GOOG, SmaCross) + stats, heatmap = bt.optimize( + fast=range(2, 7, 2), slow=range(7, 15, 2), return_heatmap=True + ) + with _tempfile() as f: + for agg in ("mean", lambda x: np.percentile(x, 75)): + plot_heatmaps(heatmap, agg, filename=f, open_browser=False) + + # Preview + plot_heatmaps(heatmap, filename=f) + time.sleep(5) + + def test_random_ohlc_data(self): + generator = random_ohlc_data(GOOG, frac=1) + new_data = next(generator) + self.assertEqual(list(new_data.index), list(GOOG.index)) + self.assertEqual(new_data.shape, GOOG.shape) + self.assertEqual(list(new_data.columns), list(GOOG.columns)) + + def test_compute_stats(self): + stats = Backtest(GOOG, SmaCross).run() + only_long_trades = stats._trades[stats._trades.Size > 0] + long_stats = compute_stats( + stats=stats, trades=only_long_trades, data=GOOG, risk_free_rate=0.02 + ) + self.assertNotEqual( + list(stats._equity_curve.Equity), list(long_stats._equity_curve.Equity) + ) + self.assertNotEqual(stats["Sharpe Ratio"], long_stats["Sharpe Ratio"]) + self.assertEqual(long_stats["# Trades"], len(only_long_trades)) + self.assertEqual(stats._strategy, long_stats._strategy) + assert_frame_equal(long_stats._trades, only_long_trades) + + def test_SignalStrategy(self): + class S(SignalStrategy): + def init(self): + sma = self.data.Close.s.rolling(10).mean() + self.set_signal(self.data.Close > sma, self.data.Close < sma) + + stats = Backtest(GOOG, S).run() + self.assertIn(stats["# Trades"], (1181, 1182)) # varies on different archs? + + def test_TrailingStrategy(self): + class S(TrailingStrategy): + def init(self): + super().init() + self.set_atr_periods(40) + self.set_trailing_sl(3) + self.sma = self.I(lambda: self.data.Close.s.rolling(10).mean()) + + def next(self): + super().next() + if not self.position and self.data.Close > self.sma: + self.buy() + + stats = Backtest(GOOG, S).run() + self.assertEqual(stats["# Trades"], 57) + + +class TestUtil(TestCase): + def test_as_str(self): + def func(): + pass + + class Class: + def __call__(self): + pass + + self.assertEqual(_as_str("4"), "4") + self.assertEqual(_as_str(4), "4") + self.assertEqual(_as_str(_Indicator([1, 2], name="x")), "x") + self.assertEqual(_as_str(func), "func") + self.assertEqual(_as_str(Class), "Class") + self.assertEqual(_as_str(Class()), "Class") + self.assertEqual(_as_str(pd.Series([1, 2], name="x")), "x") + self.assertEqual(_as_str(pd.DataFrame()), "df") + self.assertEqual(_as_str(lambda x: x), "λ") + for s in ("Open", "High", "Low", "Close", "Volume"): + self.assertEqual(_as_str(_Array([1], name=s)), s[0]) + + def test_pandas_accessors(self): + class S(Strategy): + def init(self): + close, index = self.data.Close, self.data.index + assert close.s.equals(pd.Series(close, index=index)) + assert self.data.df["Close"].equals(pd.Series(close, index=index)) + self.data.df["new_key"] = 2 * close + + def next(self): + close, index = self.data.Close, self.data.index + assert close.s.equals(pd.Series(close, index=index)) + assert self.data.df["Close"].equals(pd.Series(close, index=index)) + assert self.data.df["new_key"].equals( + pd.Series(self.data.new_key, index=index) + ) + + Backtest(GOOG.iloc[:20], S).run() + + def test_indicators_picklable(self): + bt = Backtest(SHORT_DATA, SmaCross) + with ProcessPoolExecutor() as executor: + stats = executor.submit(Backtest.run, bt).result() + assert stats._strategy._indicators[ + 0 + ]._opts, "._opts and .name were not unpickled" + bt.plot(results=stats, resample="2d", open_browser=False) + + +class TestDocs(TestCase): + DOCS_DIR = os.path.join(os.path.dirname(__file__), "..", "..", "doc") + + @unittest.skipUnless(os.path.isdir(DOCS_DIR), "docs dir doesn't exist") + def test_examples(self): + examples = glob(os.path.join(self.DOCS_DIR, "examples", "*.py")) + self.assertGreaterEqual(len(examples), 4) + with chdir(gettempdir()): + for file in examples: + with self.subTest(example=os.path.basename(file)): + run_path(file) + + def test_backtest_run_docstring_contains_stats_keys(self): + stats = Backtest(SHORT_DATA, SmaCross).run() + for key in stats.index: + self.assertIn(key, Backtest.run.__doc__) + + def test_readme_contains_stats_keys(self): + with open( + os.path.join(os.path.dirname(__file__), "..", "..", "README.md") + ) as f: + readme = f.read() + stats = Backtest(SHORT_DATA, SmaCross).run() + for key in stats.index: + self.assertIn(key, readme) + + +if __name__ == "__main__": + warnings.filterwarnings("error") + unittest.main() diff --git a/tests/unit/test_default.py b/tests/unit/test_default.py deleted file mode 100644 index 47d4f19..0000000 --- a/tests/unit/test_default.py +++ /dev/null @@ -1,2 +0,0 @@ -def test_default(): - assert True From 81860a92e618d58f205d7f5fff6b945025a093e0 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Thu, 4 Jul 2024 14:15:41 -0400 Subject: [PATCH 3/9] Splitting out backtest classes to help with parsing and circular references --- fx_backtest/_interfaces.py | 32 ++------- fx_backtest/_models.py | 143 ++++++++++++++++++------------------- fx_backtest/backtesting.py | 23 +++--- 3 files changed, 91 insertions(+), 107 deletions(-) diff --git a/fx_backtest/_interfaces.py b/fx_backtest/_interfaces.py index f8a2a0e..d53c907 100644 --- a/fx_backtest/_interfaces.py +++ b/fx_backtest/_interfaces.py @@ -1,31 +1,13 @@ -from abc import abstractmethod, ABCMeta -from typing import List, Optional -from fx_backtest._models import Trade, Order +from abc import abstractmethod +from fx_backtest._util import _Data +class IBroker: -class IBroker(metaclass=ABCMeta): - @property @abstractmethod - def trades(self) -> List[Trade]: - raise NotImplementedError + def data(self) -> _Data: + raise NotImplementedError() @property @abstractmethod - def orders(self) -> List[Order]: - raise NotImplementedError - - @abstractmethod - def new_order( - self, - size: float, - limit: Optional[float] = None, - stop: Optional[float] = None, - sl: Optional[float] = None, - tp: Optional[float] = None, - tag: object = None, - *, - trade: Optional[Trade] = None, - ): - raise NotImplementedError() - - \ No newline at end of file + def last_price(self) -> float: + raise NotImplementedError() \ No newline at end of file diff --git a/fx_backtest/_models.py b/fx_backtest/_models.py index cbffb2e..28dbd2c 100644 --- a/fx_backtest/_models.py +++ b/fx_backtest/_models.py @@ -14,61 +14,6 @@ "Trade.__init__": False, } -class Position: - """ - Currently held asset position, available as - `backtesting.backtesting.Strategy.position` within - `backtesting.backtesting.Strategy.next`. - Can be used in boolean contexts, e.g. - - if self.position: - ... # we have a position, either long or short - """ - - def __init__(self, broker: IBroker): - self.__broker = broker - - def __bool__(self): - return self.size != 0 - - @property - def size(self) -> float: - """Position size in units of asset. Negative if position is short.""" - return sum(trade.size for trade in self.__broker.trades) - - @property - def pl(self) -> float: - """Profit (positive) or loss (negative) of the current position in cash units.""" - return sum(trade.pl for trade in self.__broker.trades) - - @property - def pl_pct(self) -> float: - """Profit (positive) or loss (negative) of the current position in percent.""" - weights = np.abs([trade.size for trade in self.__broker.trades]) - weights = weights / weights.sum() - pl_pcts = np.array([trade.pl_pct for trade in self.__broker.trades]) - return (pl_pcts * weights).sum() - - @property - def is_long(self) -> bool: - """True if the position is long (position size is positive).""" - return self.size > 0 - - @property - def is_short(self) -> bool: - """True if the position is short (position size is negative).""" - return self.size < 0 - - def close(self, portion: float = 1.0): - """ - Close portion of position by closing `portion` of each active trade. See `Trade.close`. - """ - for trade in self.__broker.trades: - trade.close(portion) - - def __repr__(self): - return f"" - class Order: """ @@ -88,7 +33,6 @@ class Order: def __init__( self, - broker: IBroker, size: float, limit_price: Optional[float] = None, stop_price: Optional[float] = None, @@ -97,7 +41,6 @@ def __init__( parent_trade: Optional["Trade"] = None, tag: object = None, ): - self.__broker = broker assert size != 0 self.__size = size self.__limit_price = limit_price @@ -129,18 +72,6 @@ def __repr__(self): ) ) - def cancel(self): - """Cancel the order.""" - self.__broker.orders.remove(self) - trade = self.__parent_trade - if trade: - if self is trade._sl_order: - trade._replace(sl_order=None) - elif self is trade._tp_order: - trade._replace(tp_order=None) - else: - # XXX: https://github.com/kernc/backtesting.py/issues/251#issuecomment-835634984 ??? - assert False # Fields getters @@ -233,6 +164,16 @@ def is_contingent(self): [OCO]: https://www.investopedia.com/terms/o/oco.asp """ return bool(self.__parent_trade) + + def cancel(self): + trade = self.__parent_trade + if trade: + if self is trade._sl_order: + trade._replace(sl_order=None) + elif self is trade._tp_order: + trade._replace(tp_order=None) + else: + raise RuntimeError() class Trade: @@ -273,8 +214,7 @@ def close(self, portion: float = 1.0): """Place new `Order` to close `portion` of the trade at next market price.""" assert 0 < portion <= 1, "portion must be a fraction between 0 and 1" size = copysign(max(1, round(abs(self.__size) * portion)), -self.__size) - order = Order(self.__broker, size, parent_trade=self, tag=self.__tag) - self.__broker.orders.insert(0, order) + return Order(size, parent_trade=self, tag=self.__tag) # Fields getters @@ -332,14 +272,14 @@ def _tp_order(self): @property def entry_time(self) -> Union[pd.Timestamp, int]: """Datetime of when the trade was entered.""" - return self.__broker._data.index[self.__entry_bar] + return self.__broker.data.index[self.__entry_bar] @property def exit_time(self) -> Optional[Union[pd.Timestamp, int]]: """Datetime of when the trade was exited.""" if self.__exit_bar is None: return None - return self.__broker._data.index[self.__exit_bar] + return self.__broker.data.index[self.__exit_bar] @property def is_long(self): @@ -444,4 +384,59 @@ def __getattr__(self, item): "Backtesting 0.2.0. " "Use `Order` API instead. See docs." ) - raise AttributeError(f"'tuple' object has no attribute {item!r}") \ No newline at end of file + raise AttributeError(f"'tuple' object has no attribute {item!r}") + +class Position: + """ + Currently held asset position, available as + `backtesting.backtesting.Strategy.position` within + `backtesting.backtesting.Strategy.next`. + Can be used in boolean contexts, e.g. + + if self.position: + ... # we have a position, either long or short + """ + + def __init__(self, trades: list[Trade]): + self._trades = trades + + def __bool__(self): + return self.size != 0 + + @property + def size(self) -> float: + """Position size in units of asset. Negative if position is short.""" + return sum(trade.size for trade in self._trades) + + @property + def pl(self) -> float: + """Profit (positive) or loss (negative) of the current position in cash units.""" + return sum(trade.pl for trade in self._trades) + + @property + def pl_pct(self) -> float: + """Profit (positive) or loss (negative) of the current position in percent.""" + weights = np.abs([trade.size for trade in self._trades]) + weights = weights / weights.sum() + pl_pcts = np.array([trade.pl_pct for trade in self._trades]) + return (pl_pcts * weights).sum() + + @property + def is_long(self) -> bool: + """True if the position is long (position size is positive).""" + return self.size > 0 + + @property + def is_short(self) -> bool: + """True if the position is short (position size is negative).""" + return self.size < 0 + + def close(self, portion: float = 1.0): + """ + Close portion of position by closing `portion` of each active trade. See `Trade.close`. + """ + for trade in self._trades: + trade.close(portion) + + def __repr__(self): + return f"" \ No newline at end of file diff --git a/fx_backtest/backtesting.py b/fx_backtest/backtesting.py index c290a95..e880bfe 100644 --- a/fx_backtest/backtesting.py +++ b/fx_backtest/backtesting.py @@ -29,6 +29,7 @@ from fx_backtest._stats import compute_stats from fx_backtest._util import _as_str, _Data, _Indicator, try_ from fx_backtest._models import Position, Order, Trade, _Orders +from fx_backtest._interfaces import IBroker from fx_backtest._exceptions import _OutOfMoneyError __pdoc__ = { @@ -333,7 +334,7 @@ def next(self): setattr(self, attr, indicator[..., : len(self.data)]) super().next() -class _Broker: +class _Broker(IBroker): def __init__( self, *, @@ -361,22 +362,26 @@ def __init__( self._exclusive_orders = exclusive_orders self._equity = np.tile(np.nan, len(index)) - self._orders: List[Order] = [] - self._trades: List[Trade] = [] - self.position = Position(self) - self.closed_trades: List[Trade] = [] + self._orders: list[Order] = [] + self._trades: list[Trade] = [] + self.position = Position(self.trades) + self.closed_trades: list[Trade] = [] def __repr__(self): return f"" @property - def trades(self) -> List[Trade]: + def trades(self) -> list[Trade]: return self._trades @property - def orders(self) -> List[Order]: + def orders(self) -> list[Order]: return self._orders + @property + def data(self) -> _Data: + return self._data + def new_order( self, size: float, @@ -425,6 +430,7 @@ def new_order( for o in self.orders: if not o.is_contingent: o.cancel() + self.orders.remove(o) for t in self.trades: t.close() @@ -432,6 +438,7 @@ def new_order( return order + @property def last_price(self) -> float: """Price at the last (current) close.""" @@ -929,7 +936,7 @@ def run(self, **kwargs) -> pd.Series: else: # Close any remaining open trades so they produce some stats for trade in broker.trades: - trade.close() + broker.orders.insert(0, trade.close()) # Re-run broker one last time to handle orders placed in the last strategy # iteration. Use the same OHLC values as in the last broker iteration. From e2ad4de952d67e7f12fb83110f69619d34665b23 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Thu, 4 Jul 2024 15:08:01 -0400 Subject: [PATCH 4/9] Fixing lint errors and unit test discovery --- fx_backtest/_exceptions.py | 2 +- fx_backtest/_interfaces.py | 7 +++-- fx_backtest/_models.py | 15 +++++----- fx_backtest/_plotting.py | 17 ++++++----- fx_backtest/_stats.py | 7 +++-- fx_backtest/backtesting.py | 59 +++++++++++++++++-------------------- fx_backtest/lib.py | 30 +++++++++++-------- poetry.lock | 13 +++++++- pyproject.toml | 6 +++- tests/unit/__init__.py | 5 ++-- tests/unit/test_backtest.py | 6 ++-- 11 files changed, 95 insertions(+), 72 deletions(-) diff --git a/fx_backtest/_exceptions.py b/fx_backtest/_exceptions.py index 25c70e6..c14c378 100644 --- a/fx_backtest/_exceptions.py +++ b/fx_backtest/_exceptions.py @@ -1,2 +1,2 @@ class _OutOfMoneyError(Exception): - pass \ No newline at end of file + pass diff --git a/fx_backtest/_interfaces.py b/fx_backtest/_interfaces.py index d53c907..627013a 100644 --- a/fx_backtest/_interfaces.py +++ b/fx_backtest/_interfaces.py @@ -1,13 +1,16 @@ from abc import abstractmethod + from fx_backtest._util import _Data + + class IBroker: @property @abstractmethod def data(self) -> _Data: raise NotImplementedError() - + @property @abstractmethod def last_price(self) -> float: - raise NotImplementedError() \ No newline at end of file + raise NotImplementedError() diff --git a/fx_backtest/_models.py b/fx_backtest/_models.py index 28dbd2c..e066241 100644 --- a/fx_backtest/_models.py +++ b/fx_backtest/_models.py @@ -1,7 +1,7 @@ - from copy import copy from math import copysign from typing import Optional, Union + import numpy as np import pandas as pd @@ -72,7 +72,6 @@ def __repr__(self): ) ) - # Fields getters @property @@ -164,7 +163,7 @@ def is_contingent(self): [OCO]: https://www.investopedia.com/terms/o/oco.asp """ return bool(self.__parent_trade) - + def cancel(self): trade = self.__parent_trade if trade: @@ -182,9 +181,7 @@ class Trade: Find active trades in `Strategy.trades` and closed, settled trades in `Strategy.closed_trades`. """ - def __init__( - self, broker: IBroker, size: int, entry_price: float, entry_bar, tag - ): + def __init__(self, broker: IBroker, size: int, entry_price: float, entry_bar, tag): self.__broker = broker self.__size = size self.__entry_price = entry_price @@ -355,6 +352,7 @@ def __set_contingent(self, type, price): ) setattr(self, attr, order) + class _Orders(tuple): """ TODO: remove this class. Only for deprecation. @@ -385,7 +383,8 @@ def __getattr__(self, item): "Use `Order` API instead. See docs." ) raise AttributeError(f"'tuple' object has no attribute {item!r}") - + + class Position: """ Currently held asset position, available as @@ -439,4 +438,4 @@ def close(self, portion: float = 1.0): trade.close(portion) def __repr__(self): - return f"" \ No newline at end of file + return f"" diff --git a/fx_backtest/_plotting.py b/fx_backtest/_plotting.py index a933f69..7b2b819 100644 --- a/fx_backtest/_plotting.py +++ b/fx_backtest/_plotting.py @@ -276,7 +276,9 @@ def plot( figs_above_ohlc, figs_below_ohlc = [], [] source = ColumnDataSource(df) - source.add((df.Close >= df.Open).values.astype(np.uint8).astype(str), "inc") + source.add( + (df.Close >= df.Open).values.astype(np.uint8).astype(str).tolist(), "inc" + ) trade_source = ColumnDataSource( dict( @@ -831,16 +833,15 @@ def __eq__(self, other): set_tooltips(fig_ohlc, ohlc_tooltips, vline=True, renderers=[ohlc_bars]) - source.add(ohlc_extreme_values.min(1), "ohlc_low") - source.add(ohlc_extreme_values.max(1), "ohlc_high") + source.add(ohlc_extreme_values.min(1).to_list(), "ohlc_low") + source.add(ohlc_extreme_values.max(1).to_list(), "ohlc_high") custom_js_args = dict(ohlc_range=fig_ohlc.y_range, source=source) if plot_volume: custom_js_args.update(volume_range=fig_volume.y_range) - fig_ohlc.x_range.js_on_change( - "end", - CustomJS(args=custom_js_args, code=_AUTOSCALE_JS_CALLBACK), # type: ignore + fig_ohlc.x_range.js_on_change( # type: ignore + "end", CustomJS(args=custom_js_args, code=_AUTOSCALE_JS_CALLBACK) ) plots = figs_above_ohlc + [fig_ohlc] + figs_below_ohlc @@ -915,8 +916,8 @@ def plot_heatmaps( ) for df in dfs: name1, name2 = df.index.names - level1 = df.index.levels[0].astype(str).tolist() - level2 = df.index.levels[1].astype(str).tolist() + level1 = df.index.levels[0].astype(str).tolist() # type: ignore + level2 = df.index.levels[1].astype(str).tolist() # type: ignore df = df.reset_index() df[name1] = df[name1].astype("str") df[name2] = df[name2].astype("str") diff --git a/fx_backtest/_stats.py b/fx_backtest/_stats.py index 67d06e7..fe6a20d 100644 --- a/fx_backtest/_stats.py +++ b/fx_backtest/_stats.py @@ -2,6 +2,7 @@ import numpy as np import pandas as pd +from pandas import Series from ._util import _data_period @@ -93,7 +94,7 @@ def _round_timedelta(value, _period=_data_period(index)): have_position = np.repeat(0, len(index)) for t in trades_df.itertuples(index=False): - have_position[t.EntryBar : t.ExitBar + 1] = 1 + have_position[t.EntryBar : t.ExitBar + 1] = 1 # type:ignore s.loc["Exposure Time [%]"] = ( have_position.mean() * 100 @@ -105,7 +106,7 @@ def _round_timedelta(value, _period=_data_period(index)): s.loc["Buy & Hold Return [%]"] = (c[-1] - c[0]) / c[0] * 100 # long-only return gmean_day_return: float = 0 - day_returns = np.array(np.nan) + day_returns = Series(np.array(np.nan)) annual_trading_days = np.nan if isinstance(index, pd.DatetimeIndex): day_returns = equity_df["Equity"].resample("D").last().dropna().pct_change() @@ -126,7 +127,7 @@ def _round_timedelta(value, _period=_data_period(index)): np.sqrt( ( day_returns.var(ddof=int(bool(day_returns.shape))) - + (1 + gmean_day_return) ** 2 + + (1 + gmean_day_return) ** 2 # type:ignore ) ** annual_trading_days - (1 + gmean_day_return) ** (2 * annual_trading_days) diff --git a/fx_backtest/backtesting.py b/fx_backtest/backtesting.py index e880bfe..40c8c5e 100644 --- a/fx_backtest/backtesting.py +++ b/fx_backtest/backtesting.py @@ -21,16 +21,21 @@ import numpy as np import pandas as pd from numpy.random import default_rng -from tqdm.auto import tqdm as _tqdm -_tqdm = partial(_tqdm, leave=False) - +from skopt import forest_minimize +from skopt.callbacks import DeltaXStopper +from skopt.learning import ExtraTreesRegressor +from skopt.space import Categorical, Integer, Real +from skopt.utils import use_named_args +from tqdm.auto import tqdm +from fx_backtest._exceptions import _OutOfMoneyError +from fx_backtest._interfaces import IBroker +from fx_backtest._models import Order, Position, Trade, _Orders from fx_backtest._plotting import plot # noqa: I001 from fx_backtest._stats import compute_stats from fx_backtest._util import _as_str, _Data, _Indicator, try_ -from fx_backtest._models import Position, Order, Trade, _Orders -from fx_backtest._interfaces import IBroker -from fx_backtest._exceptions import _OutOfMoneyError + +_tqdm = partial(tqdm, leave=False) __pdoc__ = { "Strategy.__init__": False, @@ -38,7 +43,8 @@ "Position.__init__": False, "Trade.__init__": False, } - + + class Strategy(metaclass=ABCMeta): """ A trading strategy base class. Extend this class and @@ -318,6 +324,7 @@ def closed_trades(self) -> Tuple[Trade, ...]: """List of settled trades (see `Trade`).""" return tuple(self._broker.closed_trades) + class BacktestStrategy(Strategy): def init(self): @@ -334,6 +341,7 @@ def next(self): setattr(self, attr, indicator[..., : len(self.data)]) super().next() + class _Broker(IBroker): def __init__( self, @@ -418,7 +426,7 @@ def new_order( f"TP ({tp}) < LIMIT ({limit or stop or adjusted_price}) < SL ({sl})" ) - order = Order(self, size, limit, stop, sl, tp, trade, tag) + order = Order(size, limit, stop, sl, tp, trade, tag) # Put the new order in the order queue, # inserting SL/TP/trade-closing orders in-front if trade: @@ -438,7 +446,6 @@ def new_order( return order - @property def last_price(self) -> float: """Price at the last (current) close.""" @@ -800,7 +807,7 @@ def __init__( if len(data) == 0: raise ValueError("OHLC `data` is empty") if ( - len(data.columns.intersection({"Open", "High", "Low", "Close", "Volume"})) + len(data.columns.intersection(["Open", "High", "Low", "Close", "Volume"])) != 5 ): raise ValueError( @@ -901,18 +908,18 @@ def run(self, **kwargs) -> pd.Series: data._update() # Strategy.init might have changed/added to data.df # Indicators used in Strategy.next() - # indicator_attrs = { - # attr: indicator - # for attr, indicator in strategy.__dict__.items() - # if isinstance(indicator, _Indicator) - # }.items() + indicator_attrs = { + attr: indicator + for attr, indicator in strategy.__dict__.items() + if isinstance(indicator, _Indicator) + }.items() # Skip first few candles where indicators are still "warming up" # +1 to have at least two entries available start = 1 + max( ( np.isnan(indicator.astype(float)).argmin(axis=-1).max() - for _, indicator in strategy._indicator_attrs + for _, indicator in indicator_attrs ), default=0, ) @@ -1190,7 +1197,7 @@ def _batch(seq): # run so we get some, if empty, results stats = self.run(**param_combos[0]) else: - stats = self.run(**dict(zip(heatmap.index.names, best_params))) + stats = self.run(**dict(zip(heatmap.index.names, str(best_params)))) if return_heatmap: return stats, heatmap @@ -1201,18 +1208,6 @@ def _optimize_skopt() -> Union[ Tuple[pd.Series, pd.Series], Tuple[pd.Series, pd.Series, dict], ]: - try: - from skopt import forest_minimize - from skopt.callbacks import DeltaXStopper - from skopt.learning import ExtraTreesRegressor - from skopt.space import Categorical, Integer, Real - from skopt.utils import use_named_args - except ImportError: - raise ImportError( - "Need package 'scikit-optimize' for method='skopt'. " - "pip install scikit-optimize" - ) from None - nonlocal max_tries max_tries = ( 200 @@ -1308,12 +1303,12 @@ def objective_function(**params): res.func_vals = res.func_vals[valid] output.append(res) - return stats if len(output) == 1 else tuple(output) + return stats if len(output) == 1 else tuple(output) # type:ignore if method == "grid": output = _optimize_grid() elif method == "skopt": - output = _optimize_skopt() + output = _optimize_skopt() # type:ignore else: raise ValueError(f"Method should be 'grid' or 'skopt', not {method!r}") return output @@ -1331,7 +1326,7 @@ def _mp_task(backtest_uuid, batch_index): def plot( self, *, - results: pd.Series = None, + results: Optional[pd.Series] = None, filename=None, plot_width=None, plot_equity=True, diff --git a/fx_backtest/lib.py b/fx_backtest/lib.py index 15c228a..a48fbdb 100644 --- a/fx_backtest/lib.py +++ b/fx_backtest/lib.py @@ -105,12 +105,12 @@ def crossover(series1: Sequence, series2: Sequence) -> bool: True """ series1 = ( - series1.values + series1.values # type:ignore if isinstance(series1, pd.Series) else (series1, series1) if isinstance(series1, Number) else series1 ) series2 = ( - series2.values + series2.values # type:ignore if isinstance(series2, pd.Series) else (series2, series2) if isinstance(series2, Number) else series2 ) @@ -179,7 +179,7 @@ def compute_stats( *, stats: pd.Series, data: pd.DataFrame, - trades: pd.DataFrame = None, + trades: Optional[pd.DataFrame] = None, risk_free_rate: float = 0.0, ) -> pd.Series: """ @@ -204,7 +204,7 @@ def compute_stats( equity = equity.copy() equity[:] = stats._equity_curve.Equity.iloc[0] for t in trades.itertuples(index=False): - equity.iloc[t.EntryBar :] += t.PnL + equity.iloc[t.EntryBar :] += t.PnL # type:ignore return _compute_stats( trades=trades, equity=equity, @@ -219,7 +219,7 @@ def resample_apply( func: Optional[Callable[..., Sequence]], series: Union[pd.Series, pd.DataFrame, _Array], *args, - agg: Optional[Union[str, dict]] = None, + group_by: Optional[Union[str, dict]] = None, **kwargs, ): """ @@ -305,12 +305,16 @@ def func(x, *_, **__): ) series = series.s - if agg is None: - agg = OHLCV_AGG.get(getattr(series, "name", ""), "last") + if group_by is None: + group_by = OHLCV_AGG.get(getattr(series, "name", ""), "last") if isinstance(series, pd.DataFrame): - agg = {column: OHLCV_AGG.get(column, "last") for column in series.columns} + group_by = { + column: OHLCV_AGG.get(column, "last") for column in series.columns + } - resampled = series.resample(rule, label="right").agg(agg).dropna() + resampled = ( + series.resample(rule, label="right").agg(group_by).dropna() # type:ignore + ) # type:ignore resampled.name = _as_str(series) + "[" + rule + "]" # Check first few stack frames if we are being called from @@ -374,7 +378,7 @@ def random_ohlc_data( def shuffle(x): return x.sample(frac=frac, replace=frac > 1, random_state=random_state) - if len(example_data.columns.intersection({"Open", "High", "Low", "Close"})) != 4: + if len(example_data.columns.intersection(["Open", "High", "Low", "Close"])) != 4: raise ValueError( "`data` must be a pandas.DataFrame with columns " "'Open', 'High', 'Low', 'Close'" @@ -504,9 +508,11 @@ def set_atr_periods(self, periods: int = 100): hi, lo, c_prev = ( self.data.High, self.data.Low, - pd.Series(self.data.Close).shift(1), + pd.Series(self.data.Close).shift(1), # type:ignore + ) + tr = np.max( + [hi - lo, (c_prev - hi).abs(), (c_prev - lo).abs()], axis=0 # type:ignore ) - tr = np.max([hi - lo, (c_prev - hi).abs(), (c_prev - lo).abs()], axis=0) atr = pd.Series(tr).rolling(periods).mean().bfill().values self.__atr = atr diff --git a/poetry.lock b/poetry.lock index c088f06..2b48777 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1103,6 +1103,17 @@ files = [ {file = "types_pytz-2024.1.0.20240417-py3-none-any.whl", hash = "sha256:8335d443310e2db7b74e007414e74c4f53b67452c0cb0d228ca359ccfba59659"}, ] +[[package]] +name = "types-tqdm" +version = "4.66.0.20240417" +description = "Typing stubs for tqdm" +optional = false +python-versions = ">=3.8" +files = [ + {file = "types-tqdm-4.66.0.20240417.tar.gz", hash = "sha256:16dce9ef522ea8d40e4f5b8d84dd8a1166eefc13ceee7a7e158bf0f1a1421a31"}, + {file = "types_tqdm-4.66.0.20240417-py3-none-any.whl", hash = "sha256:248aef1f9986b7b8c2c12b3cb4399fc17dba0a29e7e3f3f9cd704babb879383d"}, +] + [[package]] name = "typing-extensions" version = "4.11.0" @@ -1139,4 +1150,4 @@ files = [ [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "fde4974771c868ab6211a9ebf048cebf0a20eb3d8dcedd3f84a9ccff27e75955" +content-hash = "70488d3080cba79b09d7bd5df22ff54e40226590876a0588bdf651843726f544" diff --git a/pyproject.toml b/pyproject.toml index 36918bc..a447a35 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -21,6 +21,7 @@ flake8 = "^7.0.0" black = "^24.3.0" isort = "^5.13.2" mypy = "^1.9.0" +types-tqdm = "^4.66.0.20240417" [build-system] requires = ["poetry-core"] @@ -51,7 +52,10 @@ omit = [ ] [[tool.mypy.overrides]] -module = "backtesting.*" +module = [ + "backtesting.*", + "skopt.*" +] ignore_missing_imports = true [tool.bandit] diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py index 3109573..4893ffd 100644 --- a/tests/unit/__init__.py +++ b/tests/unit/__init__.py @@ -5,12 +5,13 @@ def _read_file(filename): from os.path import dirname, join + + # df.index = pd.to_datetime(df.index, format="%Y%m%d %H:%M:%S.%f") return pd.read_csv( join(dirname(__file__), filename), index_col=0, - parse_dates=True, - infer_datetime_format=True, + parse_dates=True ) diff --git a/tests/unit/test_backtest.py b/tests/unit/test_backtest.py index 7077712..0d34e41 100644 --- a/tests/unit/test_backtest.py +++ b/tests/unit/test_backtest.py @@ -14,6 +14,8 @@ import numpy as np import pandas as pd +from pandas.testing import assert_frame_equal + from fx_backtest import Backtest, Strategy from fx_backtest._stats import compute_drawdown_duration_peaks from fx_backtest._util import _Array, _as_str, _Indicator, try_ @@ -30,8 +32,8 @@ random_ohlc_data, resample_apply, ) + from . import EURUSD, GOOG, SMA -from pandas.testing import assert_frame_equal SHORT_DATA = GOOG.iloc[:20] # Short data for fast tests with no indicator lag @@ -339,7 +341,7 @@ def almost_equal(a, b): "Duration", "StopLoss", "Tag", - "TakeProfit" + "TakeProfit", ] ), ) From be92c42656bd87a4145dd1c8e318950929e35099 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Tue, 9 Jul 2024 16:08:21 -0400 Subject: [PATCH 5/9] Adding initial indicator classes --- .flake8 | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.flake8 b/.flake8 index af263cd..45219f3 100644 --- a/.flake8 +++ b/.flake8 @@ -4,5 +4,6 @@ exclude = .git, .eggs, __pycache__, - doc/examples + doc/examples, + **/__init__.py extend-ignore = E203, E701 \ No newline at end of file From 5e199e7359085498b3ec58926a8d063a13fb8c5d Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Fri, 3 Jan 2025 08:58:56 -0500 Subject: [PATCH 6/9] Initial backtest implementation with vector support for indicators --- fx_backtest/py.typed => .bandit | 0 .flake8 | 9 +- =1.3 | 58 - ...rategy(_klass=SlopeMome\342\200\246).html" | 61 - BacktestStrategy.html | 61 - LICENSE | 21 + README.md | 120 - SlopeMomentum.html | 61 - SmaCross(fast=4,slow=6).html | 61 - SmaCross.html | 61 - docker/Dockerfile | 17 +- docker/docker-compose.yaml | 2 +- fx_backtest/__init__.py | 63 - fx_backtest/_exceptions.py | 2 - fx_backtest/_interfaces.py | 16 - fx_backtest/_models.py | 441 - fx_backtest/_plotting.py | 964 - fx_backtest/_stats.py | 186 - fx_backtest/_util.py | 207 - fx_backtest/_version.py | 17 - fx_backtest/autoscale_cb.js | 35 - fx_backtest/backtest.py | 46 + fx_backtest/backtesting.py | 1449 - fx_backtest/broker.py | 37 + fx_backtest/data.py | 165 + fx_backtest/exceptions.py | 0 fx_backtest/lib.py | 564 - fx_backtest/main.py | 19 +- fx_backtest/stats.py | 186 + fx_backtest/strategy.py | 47 + fx_backtest/utils.py | 9 + makefiles/local.mk | 2 +- poetry.lock | 819 +- pyproject.toml | 24 +- tests/unit/EURUSD.csv | 5001 -- tests/unit/GOOG.csv | 2149 - tests/unit/__init__.py | 29 - tests/unit/__main__.py | 7 - tests/unit/assets/EURGBP-2024-05_1Min.csv | 44461 ++++++++++++++++ tests/unit/assets/EURGBP-2024-05_5Min.csv | 8893 ++++ tests/unit/assets/EURJPY-2024-05_1Min.csv | 44461 ++++++++++++++++ tests/unit/assets/EURJPY-2024-05_5Min.csv | 8893 ++++ tests/unit/assets/EURUSD-2024-05_1Min.csv | 44461 ++++++++++++++++ tests/unit/assets/EURUSD-2024-05_5Min.csv | 8893 ++++ tests/unit/assets/GBPUSD-2024-05_1Min.csv | 44461 ++++++++++++++++ tests/unit/assets/GBPUSD-2024-05_5Min.csv | 8893 ++++ tests/unit/conftest.py | 95 + tests/unit/test_backtest.py | 1102 +- tests/unit/test_data.py | 32 + tests/unit/test_default.py | 2 + tests/unit/test_indicator.py | 14 + tests/unit/test_strategy.py | 109 + tests/unit/test_utils.py | 18 + 53 files changed, 214704 insertions(+), 13100 deletions(-) rename fx_backtest/py.typed => .bandit (100%) delete mode 100644 =1.3 delete mode 100644 "BacktestStrategy(_klass=SlopeMome\342\200\246).html" delete mode 100644 BacktestStrategy.html delete mode 100644 SlopeMomentum.html delete mode 100644 SmaCross(fast=4,slow=6).html delete mode 100644 SmaCross.html delete mode 100644 fx_backtest/_exceptions.py delete mode 100644 fx_backtest/_interfaces.py delete mode 100644 fx_backtest/_models.py delete mode 100644 fx_backtest/_plotting.py delete mode 100644 fx_backtest/_stats.py delete mode 100644 fx_backtest/_util.py delete mode 100644 fx_backtest/_version.py delete mode 100644 fx_backtest/autoscale_cb.js create mode 100644 fx_backtest/backtest.py delete mode 100644 fx_backtest/backtesting.py create mode 100644 fx_backtest/broker.py create mode 100644 fx_backtest/data.py create mode 100644 fx_backtest/exceptions.py delete mode 100644 fx_backtest/lib.py create mode 100644 fx_backtest/stats.py create mode 100644 fx_backtest/strategy.py create mode 100644 fx_backtest/utils.py delete mode 100644 tests/unit/EURUSD.csv delete mode 100644 tests/unit/GOOG.csv delete mode 100644 tests/unit/__main__.py create mode 100644 tests/unit/assets/EURGBP-2024-05_1Min.csv create mode 100644 tests/unit/assets/EURGBP-2024-05_5Min.csv create mode 100644 tests/unit/assets/EURJPY-2024-05_1Min.csv create mode 100644 tests/unit/assets/EURJPY-2024-05_5Min.csv create mode 100644 tests/unit/assets/EURUSD-2024-05_1Min.csv create mode 100644 tests/unit/assets/EURUSD-2024-05_5Min.csv create mode 100644 tests/unit/assets/GBPUSD-2024-05_1Min.csv create mode 100644 tests/unit/assets/GBPUSD-2024-05_5Min.csv create mode 100644 tests/unit/conftest.py create mode 100644 tests/unit/test_data.py create mode 100644 tests/unit/test_default.py create mode 100644 tests/unit/test_indicator.py create mode 100644 tests/unit/test_strategy.py create mode 100644 tests/unit/test_utils.py diff --git a/fx_backtest/py.typed b/.bandit similarity index 100% rename from fx_backtest/py.typed rename to .bandit diff --git a/.flake8 b/.flake8 index 45219f3..79a16af 100644 --- a/.flake8 +++ b/.flake8 @@ -1,9 +1,2 @@ [flake8] -max-line-length = 120 -exclude = - .git, - .eggs, - __pycache__, - doc/examples, - **/__init__.py -extend-ignore = E203, E701 \ No newline at end of file +max-line-length = 120 \ No newline at end of file diff --git a/=1.3 b/=1.3 deleted file mode 100644 index 140f249..0000000 --- a/=1.3 +++ /dev/null @@ -1,58 +0,0 @@ -Using version ^0.11.0 for pdoc3 -Using version ^1.16.2 for jupytext -Using version ^7.16.4 for nbconvert -Using version ^6.29.4 for ipykernel -Using version ^8.6.2 for jupyter-client - -Updating dependencies -Resolving dependencies... - -Package operations: 45 installs, 0 updates, 0 removals - - - Installing attrs (23.2.0) - - Installing rpds-py (0.18.1) - - Installing referencing (0.35.1) - - Installing jsonschema-specifications (2023.12.1) - - Installing traitlets (5.14.3) - - Installing asttokens (2.4.1) - - Installing executing (2.0.1) - - Installing fastjsonschema (2.20.0) - - Installing jsonschema (4.22.0) - - Installing jupyter-core (5.7.2) - - Installing parso (0.8.4) - - Installing ptyprocess (0.7.0) - - Installing pure-eval (0.2.2) - - Installing pyzmq (26.0.3) - - Installing wcwidth (0.2.13) - - Installing decorator (5.1.1) - - Installing jedi (0.19.1) - - Installing jupyter-client (8.6.2) - - Installing matplotlib-inline (0.1.7) - - Installing nbformat (5.10.4) - - Installing pexpect (4.9.0) - - Installing prompt-toolkit (3.0.47) - - Installing soupsieve (2.5) - - Installing stack-data (0.6.3) - - Installing webencodings (0.5.1) - - Installing beautifulsoup4 (4.12.3) - - Installing bleach (6.1.0) - - Installing comm (0.2.2) - - Installing debugpy (1.8.1) - - Installing ipython (8.25.0) - - Installing jupyterlab-pygments (0.3.0) - - Installing defusedxml (0.7.1) - - Installing mako (1.3.5) - - Installing mistune (3.0.2) - - Installing nbclient (0.10.0) - - Installing markdown (3.6) - - Installing psutil (6.0.0) - - Installing nest-asyncio (1.6.0) - - Installing tinycss2 (1.3.0) - - Installing pandocfilters (1.5.1) - - Installing mdit-py-plugins (0.4.1) - - Installing ipykernel (6.29.4) - - Installing jupytext (1.16.2) - - Installing nbconvert (7.16.4) - - Installing pdoc3 (0.11.0) - -Writing lock file diff --git "a/BacktestStrategy(_klass=SlopeMome\342\200\246).html" "b/BacktestStrategy(_klass=SlopeMome\342\200\246).html" deleted file mode 100644 index fa85df8..0000000 --- "a/BacktestStrategy(_klass=SlopeMome\342\200\246).html" +++ /dev/null @@ -1,61 +0,0 @@ - - - - - BacktestStrategy(_klass=SlopeMome…).html - - - - - -
- - - - - \ No newline at end of file diff --git a/BacktestStrategy.html b/BacktestStrategy.html deleted file mode 100644 index f2ad72f..0000000 --- a/BacktestStrategy.html +++ /dev/null @@ -1,61 +0,0 @@ - - - - - BacktestStrategy(_klass=SlopeMome…).html - - - - - -
- - - - - \ No newline at end of file diff --git a/LICENSE b/LICENSE index 8b13789..0acff47 100644 --- a/LICENSE +++ b/LICENSE @@ -1 +1,22 @@ +MIT License + +Copyright (c) 2024, Kyle Widmann + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md index bbbcd83..e69de29 100644 --- a/README.md +++ b/README.md @@ -1,120 +0,0 @@ -[![](https://i.imgur.com/E8Kj69Y.png)](https://kernc.github.io/backtesting.py/) - -Backtesting.py -============== -[![Build Status](https://img.shields.io/github/actions/workflow/status/kernc/backtesting.py/ci.yml?branch=master&style=for-the-badge)](https://github.com/kernc/backtesting.py/actions) -[![Code Coverage](https://img.shields.io/codecov/c/gh/kernc/backtesting.py.svg?style=for-the-badge)](https://codecov.io/gh/kernc/backtesting.py) -[![Backtesting on PyPI](https://img.shields.io/pypi/v/backtesting.svg?color=blue&style=for-the-badge)](https://pypi.org/project/backtesting) -[![PyPI downloads](https://img.shields.io/pypi/dd/backtesting.svg?color=skyblue&style=for-the-badge)](https://pypi.org/project/backtesting) -[![GitHub Sponsors](https://img.shields.io/github/sponsors/kernc?color=pink&style=for-the-badge)](https://github.com/sponsors/kernc) - -Backtest trading strategies with Python. - -[**Project website**](https://kernc.github.io/backtesting.py) + [Documentation] - -[Documentation]: https://kernc.github.io/backtesting.py/doc/backtesting/ - - -Installation ------------- - - $ pip install backtesting - - -Usage ------ -```python -from backtesting import Backtest, Strategy -from backtesting.lib import crossover - -from backtesting.test import SMA, GOOG - - -class SmaCross(Strategy): - def init(self): - price = self.data.Close - self.ma1 = self.I(SMA, price, 10) - self.ma2 = self.I(SMA, price, 20) - - def next(self): - if crossover(self.ma1, self.ma2): - self.buy() - elif crossover(self.ma2, self.ma1): - self.sell() - - -bt = Backtest(GOOG, SmaCross, commission=.002, - exclusive_orders=True) -stats = bt.run() -bt.plot() -``` - -Results in: - -```text -Start 2004-08-19 00:00:00 -End 2013-03-01 00:00:00 -Duration 3116 days 00:00:00 -Exposure Time [%] 94.27 -Equity Final [$] 68935.12 -Equity Peak [$] 68991.22 -Return [%] 589.35 -Buy & Hold Return [%] 703.46 -Return (Ann.) [%] 25.42 -Volatility (Ann.) [%] 38.43 -Sharpe Ratio 0.66 -Sortino Ratio 1.30 -Calmar Ratio 0.77 -Max. Drawdown [%] -33.08 -Avg. Drawdown [%] -5.58 -Max. Drawdown Duration 688 days 00:00:00 -Avg. Drawdown Duration 41 days 00:00:00 -# Trades 93 -Win Rate [%] 53.76 -Best Trade [%] 57.12 -Worst Trade [%] -16.63 -Avg. Trade [%] 1.96 -Max. Trade Duration 121 days 00:00:00 -Avg. Trade Duration 32 days 00:00:00 -Profit Factor 2.13 -Expectancy [%] 6.91 -SQN 1.78 -Kelly Criterion 0.6134 -_strategy SmaCross(n1=10, n2=20) -_equity_curve Equ... -_trades Size EntryB... -dtype: object -``` -[![plot of trading simulation](https://i.imgur.com/xRFNHfg.png)](https://kernc.github.io/backtesting.py/#example) - -Find more usage examples in the [documentation]. - - -Features --------- -* Simple, well-documented API -* Blazing fast execution -* Built-in optimizer -* Library of composable base strategies and utilities -* Indicator-library-agnostic -* Supports _any_ financial instrument with candlestick data -* Detailed results -* Interactive visualizations - -![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png) - - -Bugs ----- -Before reporting bugs or posting to the -[discussion board](https://github.com/kernc/backtesting.py/discussions), -please read [contributing guidelines](CONTRIBUTING.md), particularly the section -about crafting useful bug reports and ```` ``` ````-fencing your code. We thank you! - - -Alternatives ------------- -See [alternatives.md] for a list of alternative Python -backtesting frameworks and related packages. - -[alternatives.md]: https://github.com/kernc/backtesting.py/blob/master/doc/alternatives.md diff --git a/SlopeMomentum.html b/SlopeMomentum.html deleted file mode 100644 index 3cad09c..0000000 --- a/SlopeMomentum.html +++ /dev/null @@ -1,61 +0,0 @@ - - - - - SlopeMomentum.html - - - - - -
- - - - - \ No newline at end of file diff --git a/SmaCross(fast=4,slow=6).html b/SmaCross(fast=4,slow=6).html deleted file mode 100644 index ba2c125..0000000 --- a/SmaCross(fast=4,slow=6).html +++ /dev/null @@ -1,61 +0,0 @@ - - - - - SmaCross(fast=4,slow=6).html - - - - - -
- - - - - \ No newline at end of file diff --git a/SmaCross.html b/SmaCross.html deleted file mode 100644 index 3c557b2..0000000 --- a/SmaCross.html +++ /dev/null @@ -1,61 +0,0 @@ - - - - - SmaCross.html - - - - - -
- - - - - \ No newline at end of file diff --git a/docker/Dockerfile b/docker/Dockerfile index 4cc97ee..e0b6bc3 100644 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -25,9 +25,7 @@ RUN curl -sSL https://install.python-poetry.org | python3 - \ WORKDIR /app/${PROJECT_DIR} COPY ${PROJECT_DIR}/pyproject.toml ${PROJECT_DIR}/poetry.lock ./ -COPY fx-strategy ../fx-strategy -COPY vendors/backtesting.py ../vendors/backtesting.py -# RUN poetry install --only main +RUN poetry install --only main ################################################## ## PRODUCTION ## @@ -44,7 +42,7 @@ RUN apt-get update \ curl \ build-essential -ENV PATH="/app/${PROJECT_DIR}/.venv/bin:$PATH" +ENV PATH="/app/.venv/bin:$PATH" ENV APP_USER app ENV APP_GROUP app RUN groupadd ${APP_GROUP} @@ -53,11 +51,9 @@ RUN useradd -g ${APP_GROUP} ${APP_USER} WORKDIR /app COPY --chown=${APP_USER}:${APP_GROUP} ${PROJECT_DIR}/ ./ COPY --from=base /app . - -WORKDIR /app/${PROJECT_DIR} USER ${APP_USER} -ENTRYPOINT ["/app/${PROJECT_DIR}/scripts/entrypoint.sh"] +ENTRYPOINT ["/app/scripts/entrypoint.sh"] ################################################## ## DEVELOPMENT ## @@ -65,7 +61,7 @@ ENTRYPOINT ["/app/${PROJECT_DIR}/scripts/entrypoint.sh"] FROM base as development -ENV PATH="/app/${PROJECT_DIR}/.venv/bin:$PATH" +ENV PATH="/app/.venv/bin:$PATH" ENV APP_USER app ENV APP_GROUP app RUN groupadd ${APP_GROUP} @@ -77,10 +73,7 @@ RUN set -ex \ WORKDIR /app COPY --chown=${APP_USER}:${APP_GROUP} . ./ - -WORKDIR /app/${PROJECT_DIR} RUN poetry install -RUN chown ${APP_USER}:${APP_GROUP} . USER ${APP_USER} -ENTRYPOINT ["/app/${PROJECT_DIR}/scripts/entrypoint.sh"] \ No newline at end of file +ENTRYPOINT ["/app/scripts/entrypoint.sh"] \ No newline at end of file diff --git a/docker/docker-compose.yaml b/docker/docker-compose.yaml index ffcdbd2..291dd73 100644 --- a/docker/docker-compose.yaml +++ b/docker/docker-compose.yaml @@ -44,4 +44,4 @@ services: extends: file: docker-compose.base.yaml service: base - entrypoint: ["/app/fx-backtest/scripts/test.sh"] \ No newline at end of file + entrypoint: ["/app/scripts/test.sh"] \ No newline at end of file diff --git a/fx_backtest/__init__.py b/fx_backtest/__init__.py index 79616eb..e69de29 100644 --- a/fx_backtest/__init__.py +++ b/fx_backtest/__init__.py @@ -1,63 +0,0 @@ -""" - -![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png) - -## Manuals - -* [**Quick Start User Guide**](../examples/Quick Start User Guide.html) - -## Tutorials - -* [Library of Utilities and Composable Base Strategies](../examples/Strategies Library.html) -* [Multiple Time Frames](../examples/Multiple Time Frames.html) -* [**Parameter Heatmap & Optimization**](../examples/Parameter Heatmap & Optimization.html) -* [Trading with Machine Learning](../examples/Trading with Machine Learning.html) - -These tutorials are also available as live Jupyter notebooks: -[![Binder](https://mybinder.org/badge_logo.svg)][binder] -[![Google Colab](https://colab.research.google.com/assets/colab-badge.png)][colab] -
In Colab, you might have to `!pip install backtesting`. - -[binder]: \ - https://mybinder.org/v2/gh/kernc/backtesting.py/master?\ -urlpath=lab%2Ftree%2Fdoc%2Fexamples%2FQuick%20Start%20User%20Guide.ipynb -[colab]: https://colab.research.google.com/github/kernc/backtesting.py/ - -## Example Strategies - -* (contributions welcome) - - -.. tip:: - For an overview of recent changes, see - [What's New](https://github.com/kernc/backtesting.py/blob/master/CHANGELOG.md). - - -## FAQ - -Some answers to frequent and popular questions can be found on the -[issue tracker](https://github.com/kernc/backtesting.py/issues?q=label%3Aquestion+-label%3Ainvalid) -or on the [discussion forum](https://github.com/kernc/backtesting.py/discussions) on GitHub. -Please use the search! - -## License - -This software is licensed under the terms of [AGPL 3.0]{: rel=license}, -meaning you can use it for any reasonable purpose and remain in -complete ownership of all the excellent trading strategies you produce, -but you are also encouraged to make sure any upgrades to _Backtesting.py_ -itself find their way back to the community. - -[AGPL 3.0]: https://www.gnu.org/licenses/agpl-3.0.html - -# API Reference Documentation -""" - -try: - from ._version import version as __version__ -except ImportError: - __version__ = "?.?.?" # Package not installed - -from . import lib # noqa: F401 -from ._plotting import set_bokeh_output # noqa: F401 -from .backtesting import Backtest, Strategy # noqa: F401 diff --git a/fx_backtest/_exceptions.py b/fx_backtest/_exceptions.py deleted file mode 100644 index c14c378..0000000 --- a/fx_backtest/_exceptions.py +++ /dev/null @@ -1,2 +0,0 @@ -class _OutOfMoneyError(Exception): - pass diff --git a/fx_backtest/_interfaces.py b/fx_backtest/_interfaces.py deleted file mode 100644 index 627013a..0000000 --- a/fx_backtest/_interfaces.py +++ /dev/null @@ -1,16 +0,0 @@ -from abc import abstractmethod - -from fx_backtest._util import _Data - - -class IBroker: - - @property - @abstractmethod - def data(self) -> _Data: - raise NotImplementedError() - - @property - @abstractmethod - def last_price(self) -> float: - raise NotImplementedError() diff --git a/fx_backtest/_models.py b/fx_backtest/_models.py deleted file mode 100644 index e066241..0000000 --- a/fx_backtest/_models.py +++ /dev/null @@ -1,441 +0,0 @@ -from copy import copy -from math import copysign -from typing import Optional, Union - -import numpy as np -import pandas as pd - -from fx_backtest._interfaces import IBroker - -__pdoc__ = { - "Strategy.__init__": False, - "Order.__init__": False, - "Position.__init__": False, - "Trade.__init__": False, -} - - -class Order: - """ - Place new orders through `Strategy.buy()` and `Strategy.sell()`. - Query existing orders through `Strategy.orders`. - - When an order is executed or [filled], it results in a `Trade`. - - If you wish to modify aspects of a placed but not yet filled order, - cancel it and place a new one instead. - - All placed orders are [Good 'Til Canceled]. - - [filled]: https://www.investopedia.com/terms/f/fill.asp - [Good 'Til Canceled]: https://www.investopedia.com/terms/g/gtc.asp - """ - - def __init__( - self, - size: float, - limit_price: Optional[float] = None, - stop_price: Optional[float] = None, - sl_price: Optional[float] = None, - tp_price: Optional[float] = None, - parent_trade: Optional["Trade"] = None, - tag: object = None, - ): - assert size != 0 - self.__size = size - self.__limit_price = limit_price - self.__stop_price = stop_price - self.__sl_price = sl_price - self.__tp_price = tp_price - self.__parent_trade = parent_trade - self.__tag = tag - - def _replace(self, **kwargs): - for k, v in kwargs.items(): - setattr(self, f"_{self.__class__.__qualname__}__{k}", v) - return self - - def __repr__(self): - return "".format( - ", ".join( - f"{param}={round(value, 5)}" - for param, value in ( - ("size", self.__size), - ("limit", self.__limit_price), - ("stop", self.__stop_price), - ("sl", self.__sl_price), - ("tp", self.__tp_price), - ("contingent", self.is_contingent), - ("tag", self.__tag), - ) - if value is not None - ) - ) - - # Fields getters - - @property - def size(self) -> float: - """ - Order size (negative for short orders). - - If size is a value between 0 and 1, it is interpreted as a fraction of current - available liquidity (cash plus `Position.pl` minus used margin). - A value greater than or equal to 1 indicates an absolute number of units. - """ - return self.__size - - @property - def limit(self) -> Optional[float]: - """ - Order limit price for [limit orders], or None for [market orders], - which are filled at next available price. - - [limit orders]: https://www.investopedia.com/terms/l/limitorder.asp - [market orders]: https://www.investopedia.com/terms/m/marketorder.asp - """ - return self.__limit_price - - @property - def stop(self) -> Optional[float]: - """ - Order stop price for [stop-limit/stop-market][_] order, - otherwise None if no stop was set, or the stop price has already been hit. - - [_]: https://www.investopedia.com/terms/s/stoporder.asp - """ - return self.__stop_price - - @property - def sl(self) -> Optional[float]: - """ - A stop-loss price at which, if set, a new contingent stop-market order - will be placed upon the `Trade` following this order's execution. - See also `Trade.sl`. - """ - return self.__sl_price - - @property - def tp(self) -> Optional[float]: - """ - A take-profit price at which, if set, a new contingent limit order - will be placed upon the `Trade` following this order's execution. - See also `Trade.tp`. - """ - return self.__tp_price - - @property - def parent_trade(self): - return self.__parent_trade - - @property - def tag(self): - """ - Arbitrary value (such as a string) which, if set, enables tracking - of this order and the associated `Trade` (see `Trade.tag`). - """ - return self.__tag - - __pdoc__["Order.parent_trade"] = False - - # Extra properties - - @property - def is_long(self): - """True if the order is long (order size is positive).""" - return self.__size > 0 - - @property - def is_short(self): - """True if the order is short (order size is negative).""" - return self.__size < 0 - - @property - def is_contingent(self): - """ - True for [contingent] orders, i.e. [OCO] stop-loss and take-profit bracket orders - placed upon an active trade. Remaining contingent orders are canceled when - their parent `Trade` is closed. - - You can modify contingent orders through `Trade.sl` and `Trade.tp`. - - [contingent]: https://www.investopedia.com/terms/c/contingentorder.asp - [OCO]: https://www.investopedia.com/terms/o/oco.asp - """ - return bool(self.__parent_trade) - - def cancel(self): - trade = self.__parent_trade - if trade: - if self is trade._sl_order: - trade._replace(sl_order=None) - elif self is trade._tp_order: - trade._replace(tp_order=None) - else: - raise RuntimeError() - - -class Trade: - """ - When an `Order` is filled, it results in an active `Trade`. - Find active trades in `Strategy.trades` and closed, settled trades in `Strategy.closed_trades`. - """ - - def __init__(self, broker: IBroker, size: int, entry_price: float, entry_bar, tag): - self.__broker = broker - self.__size = size - self.__entry_price = entry_price - self.__exit_price: Optional[float] = None - self.__entry_bar: int = entry_bar - self.__exit_bar: Optional[int] = None - self.__sl_order: Optional[Order] = None - self.__tp_order: Optional[Order] = None - self.__tag = tag - - def __repr__(self): - return ( - f'' - ) - - def _replace(self, **kwargs): - for k, v in kwargs.items(): - setattr(self, f"_{self.__class__.__qualname__}__{k}", v) - return self - - def _copy(self, **kwargs): - return copy(self)._replace(**kwargs) - - def close(self, portion: float = 1.0): - """Place new `Order` to close `portion` of the trade at next market price.""" - assert 0 < portion <= 1, "portion must be a fraction between 0 and 1" - size = copysign(max(1, round(abs(self.__size) * portion)), -self.__size) - return Order(size, parent_trade=self, tag=self.__tag) - - # Fields getters - - @property - def size(self): - """Trade size (volume; negative for short trades).""" - return self.__size - - @property - def entry_price(self) -> float: - """Trade entry price.""" - return self.__entry_price - - @property - def exit_price(self) -> Optional[float]: - """Trade exit price (or None if the trade is still active).""" - return self.__exit_price - - @property - def entry_bar(self) -> int: - """Candlestick bar index of when the trade was entered.""" - return self.__entry_bar - - @property - def exit_bar(self) -> Optional[int]: - """ - Candlestick bar index of when the trade was exited - (or None if the trade is still active). - """ - return self.__exit_bar - - @property - def tag(self): - """ - A tag value inherited from the `Order` that opened - this trade. - - This can be used to track trades and apply conditional - logic / subgroup analysis. - - See also `Order.tag`. - """ - return self.__tag - - @property - def _sl_order(self): - return self.__sl_order - - @property - def _tp_order(self): - return self.__tp_order - - # Extra properties - - @property - def entry_time(self) -> Union[pd.Timestamp, int]: - """Datetime of when the trade was entered.""" - return self.__broker.data.index[self.__entry_bar] - - @property - def exit_time(self) -> Optional[Union[pd.Timestamp, int]]: - """Datetime of when the trade was exited.""" - if self.__exit_bar is None: - return None - return self.__broker.data.index[self.__exit_bar] - - @property - def is_long(self): - """True if the trade is long (trade size is positive).""" - return self.__size > 0 - - @property - def is_short(self): - """True if the trade is short (trade size is negative).""" - return not self.is_long - - @property - def pl(self): - """Trade profit (positive) or loss (negative) in cash units.""" - price = self.__exit_price or self.__broker.last_price - return self.__size * (price - self.__entry_price) - - @property - def pl_pct(self): - """Trade profit (positive) or loss (negative) in percent.""" - price = self.__exit_price or self.__broker.last_price - return copysign(1, self.__size) * (price / self.__entry_price - 1) - - @property - def value(self): - """Trade total value in cash (volume × price).""" - price = self.__exit_price or self.__broker.last_price - return abs(self.__size) * price - - # SL/TP management API - - @property - def sl(self): - """ - Stop-loss price at which to close the trade. - - This variable is writable. By assigning it a new price value, - you create or modify the existing SL order. - By assigning it `None`, you cancel it. - """ - return self.__sl_order and self.__sl_order.stop - - @sl.setter - def sl(self, price: float): - self.__set_contingent("sl", price) - - @property - def tp(self): - """ - Take-profit price at which to close the trade. - - This property is writable. By assigning it a new price value, - you create or modify the existing TP order. - By assigning it `None`, you cancel it. - """ - return self.__tp_order and self.__tp_order.limit - - @tp.setter - def tp(self, price: float): - self.__set_contingent("tp", price) - - def __set_contingent(self, type, price): - assert type in ("sl", "tp") - assert price is None or 0 < price < np.inf - attr = f"_{self.__class__.__qualname__}__{type}_order" - order: Order = getattr(self, attr) - if order: - order.cancel() - if price: - kwargs = {"stop": price} if type == "sl" else {"limit": price} - order = self.__broker.new_order( - -self.size, trade=self, tag=self.tag, **kwargs - ) - setattr(self, attr, order) - - -class _Orders(tuple): - """ - TODO: remove this class. Only for deprecation. - """ - - def cancel(self): - """Cancel all non-contingent (i.e. SL/TP) orders.""" - for order in self: - if not order.is_contingent: - order.cancel() - - def __getattr__(self, item): - # TODO: Warn on deprecations from the previous version. Remove in the next. - removed_attrs = ( - "entry", - "set_entry", - "is_long", - "is_short", - "sl", - "tp", - "set_sl", - "set_tp", - ) - if item in removed_attrs: - raise AttributeError( - f'Strategy.orders.{"/.".join(removed_attrs)} were removed in' - "Backtesting 0.2.0. " - "Use `Order` API instead. See docs." - ) - raise AttributeError(f"'tuple' object has no attribute {item!r}") - - -class Position: - """ - Currently held asset position, available as - `backtesting.backtesting.Strategy.position` within - `backtesting.backtesting.Strategy.next`. - Can be used in boolean contexts, e.g. - - if self.position: - ... # we have a position, either long or short - """ - - def __init__(self, trades: list[Trade]): - self._trades = trades - - def __bool__(self): - return self.size != 0 - - @property - def size(self) -> float: - """Position size in units of asset. Negative if position is short.""" - return sum(trade.size for trade in self._trades) - - @property - def pl(self) -> float: - """Profit (positive) or loss (negative) of the current position in cash units.""" - return sum(trade.pl for trade in self._trades) - - @property - def pl_pct(self) -> float: - """Profit (positive) or loss (negative) of the current position in percent.""" - weights = np.abs([trade.size for trade in self._trades]) - weights = weights / weights.sum() - pl_pcts = np.array([trade.pl_pct for trade in self._trades]) - return (pl_pcts * weights).sum() - - @property - def is_long(self) -> bool: - """True if the position is long (position size is positive).""" - return self.size > 0 - - @property - def is_short(self) -> bool: - """True if the position is short (position size is negative).""" - return self.size < 0 - - def close(self, portion: float = 1.0): - """ - Close portion of position by closing `portion` of each active trade. See `Trade.close`. - """ - for trade in self._trades: - trade.close(portion) - - def __repr__(self): - return f"" diff --git a/fx_backtest/_plotting.py b/fx_backtest/_plotting.py deleted file mode 100644 index 7b2b819..0000000 --- a/fx_backtest/_plotting.py +++ /dev/null @@ -1,964 +0,0 @@ -import os -import re -import sys -import warnings -from colorsys import hls_to_rgb, rgb_to_hls -from functools import partial -from itertools import combinations, cycle -from typing import Callable, List, Union - -import numpy as np -import pandas as pd -from bokeh.colors import RGB -from bokeh.colors.named import lime as BULL_COLOR -from bokeh.colors.named import tomato as BEAR_COLOR -from bokeh.models import ( # type: ignore - ColumnDataSource, - CrosshairTool, - CustomJS, - DatetimeTickFormatter, - HoverTool, - LinearColorMapper, - NumeralTickFormatter, - Range1d, - Span, - WheelZoomTool, -) -from bokeh.plotting import figure as _figure - -try: - from bokeh.models import CustomJSTickFormatter -except ImportError: # Bokeh < 3.0 - from bokeh.models import FuncTickFormatter as CustomJSTickFormatter # type: ignore - -from backtesting._util import _as_list, _data_period, _Indicator -from bokeh.io import output_file, output_notebook, show -from bokeh.io.state import curstate -from bokeh.layouts import gridplot -from bokeh.palettes import Category10 -from bokeh.transform import factor_cmap - -with open( - os.path.join(os.path.dirname(__file__), "autoscale_cb.js"), encoding="utf-8" -) as _f: - _AUTOSCALE_JS_CALLBACK = _f.read() - -IS_JUPYTER_NOTEBOOK = "JPY_PARENT_PID" in os.environ - -if IS_JUPYTER_NOTEBOOK: - warnings.warn( - "Jupyter Notebook detected. " - "Setting Bokeh output to notebook. " - "This may not work in Jupyter clients without JavaScript " - "support (e.g. PyCharm, Spyder IDE). " - "Reset with `backtesting.set_bokeh_output(notebook=False)`." - ) - output_notebook() - - -def set_bokeh_output(notebook=False): - """ - Set Bokeh to output either to a file or Jupyter notebook. - By default, Bokeh outputs to notebook if running from within - notebook was detected. - """ - global IS_JUPYTER_NOTEBOOK - IS_JUPYTER_NOTEBOOK = notebook - - -def _windos_safe_filename(filename): - if sys.platform.startswith("win"): - return re.sub(r"[^a-zA-Z0-9,_-]", "_", filename.replace("=", "-")) - return filename - - -def _bokeh_reset(filename=None): - curstate().reset() - if filename: - if not filename.endswith(".html"): - filename += ".html" - output_file(filename, title=filename) - elif IS_JUPYTER_NOTEBOOK: - curstate().output_notebook() - - -def colorgen(): - yield from cycle(Category10[10]) - - -def lightness(color, lightness=0.94): - rgb = np.array([color.r, color.g, color.b]) / 255 - h, _, s = rgb_to_hls(*rgb) - rgb = np.array(hls_to_rgb(h, lightness, s)) * 255.0 - return RGB(*rgb) - - -_MAX_CANDLES = 10_000 - - -def _maybe_resample_data(resample_rule, df, indicators, equity_data, trades): - if isinstance(resample_rule, str): - freq = resample_rule - else: - if resample_rule is False or len(df) <= _MAX_CANDLES: - return df, indicators, equity_data, trades - - freq_minutes = pd.Series( - { - "1T": 1, - "5T": 5, - "10T": 10, - "15T": 15, - "30T": 30, - "1H": 60, - "2H": 60 * 2, - "4H": 60 * 4, - "8H": 60 * 8, - "1D": 60 * 24, - "1W": 60 * 24 * 7, - "1M": np.inf, - } - ) - timespan = df.index[-1] - df.index[0] - require_minutes = (timespan / _MAX_CANDLES).total_seconds() // 60 - freq = freq_minutes.where(freq_minutes >= require_minutes).first_valid_index() - warnings.warn( - f"Data contains too many candlesticks to plot; downsampling to {freq!r}. " - "See `Backtest.plot(resample=...)`" - ) - - from .lib import _EQUITY_AGG, OHLCV_AGG, TRADES_AGG - - df = df.resample(freq, label="right").agg(OHLCV_AGG).dropna() - - indicators = [ - _Indicator( - i.df.resample(freq, label="right") - .mean() - .dropna() - .reindex(df.index) - .values.T, - **dict( - i._opts, - name=i.name, - # Replace saved index with the resampled one - index=df.index, - ), - ) - for i in indicators - ] - assert not indicators or indicators[0].df.index.equals(df.index) - - equity_data = ( - equity_data.resample(freq, label="right").agg(_EQUITY_AGG).dropna(how="all") - ) - assert equity_data.index.equals(df.index) - - def _weighted_returns(s, trades=trades): - df = trades.loc[s.index] - return ((df["Size"].abs() * df["ReturnPct"]) / df["Size"].abs().sum()).sum() - - def _group_trades(column): - def f(s, new_index=pd.Index(df.index.view(int)), bars=trades[column]): - if s.size: - # Via int64 because on pandas recently broken datetime - mean_time = int(bars.loc[s.index].view(int).mean()) - new_bar_idx = new_index.get_indexer([mean_time], method="nearest")[0] - return new_bar_idx - - return f - - if len(trades): # Avoid pandas "resampling on Int64 index" error - trades = ( - trades.assign(count=1) - .resample(freq, on="ExitTime", label="right") - .agg( - dict( - TRADES_AGG, - ReturnPct=_weighted_returns, - count="sum", - EntryBar=_group_trades("EntryTime"), - ExitBar=_group_trades("ExitTime"), - ) - ) - .dropna() - ) - - return df, indicators, equity_data, trades - - -def plot( - *, - results: pd.Series, - df: pd.DataFrame, - indicators: List[_Indicator], - filename="", - plot_width=None, - plot_equity=True, - plot_return=False, - plot_pl=True, - plot_volume=True, - plot_drawdown=False, - plot_trades=True, - smooth_equity=False, - relative_equity=True, - superimpose=True, - resample=True, - reverse_indicators=True, - show_legend=True, - open_browser=True, -): - """ - Like much of GUI code everywhere, this is a mess. - """ - # We need to reset global Bokeh state, otherwise subsequent runs of - # plot() contain some previous run's cruft data (was noticed when - # TestPlot.test_file_size() test was failing). - if not filename and not IS_JUPYTER_NOTEBOOK: - filename = _windos_safe_filename(str(results._strategy)) - _bokeh_reset(filename) - - COLORS = [BEAR_COLOR, BULL_COLOR] - BAR_WIDTH = 0.8 - - assert df.index.equals(results["_equity_curve"].index) - equity_data = results["_equity_curve"].copy(deep=False) - trades = results["_trades"] - - plot_volume = plot_volume and not df.Volume.isnull().all() - plot_equity = plot_equity and not trades.empty - plot_return = plot_return and not trades.empty - plot_pl = plot_pl and not trades.empty - is_datetime_index = isinstance(df.index, pd.DatetimeIndex) - - from .lib import OHLCV_AGG - - # ohlc df may contain many columns. We're only interested in, and pass on to Bokeh, these - df = df[list(OHLCV_AGG.keys())].copy(deep=False) - - # Limit data to max_candles - if is_datetime_index: - df, indicators, equity_data, trades = _maybe_resample_data( - resample, df, indicators, equity_data, trades - ) - - df.index.name = None # Provides source name @index - df["datetime"] = df.index # Save original, maybe datetime index - df = df.reset_index(drop=True) - equity_data = equity_data.reset_index(drop=True) - index = df.index - - new_bokeh_figure = partial( - _figure, - x_axis_type="linear", - width=plot_width, - height=400, - tools="xpan,xwheel_zoom,box_zoom,undo,redo,reset,save", - active_drag="xpan", - active_scroll="xwheel_zoom", - ) - - pad = (index[-1] - index[0]) / 20 - - _kwargs = ( - dict( - x_range=Range1d( - index[0], - index[-1], - min_interval=10, - bounds=(index[0] - pad, index[-1] + pad), - ) - ) - if index.size > 1 - else {} - ) - fig_ohlc = new_bokeh_figure(**_kwargs) - figs_above_ohlc, figs_below_ohlc = [], [] - - source = ColumnDataSource(df) - source.add( - (df.Close >= df.Open).values.astype(np.uint8).astype(str).tolist(), "inc" - ) - - trade_source = ColumnDataSource( - dict( - index=trades["ExitBar"], - datetime=trades["ExitTime"], - exit_price=trades["ExitPrice"], - size=trades["Size"], - tp=trades["TakeProfit"], - sl=trades["StopLoss"], - returns_positive=(trades["ReturnPct"] > 0).astype(int).astype(str), - ) - ) - - inc_cmap = factor_cmap("inc", COLORS, ["0", "1"]) - cmap = factor_cmap("returns_positive", COLORS, ["0", "1"]) - colors_darker = [lightness(BEAR_COLOR, 0.35), lightness(BULL_COLOR, 0.35)] - trades_cmap = factor_cmap("returns_positive", colors_darker, ["0", "1"]) - - if is_datetime_index: - fig_ohlc.xaxis.formatter = CustomJSTickFormatter( - args=dict( - axis=fig_ohlc.xaxis[0], - formatter=DatetimeTickFormatter(days="%a, %d %b", months="%m/%Y"), - source=source, - ), - code=""" -this.labels = this.labels || formatter.doFormat(ticks - .map(i => source.data.datetime[i]) - .filter(t => t !== undefined)); -return this.labels[index] || ""; - """, - ) - - NBSP = "\N{NBSP}" * 4 # noqa: E999 - ohlc_extreme_values = df[["High", "Low"]].copy(deep=False) - ohlc_tooltips = [ - ("x, y", NBSP.join(("$index", "$y{0,0.0[0000]}"))), - ( - "OHLC", - NBSP.join( - ( - "@Open{0,0.0[0000]}", - "@High{0,0.0[0000]}", - "@Low{0,0.0[0000]}", - "@Close{0,0.0[0000]}", - ) - ), - ), - ("Volume", "@Volume{0,0}"), - ] - - def new_indicator_figure(**kwargs): - kwargs.setdefault("height", 90) - fig = new_bokeh_figure( - x_range=fig_ohlc.x_range, - active_scroll="xwheel_zoom", - active_drag="xpan", - **kwargs, - ) - fig.xaxis.visible = False - fig.yaxis.minor_tick_line_color = None - return fig - - def set_tooltips(fig, tooltips=(), vline=True, renderers=()): - tooltips = list(tooltips) - renderers = list(renderers) - - if is_datetime_index: - formatters = {"@datetime": "datetime"} - tooltips = [("Date", "@datetime{%c}")] + tooltips - else: - formatters = {} - tooltips = [("#", "@index")] + tooltips - fig.add_tools( - HoverTool( - point_policy="follow_mouse", - renderers=renderers, - formatters=formatters, - tooltips=tooltips, - mode="vline" if vline else "mouse", - ) - ) - - def _plot_equity_section(is_return=False): - """Equity section""" - # Max DD Dur. line - equity = equity_data["Equity"].copy() - dd_end = equity_data["DrawdownDuration"].idxmax() - if np.isnan(dd_end): - dd_start = dd_end = equity.index[0] - else: - dd_start = equity[:dd_end].idxmax() - # If DD not extending into the future, get exact point of intersection with equity - if dd_end != equity.index[-1]: - dd_end = np.interp( - equity[dd_start], - (equity[dd_end - 1], equity[dd_end]), - (dd_end - 1, dd_end), - ) - - if smooth_equity: - interest_points = pd.Index( - [ - # Beginning and end - equity.index[0], - equity.index[-1], - # Peak equity and peak DD - equity.idxmax(), - equity_data["DrawdownPct"].idxmax(), - # Include max dd end points. Otherwise the MaxDD line looks amiss. - dd_start, - int(dd_end), - min(int(dd_end + 1), equity.size - 1), - ] - ) - select = pd.Index(trades["ExitBar"]).union(interest_points) - select = select.unique().dropna() - equity = equity.iloc[select].reindex(equity.index) - equity.interpolate(inplace=True) - - assert equity.index.equals(equity_data.index) - - if relative_equity: - equity /= equity.iloc[0] - if is_return: - equity -= equity.iloc[0] - - yaxis_label = "Return" if is_return else "Equity" - source_key = "eq_return" if is_return else "equity" - source.add(equity, source_key) - fig = new_indicator_figure( - y_axis_label=yaxis_label, **({} if plot_drawdown else dict(height=110)) - ) - - # High-watermark drawdown dents - fig.patch( - "index", - "equity_dd", - source=ColumnDataSource( - dict( - index=np.r_[index, index[::-1]], - equity_dd=np.r_[equity, equity.cummax()[::-1]], - ) - ), - fill_color="#ffffea", - line_color="#ffcb66", - ) - - # Equity line - r = fig.line("index", source_key, source=source, line_width=1.5, line_alpha=1) - if relative_equity: - tooltip_format = f"@{source_key}{{+0,0.[000]%}}" - tick_format = "0,0.[00]%" - legend_format = "{:,.0f}%" - else: - tooltip_format = f"@{source_key}{{$ 0,0}}" - tick_format = "$ 0.0 a" - legend_format = "${:,.0f}" - set_tooltips(fig, [(yaxis_label, tooltip_format)], renderers=[r]) - fig.yaxis.formatter = NumeralTickFormatter(format=tick_format) - - # Peaks - argmax = equity.idxmax() - fig.scatter( - argmax, - equity[argmax], - legend_label="Peak ({})".format( - legend_format.format(equity[argmax] * (100 if relative_equity else 1)) - ), - color="cyan", - size=8, - ) - fig.scatter( - index[-1], - equity.values[-1], - legend_label="Final ({})".format( - legend_format.format(equity.iloc[-1] * (100 if relative_equity else 1)) - ), - color="blue", - size=8, - ) - - if not plot_drawdown: - drawdown = equity_data["DrawdownPct"] - argmax = drawdown.idxmax() - fig.scatter( - argmax, - equity[argmax], - legend_label="Max Drawdown (-{:.1f}%)".format(100 * drawdown[argmax]), - color="red", - size=8, - ) - dd_timedelta_label = ( - df["datetime"].iloc[int(round(dd_end))] - df["datetime"].iloc[dd_start] - ) - fig.line( - [dd_start, dd_end], - equity.iloc[dd_start], - line_color="red", - line_width=2, - legend_label=f"Max Dd Dur. ({dd_timedelta_label})".replace( - " 00:00:00", "" - ).replace("(0 days ", "("), - ) - - figs_above_ohlc.append(fig) - - def _plot_drawdown_section(): - """Drawdown section""" - fig = new_indicator_figure(y_axis_label="Drawdown") - drawdown = equity_data["DrawdownPct"] - argmax = drawdown.idxmax() - source.add(drawdown, "drawdown") - r = fig.line("index", "drawdown", source=source, line_width=1.3) - fig.scatter( - argmax, - drawdown[argmax], - legend_label="Peak (-{:.1f}%)".format(100 * drawdown[argmax]), - color="red", - size=8, - ) - set_tooltips(fig, [("Drawdown", "@drawdown{-0.[0]%}")], renderers=[r]) - fig.yaxis.formatter = NumeralTickFormatter(format="-0.[0]%") - return fig - - def _plot_pl_section(): - """Profit/Loss markers section""" - fig = new_indicator_figure(y_axis_label="Profit / Loss") - fig.add_layout( - Span( - location=0, - dimension="width", - line_color="#666666", - line_dash="dashed", - line_width=1, - ) - ) - returns_long = np.where(trades["Size"] > 0, trades["ReturnPct"], np.nan) - returns_short = np.where(trades["Size"] < 0, trades["ReturnPct"], np.nan) - size = trades["Size"].abs() - size = np.interp(size, (size.min(), size.max()), (8, 20)) - trade_source.add(returns_long, "returns_long") - trade_source.add(returns_short, "returns_short") - trade_source.add(size, "marker_size") - # if 'TakeProfit' in trades: - # trade_source.add(trades['TakeProfit'], 'tp') - # if 'StopLoss' in trades: - # trade_source.add(trades['StopLoss'], 'sl') - if "count" in trades: - trade_source.add(trades["count"], "count") - r1 = fig.scatter( - "index", - "returns_long", - source=trade_source, - fill_color=cmap, - marker="triangle", - line_color="black", - size="marker_size", - ) - r2 = fig.scatter( - "index", - "returns_short", - source=trade_source, - fill_color=cmap, - marker="inverted_triangle", - line_color="black", - size="marker_size", - ) - tooltips = [("Size", "@size{0,0}")] - - if "TakeProfit" in trades: - tooltips.append(("TP", "@tp")) - if "StopLoss" in trades: - tooltips.append(("SL", "@sl")) - if "count" in trades: - tooltips.append(("Count", "@count{0,0}")) - set_tooltips( - fig, - tooltips + [("P/L", "@returns_long{+0.[000]%}")], - vline=False, - renderers=[r1], - ) - set_tooltips( - fig, - tooltips + [("P/L", "@returns_short{+0.[000]%}")], - vline=False, - renderers=[r2], - ) - fig.yaxis.formatter = NumeralTickFormatter(format="0.[00]%") - return fig - - def _plot_volume_section(): - """Volume section""" - fig = new_indicator_figure(y_axis_label="Volume") - fig.xaxis.formatter = fig_ohlc.xaxis[0].formatter - fig.xaxis.visible = True - fig_ohlc.xaxis.visible = False # Show only Volume's xaxis - r = fig.vbar("index", BAR_WIDTH, "Volume", source=source, color=inc_cmap) - set_tooltips(fig, [("Volume", "@Volume{0.00 a}")], renderers=[r]) - fig.yaxis.formatter = NumeralTickFormatter(format="0 a") - return fig - - def _plot_superimposed_ohlc(): - """Superimposed, downsampled vbars""" - time_resolution = pd.DatetimeIndex(df["datetime"]).resolution - resample_rule = ( - superimpose - if isinstance(superimpose, str) - else dict(day="M", hour="D", minute="H", second="T", millisecond="S").get( - time_resolution - ) - ) - if not resample_rule: - warnings.warn( - f"'Can't superimpose OHLC data with rule '{resample_rule}'" - f"(index datetime resolution: '{time_resolution}'). Skipping.", - stacklevel=4, - ) - return - - df2 = ( - df.assign(_width=1) - .set_index("datetime") - .resample(resample_rule, label="left") - .agg(dict(OHLCV_AGG, _width="count")) - ) - - # Check if resampling was downsampling; error on upsampling - orig_freq = _data_period(df["datetime"]) - resample_freq = _data_period(df2.index) - if resample_freq < orig_freq: - raise ValueError( - "Invalid value for `superimpose`: Upsampling not supported." - ) - if resample_freq == orig_freq: - warnings.warn( - "Superimposed OHLC plot matches the original plot. Skipping.", - stacklevel=4, - ) - return - - df2.index = df2["_width"].cumsum().shift(1).fillna(0) - df2.index += df2["_width"] / 2 - 0.5 - df2["_width"] -= 0.1 # Candles don't touch - - df2["inc"] = (df2.Close >= df2.Open).astype(int).astype(str) - df2.index.name = None - source2 = ColumnDataSource(df2) - fig_ohlc.segment( - "index", "High", "index", "Low", source=source2, color="#bbbbbb" - ) - colors_lighter = [lightness(BEAR_COLOR, 0.92), lightness(BULL_COLOR, 0.92)] - fig_ohlc.vbar( - "index", - "_width", - "Open", - "Close", - source=source2, - line_color=None, - fill_color=factor_cmap("inc", colors_lighter, ["0", "1"]), - ) - - def _plot_ohlc(): - """Main OHLC bars""" - fig_ohlc.segment("index", "High", "index", "Low", source=source, color="black") - r = fig_ohlc.vbar( - "index", - BAR_WIDTH, - "Open", - "Close", - source=source, - line_color="black", - fill_color=inc_cmap, - ) - return r - - def _plot_ohlc_trades(): - """Trade entry / exit markers on OHLC plot""" - trade_source.add( - trades[["EntryBar", "ExitBar"]].values.tolist(), "position_lines_xs" - ) - trade_source.add( - trades[["EntryPrice", "ExitPrice"]].values.tolist(), "position_lines_ys" - ) - fig_ohlc.multi_line( - xs="position_lines_xs", - ys="position_lines_ys", - source=trade_source, - line_color=trades_cmap, - legend_label=f"Trades ({len(trades)})", - line_width=8, - line_alpha=1, - line_dash="dotted", - ) - - def _plot_indicators(): - """Strategy indicators""" - - def _too_many_dims(value): - assert value.ndim >= 2 - if value.ndim > 2: - warnings.warn( - f"Can't plot indicators with >2D ('{value.name}')", stacklevel=5 - ) - return True - return False - - class LegendStr(str): - # The legend string is such a string that only matches - # itself if it's the exact same object. This ensures - # legend items are listed separately even when they have the - # same string contents. Otherwise, Bokeh would always consider - # equal strings as one and the same legend item. - def __eq__(self, other): - return self is other - - ohlc_colors = colorgen() - indicator_figs = [] - - for i, value in enumerate(indicators): - value = np.atleast_2d(value) - - # Use .get()! A user might have assigned a Strategy.data-evolved - # _Array without Strategy.I() - if not value._opts.get("plot") or _too_many_dims(value): - continue - - is_overlay = value._opts["overlay"] - is_scatter = value._opts["scatter"] - if is_overlay: - fig = fig_ohlc - else: - fig = new_indicator_figure() - indicator_figs.append(fig) - tooltips = [] - colors = value._opts["color"] - colors = ( - colors - and cycle(_as_list(colors)) - or (cycle([next(ohlc_colors)]) if is_overlay else colorgen()) - ) - legend_label = LegendStr(value.name) - for j, arr in enumerate(value, 1): - color = next(colors) - source_name = f"{legend_label}_{i}_{j}" - if arr.dtype == bool: - arr = arr.astype(int) - source.add(arr, source_name) - tooltips.append(f"@{{{source_name}}}{{0,0.0[0000]}}") - if is_overlay: - ohlc_extreme_values[source_name] = arr - if is_scatter: - fig.scatter( - "index", - source_name, - source=source, - legend_label=legend_label, - color=color, - line_color="black", - fill_alpha=0.8, - marker="circle", - radius=BAR_WIDTH / 2 * 1.5, - ) - else: - fig.line( - "index", - source_name, - source=source, - legend_label=legend_label, - line_color=color, - line_width=1.3, - ) - else: - if is_scatter: - r = fig.scatter( - "index", - source_name, - source=source, - legend_label=LegendStr(legend_label), - color=color, - marker="circle", - radius=BAR_WIDTH / 2 * 0.9, - ) - else: - r = fig.line( - "index", - source_name, - source=source, - legend_label=LegendStr(legend_label), - line_color=color, - line_width=1.3, - ) - # Add dashed centerline just because - mean = float(pd.Series(arr).mean()) - if not np.isnan(mean) and ( - abs(mean) < 0.1 - or round(abs(mean), 1) == 0.5 - or round(abs(mean), -1) in (50, 100, 200) - ): - fig.add_layout( - Span( - location=float(mean), - dimension="width", - line_color="#666666", - line_dash="dashed", - line_width=0.5, - ) - ) - if is_overlay: - ohlc_tooltips.append((legend_label, NBSP.join(tooltips))) - else: - set_tooltips( - fig, - [(legend_label, NBSP.join(tooltips))], - vline=True, - renderers=[r], - ) - # If the sole indicator line on this figure, - # have the legend only contain text without the glyph - if len(value) == 1: - fig.legend.glyph_width = 0 - return indicator_figs - - # Construct figure ... - - if plot_equity: - _plot_equity_section() - - if plot_return: - _plot_equity_section(is_return=True) - - if plot_drawdown: - figs_above_ohlc.append(_plot_drawdown_section()) - - if plot_pl: - figs_above_ohlc.append(_plot_pl_section()) - - if plot_volume: - fig_volume = _plot_volume_section() - figs_below_ohlc.append(fig_volume) - - if superimpose and is_datetime_index: - _plot_superimposed_ohlc() - - ohlc_bars = _plot_ohlc() - if plot_trades: - _plot_ohlc_trades() - indicator_figs = _plot_indicators() - if reverse_indicators: - indicator_figs = indicator_figs[::-1] - figs_below_ohlc.extend(indicator_figs) - - set_tooltips(fig_ohlc, ohlc_tooltips, vline=True, renderers=[ohlc_bars]) - - source.add(ohlc_extreme_values.min(1).to_list(), "ohlc_low") - source.add(ohlc_extreme_values.max(1).to_list(), "ohlc_high") - - custom_js_args = dict(ohlc_range=fig_ohlc.y_range, source=source) - if plot_volume: - custom_js_args.update(volume_range=fig_volume.y_range) - - fig_ohlc.x_range.js_on_change( # type: ignore - "end", CustomJS(args=custom_js_args, code=_AUTOSCALE_JS_CALLBACK) - ) - - plots = figs_above_ohlc + [fig_ohlc] + figs_below_ohlc - linked_crosshair = CrosshairTool(dimensions="both") - - for f in plots: - if f.legend: - f.legend.visible = show_legend - f.legend.location = "top_left" - f.legend.border_line_width = 1 - f.legend.border_line_color = "#333333" - f.legend.padding = 5 - f.legend.spacing = 0 - f.legend.margin = 0 - f.legend.label_text_font_size = "8pt" - f.legend.click_policy = "hide" - f.min_border_left = 0 - f.min_border_top = 3 - f.min_border_bottom = 6 - f.min_border_right = 10 - f.outline_line_color = "#666666" - - f.add_tools(linked_crosshair) - wheelzoom_tool = next(wz for wz in f.tools if isinstance(wz, WheelZoomTool)) - wheelzoom_tool.maintain_focus = False # type: ignore - - kwargs = {} - if plot_width is None: - kwargs["sizing_mode"] = "stretch_width" - - fig = gridplot( - plots, - ncols=1, - toolbar_location="right", - toolbar_options=dict(logo=None), - merge_tools=True, - **kwargs, # type: ignore - ) - show(fig, browser=None if open_browser else "none") - return fig - - -def plot_heatmaps( - heatmap: pd.Series, - agg: Union[Callable, str], - ncols: int, - filename: str = "", - plot_width: int = 1200, - open_browser: bool = True, -): - if not ( - isinstance(heatmap, pd.Series) and isinstance(heatmap.index, pd.MultiIndex) - ): - raise ValueError( - "heatmap must be heatmap Series as returned by " - "`Backtest.optimize(..., return_heatmap=True)`" - ) - - _bokeh_reset(filename) - - param_combinations = combinations(heatmap.index.names, 2) - dfs = [ - heatmap.groupby(list(dims)).agg(agg).to_frame(name="_Value") - for dims in param_combinations - ] - plots = [] - cmap = LinearColorMapper( - palette="Viridis256", - low=min(df.min().min() for df in dfs), - high=max(df.max().max() for df in dfs), - nan_color="white", - ) - for df in dfs: - name1, name2 = df.index.names - level1 = df.index.levels[0].astype(str).tolist() # type: ignore - level2 = df.index.levels[1].astype(str).tolist() # type: ignore - df = df.reset_index() - df[name1] = df[name1].astype("str") - df[name2] = df[name2].astype("str") - - fig = _figure( - x_range=level1, - y_range=level2, - x_axis_label=name1, - y_axis_label=name2, - width=plot_width // ncols, - height=plot_width // ncols, - tools="box_zoom,reset,save", - tooltips=[ - (name1, "@" + name1), - (name2, "@" + name2), - ("Value", "@_Value{0.[000]}"), - ], - ) - fig.grid.grid_line_color = None - fig.axis.axis_line_color = None - fig.axis.major_tick_line_color = None - fig.axis.major_label_standoff = 0 - - fig.rect( - x=name1, - y=name2, - width=1, - height=1, - source=df, - line_color=None, - fill_color=dict(field="_Value", transform=cmap), - ) - plots.append(fig) - - fig = gridplot( - plots, # type: ignore - ncols=ncols, - toolbar_options=dict(logo=None), - toolbar_location="above", - merge_tools=True, - ) - - show(fig, browser=None if open_browser else "none") - return fig diff --git a/fx_backtest/_stats.py b/fx_backtest/_stats.py deleted file mode 100644 index fe6a20d..0000000 --- a/fx_backtest/_stats.py +++ /dev/null @@ -1,186 +0,0 @@ -from typing import TYPE_CHECKING, List, Union - -import numpy as np -import pandas as pd -from pandas import Series - -from ._util import _data_period - -if TYPE_CHECKING: - from .backtesting import Strategy, Trade - - -def compute_drawdown_duration_peaks(dd: pd.Series): - iloc = np.unique(np.r_[(dd == 0).values.nonzero()[0], len(dd) - 1]) # type: ignore - iloc = pd.Series(iloc, index=dd.index[iloc]) # type: ignore - df = iloc.to_frame("iloc").assign(prev=iloc.shift()) # type: ignore - df = df[df["iloc"] > df["prev"] + 1].astype(int) - - # If no drawdown since no trade, avoid below for pandas sake and return nan series - if not len(df): - return (dd.replace(0, np.nan),) * 2 - - df["duration"] = df["iloc"].map(dd.index.__getitem__) - df["prev"].map( - dd.index.__getitem__ - ) - df["peak_dd"] = df.apply( - lambda row: dd.iloc[row["prev"] : row["iloc"] + 1].max(), axis=1 - ) - df = df.reindex(dd.index) - return df["duration"], df["peak_dd"] - - -def geometric_mean(returns: pd.Series) -> float: - returns = returns.fillna(0) + 1 - if np.any(returns <= 0): - return 0 - return np.exp(np.log(returns).sum() / (len(returns) or np.nan)) - 1 - - -def compute_stats( - trades: Union[List["Trade"], pd.DataFrame], - equity: np.ndarray, - ohlc_data: pd.DataFrame, - strategy_instance: "Strategy", - risk_free_rate: float = 0, -) -> pd.Series: - assert -1 < risk_free_rate < 1 - - index = ohlc_data.index - dd = 1 - equity / np.maximum.accumulate(equity) - dd_dur, dd_peaks = compute_drawdown_duration_peaks(pd.Series(dd, index=index)) - - equity_df = pd.DataFrame( - {"Equity": equity, "DrawdownPct": dd, "DrawdownDuration": dd_dur}, index=index - ) - - if isinstance(trades, pd.DataFrame): - trades_df: pd.DataFrame = trades - else: - # Came straight from Backtest.run() - trades_df = pd.DataFrame( - { - "Size": [t.size for t in trades], - "EntryBar": [t.entry_bar for t in trades], - "ExitBar": [t.exit_bar for t in trades], - "EntryPrice": [t.entry_price for t in trades], - "ExitPrice": [t.exit_price for t in trades], - "PnL": [t.pl for t in trades], - "ReturnPct": [t.pl_pct for t in trades], - "EntryTime": [t.entry_time for t in trades], - "ExitTime": [t.exit_time for t in trades], - "Tag": [t.tag for t in trades], - "TakeProfit": [t.tp for t in trades], - "StopLoss": [t.sl for t in trades], - } - ) - trades_df["Duration"] = trades_df["ExitTime"] - trades_df["EntryTime"] - del trades - - pl = trades_df["PnL"] - returns = trades_df["ReturnPct"] - durations = trades_df["Duration"] - - def _round_timedelta(value, _period=_data_period(index)): - if not isinstance(value, pd.Timedelta): - return value - resolution = getattr(_period, "resolution_string", None) or _period.resolution - return value.ceil(resolution) - - s = pd.Series(dtype=object) - s.loc["Start"] = index[0] - s.loc["End"] = index[-1] - s.loc["Duration"] = s.End - s.Start - - have_position = np.repeat(0, len(index)) - for t in trades_df.itertuples(index=False): - have_position[t.EntryBar : t.ExitBar + 1] = 1 # type:ignore - - s.loc["Exposure Time [%]"] = ( - have_position.mean() * 100 - ) # In "n bars" time, not index time - s.loc["Equity Final [$]"] = equity[-1] - s.loc["Equity Peak [$]"] = equity.max() - s.loc["Return [%]"] = (equity[-1] - equity[0]) / equity[0] * 100 - c = ohlc_data.Close.values - s.loc["Buy & Hold Return [%]"] = (c[-1] - c[0]) / c[0] * 100 # long-only return - - gmean_day_return: float = 0 - day_returns = Series(np.array(np.nan)) - annual_trading_days = np.nan - if isinstance(index, pd.DatetimeIndex): - day_returns = equity_df["Equity"].resample("D").last().dropna().pct_change() - gmean_day_return = geometric_mean(day_returns) - annual_trading_days = float( - 365 - if index.dayofweek.to_series().between(5, 6).mean() > 2 / 7 * 0.6 - else 252 - ) - - # Annualized return and risk metrics are computed based on the (mostly correct) - # assumption that the returns are compounded. See: https://dx.doi.org/10.2139/ssrn.3054517 - # Our annualized return matches `empyrical.annual_return(day_returns)` whereas - # our risk doesn't; they use the simpler approach below. - annualized_return = (1 + gmean_day_return) ** annual_trading_days - 1 - s.loc["Return (Ann.) [%]"] = annualized_return * 100 - s.loc["Volatility (Ann.) [%]"] = ( - np.sqrt( - ( - day_returns.var(ddof=int(bool(day_returns.shape))) - + (1 + gmean_day_return) ** 2 # type:ignore - ) - ** annual_trading_days - - (1 + gmean_day_return) ** (2 * annual_trading_days) - ) - * 100 - ) # noqa: E501 - # s.loc['Return (Ann.) [%]'] = gmean_day_return * annual_trading_days * 100 - # s.loc['Risk (Ann.) [%]'] = day_returns.std(ddof=1) * np.sqrt(annual_trading_days) * 100 - - # Our Sharpe mismatches `empyrical.sharpe_ratio()` because they use arithmetic mean return - # and simple standard deviation - s.loc["Sharpe Ratio"] = (s.loc["Return (Ann.) [%]"] - risk_free_rate) / ( - s.loc["Volatility (Ann.) [%]"] or np.nan - ) # noqa: E501 - # Our Sortino mismatches `empyrical.sortino_ratio()` because they use arithmetic mean return - s.loc["Sortino Ratio"] = (annualized_return - risk_free_rate) / ( - np.sqrt(np.mean(day_returns.clip(-np.inf, 0) ** 2)) - * np.sqrt(annual_trading_days) - ) # noqa: E501 - max_dd = -np.nan_to_num(dd.max()) - s.loc["Calmar Ratio"] = annualized_return / (-max_dd or np.nan) - s.loc["Max. Drawdown [%]"] = max_dd * 100 - s.loc["Avg. Drawdown [%]"] = -dd_peaks.mean() * 100 - s.loc["Max. Drawdown Duration"] = _round_timedelta(dd_dur.max()) - s.loc["Avg. Drawdown Duration"] = _round_timedelta(dd_dur.mean()) - s.loc["# Trades"] = n_trades = len(trades_df) - win_rate = np.nan if not n_trades else (pl > 0).mean() - s.loc["Win Rate [%]"] = win_rate * 100 - s.loc["Best Trade [%]"] = returns.max() * 100 - s.loc["Worst Trade [%]"] = returns.min() * 100 - mean_return = geometric_mean(returns) - s.loc["Avg. Trade [%]"] = mean_return * 100 - s.loc["Max. Trade Duration"] = _round_timedelta(durations.max()) - s.loc["Avg. Trade Duration"] = _round_timedelta(durations.mean()) - s.loc["Profit Factor"] = returns[returns > 0].sum() / ( - abs(returns[returns < 0].sum()) or np.nan - ) # noqa: E501 - s.loc["Expectancy [%]"] = returns.mean() * 100 - s.loc["SQN"] = np.sqrt(n_trades) * pl.mean() / (pl.std() or np.nan) - s.loc["Kelly Criterion"] = win_rate - (1 - win_rate) / ( - pl[pl > 0].mean() / -pl[pl < 0].mean() - ) - - s.loc["_strategy"] = strategy_instance - s.loc["_equity_curve"] = equity_df - s.loc["_trades"] = trades_df - - s = _Stats(s) - return s - - -class _Stats(pd.Series): - def __repr__(self): - # Prevent expansion due to _equity and _trades dfs - with pd.option_context("max_colwidth", 20): - return super().__repr__() diff --git a/fx_backtest/_util.py b/fx_backtest/_util.py deleted file mode 100644 index 6350e1f..0000000 --- a/fx_backtest/_util.py +++ /dev/null @@ -1,207 +0,0 @@ -import warnings -from numbers import Number -from typing import Dict, List, Optional, Sequence, Union, cast - -import numpy as np -import pandas as pd - - -def try_(lazy_func, default=None, exception=Exception): - try: - return lazy_func() - except exception: - return default - - -def _as_str(value) -> str: - if isinstance(value, (Number, str)): - return str(value) - if isinstance(value, pd.DataFrame): - return "df" - name = str(getattr(value, "name", "") or "") - if name in ("Open", "High", "Low", "Close", "Volume"): - return name[:1] - if callable(value): - name = getattr(value, "__name__", value.__class__.__name__).replace( - "", "λ" - ) - if len(name) > 10: - name = name[:9] + "…" - return name - - -def _as_list(value) -> List: - if isinstance(value, Sequence) and not isinstance(value, str): - return list(value) - return [value] - - -def _data_period(index) -> Union[pd.Timedelta, Number]: - """Return data index period as pd.Timedelta""" - values = pd.Series(index[-100:]) - return values.diff().dropna().median() - - -class _Array(np.ndarray): - """ - ndarray extended to supply .name and other arbitrary properties - in ._opts dict. - """ - - def __new__(cls, array, *, name=None, **kwargs): - obj = np.asarray(array).view(cls) - obj.name = name or array.name - obj._opts = kwargs - return obj - - def __array_finalize__(self, obj): - if obj is not None: - self.name = getattr(obj, "name", "") - self._opts = getattr(obj, "_opts", {}) - - # Make sure properties name and _opts are carried over - # when (un-)pickling. - def __reduce__(self): - value = super().__reduce__() - return value[:2] + (value[2] + (self.__dict__,),) - - def __setstate__(self, state): - self.__dict__.update(state[-1]) - super().__setstate__(state[:-1]) - - def __bool__(self): - try: - return bool(self[-1]) - except IndexError: - return super().__bool__() - - def __float__(self): - try: - return float(self[-1]) - except IndexError: - return super().__float__() - - def to_series(self): - warnings.warn( - "`.to_series()` is deprecated. For pd.Series conversion, use accessor `.s`" - ) - return self.s - - @property - def s(self) -> pd.Series: - values = np.atleast_2d(self) - index = self._opts["index"][: values.shape[1]] - return pd.Series(values[0], index=index, name=self.name) - - @property - def df(self) -> pd.DataFrame: - values = np.atleast_2d(np.asarray(self)) - index = self._opts["index"][: values.shape[1]] - df = pd.DataFrame(values.T, index=index, columns=[self.name] * len(values)) - return df - - -class _Indicator(_Array): - pass - - -class _Data: - """ - A data array accessor. Provides access to OHLCV "columns" - as a standard `pd.DataFrame` would, except it's not a DataFrame - and the returned "series" are _not_ `pd.Series` but `np.ndarray` - for performance reasons. - """ - - def __init__(self, df: pd.DataFrame): - self.__df = df - self.__i = len(df) - self.__pip: Optional[float] = None - self.__cache: Dict[str, _Array] = {} - self.__arrays: Dict[str, _Array] = {} - self._update() - - def __getitem__(self, item): - return self.__get_array(item) - - def __getattr__(self, item): - try: - return self.__get_array(item) - except KeyError: - raise AttributeError(f"Column '{item}' not in data") from None - - def _set_length(self, i): - self.__i = i - self.__cache.clear() - - def _update(self): - index = self.__df.index.copy() - self.__arrays = { - col: _Array(arr, index=index) for col, arr in self.__df.items() - } - # Leave index as Series because pd.Timestamp nicer API to work with - self.__arrays["__index"] = index - - def __repr__(self): - i = min(self.__i, len(self.__df)) - 1 - index = self.__arrays["__index"][i] - items = ", ".join(f"{k}={v}" for k, v in self.__df.iloc[i].items()) - return f"" - - def __len__(self): - return self.__i - - @property - def df(self) -> pd.DataFrame: - return self.__df.iloc[: self.__i] if self.__i < len(self.__df) else self.__df - - @property - def pip(self) -> float: - if self.__pip is None: - self.__pip = float( - 10 - ** -np.median( - [ - len(s.partition(".")[-1]) - for s in self.__arrays["Close"].astype(str) - ] - ) - ) - return self.__pip - - def __get_array(self, key) -> _Array: - arr = self.__cache.get(key) - if arr is None: - arr = self.__cache[key] = cast(_Array, self.__arrays[key][: self.__i]) - return arr - - @property - def Open(self) -> _Array: - return self.__get_array("Open") - - @property - def High(self) -> _Array: - return self.__get_array("High") - - @property - def Low(self) -> _Array: - return self.__get_array("Low") - - @property - def Close(self) -> _Array: - return self.__get_array("Close") - - @property - def Volume(self) -> _Array: - return self.__get_array("Volume") - - @property - def index(self): - return self.__get_array("__index") - - # Make pickling in Backtest.optimize() work with our catch-all __getattr__ - def __getstate__(self): - return self.__dict__ - - def __setstate__(self, state): - self.__dict__ = state diff --git a/fx_backtest/_version.py b/fx_backtest/_version.py deleted file mode 100644 index 2e41576..0000000 --- a/fx_backtest/_version.py +++ /dev/null @@ -1,17 +0,0 @@ -# file generated by setuptools_scm -# don't change, don't track in version control -TYPE_CHECKING = False -if TYPE_CHECKING: - from typing import Tuple, Union - - VERSION_TUPLE = Tuple[Union[int, str], ...] -else: - VERSION_TUPLE = object - -version: str -__version__: str -__version_tuple__: VERSION_TUPLE -version_tuple: VERSION_TUPLE - -__version__ = version = "0.1.dev279+g0ce24d8.d20240114" -__version_tuple__ = version_tuple = (0, 1, "dev279", "g0ce24d8.d20240114") diff --git a/fx_backtest/autoscale_cb.js b/fx_backtest/autoscale_cb.js deleted file mode 100644 index da888ec..0000000 --- a/fx_backtest/autoscale_cb.js +++ /dev/null @@ -1,35 +0,0 @@ -if (!window._bt_scale_range) { - window._bt_scale_range = function (range, min, max, pad) { - "use strict"; - if (min !== Infinity && max !== -Infinity) { - pad = pad ? (max - min) * .03 : 0; - range.start = min - pad; - range.end = max + pad; - } else console.error('backtesting: scale range error:', min, max, range); - }; -} - -clearTimeout(window._bt_autoscale_timeout); - -window._bt_autoscale_timeout = setTimeout(function () { - /** - * @variable cb_obj `fig_ohlc.x_range`. - * @variable source `ColumnDataSource` - * @variable ohlc_range `fig_ohlc.y_range`. - * @variable volume_range `fig_volume.y_range`. - */ - "use strict"; - - let i = Math.max(Math.floor(cb_obj.start), 0), - j = Math.min(Math.ceil(cb_obj.end), source.data['ohlc_high'].length); - - let max = Math.max.apply(null, source.data['ohlc_high'].slice(i, j)), - min = Math.min.apply(null, source.data['ohlc_low'].slice(i, j)); - _bt_scale_range(ohlc_range, min, max, true); - - if (volume_range) { - max = Math.max.apply(null, source.data['Volume'].slice(i, j)); - _bt_scale_range(volume_range, 0, max * 1.03, false); - } - -}, 50); diff --git a/fx_backtest/backtest.py b/fx_backtest/backtest.py new file mode 100644 index 0000000..f660f68 --- /dev/null +++ b/fx_backtest/backtest.py @@ -0,0 +1,46 @@ +from typing import Type +from fx_lib.strategy import FxStrategy + +from fx_backtest.broker import BacktestBroker +from fx_backtest.data import MarketData + +from fx_backtest.strategy import BacktestStrategyWrapper + + +class Backtest: + + def __init__( + self, + data: MarketData, + kstrategy: Type[FxStrategy], + cash: float, + comission: float = 0.0, + margin: float = 1.0, + ): + self.data = data + self.kstrategy = kstrategy + self.cash = cash + self.comission = comission + self.margin = margin + + async def run(self): + + broker = BacktestBroker(self.data) + + strategy = BacktestStrategyWrapper(broker, self.data, self.kstrategy) + strategy.init() + + while self.data.next(): + + broker.next() + await strategy.next() + + + # Increment data points + # Update indicators + # Update trades + # Claculate results/stats + pass + + def plot(self): + pass diff --git a/fx_backtest/backtesting.py b/fx_backtest/backtesting.py deleted file mode 100644 index 40c8c5e..0000000 --- a/fx_backtest/backtesting.py +++ /dev/null @@ -1,1449 +0,0 @@ -""" -Core framework data structures. -Objects from this module can also be imported from the top-level -module directly, e.g. - - from fx_backtest import Backtest, Strategy -""" - -import multiprocessing as mp -import os -import sys -import warnings -from abc import ABCMeta, abstractmethod -from concurrent.futures import ProcessPoolExecutor, as_completed -from functools import lru_cache, partial -from itertools import chain, compress, product, repeat -from math import copysign -from numbers import Number -from typing import Callable, Dict, List, Optional, Sequence, Tuple, Type, Union - -import numpy as np -import pandas as pd -from numpy.random import default_rng -from skopt import forest_minimize -from skopt.callbacks import DeltaXStopper -from skopt.learning import ExtraTreesRegressor -from skopt.space import Categorical, Integer, Real -from skopt.utils import use_named_args -from tqdm.auto import tqdm - -from fx_backtest._exceptions import _OutOfMoneyError -from fx_backtest._interfaces import IBroker -from fx_backtest._models import Order, Position, Trade, _Orders -from fx_backtest._plotting import plot # noqa: I001 -from fx_backtest._stats import compute_stats -from fx_backtest._util import _as_str, _Data, _Indicator, try_ - -_tqdm = partial(tqdm, leave=False) - -__pdoc__ = { - "Strategy.__init__": False, - "Order.__init__": False, - "Position.__init__": False, - "Trade.__init__": False, -} - - -class Strategy(metaclass=ABCMeta): - """ - A trading strategy base class. Extend this class and - override methods - `backtesting.backtesting.Strategy.init` and - `backtesting.backtesting.Strategy.next` to define - your own strategy. - """ - - def __init__(self, broker, data, params): - self._indicators = [] - self._broker: _Broker = broker - self._data: _Data = data - self._params = self._check_params(params) - - def __repr__(self): - return "" - - def __str__(self): - params = ",".join( - f"{i[0]}={i[1]}" - for i in zip(self._params.keys(), map(_as_str, self._params.values())) - ) - if params: - params = "(" + params + ")" - return f"{self.__class__.__name__}{params}" - - def _check_params(self, params): - for k, v in params.items(): - if not hasattr(self, k): - raise AttributeError( - f"Strategy '{self.__class__.__name__}' is missing parameter '{k}'." - "Strategy class should define parameters as class variables before they " - "can be optimized or run with." - ) - setattr(self, k, v) - return params - - def I( # noqa: E743 - self, - func: Callable, - *args, - name=None, - plot=True, - overlay=None, - color=None, - scatter=False, - **kwargs, - ) -> np.ndarray: - """ - Declare an indicator. An indicator is just an array of values, - but one that is revealed gradually in - `backtesting.backtesting.Strategy.next` much like - `backtesting.backtesting.Strategy.data` is. - Returns `np.ndarray` of indicator values. - - `func` is a function that returns the indicator array(s) of - same length as `backtesting.backtesting.Strategy.data`. - - In the plot legend, the indicator is labeled with - function name, unless `name` overrides it. - - If `plot` is `True`, the indicator is plotted on the resulting - `backtesting.backtesting.Backtest.plot`. - - If `overlay` is `True`, the indicator is plotted overlaying the - price candlestick chart (suitable e.g. for moving averages). - If `False`, the indicator is plotted standalone below the - candlestick chart. By default, a heuristic is used which decides - correctly most of the time. - - `color` can be string hex RGB triplet or X11 color name. - By default, the next available color is assigned. - - If `scatter` is `True`, the plotted indicator marker will be a - circle instead of a connected line segment (default). - - Additional `*args` and `**kwargs` are passed to `func` and can - be used for parameters. - - For example, using simple moving average function from TA-Lib: - - def init(): - self.sma = self.I(ta.SMA, self.data.Close, self.n_sma) - """ - if name is None: - params = ",".join(filter(None, map(_as_str, chain(args, kwargs.values())))) - func_name = _as_str(func) - name = f"{func_name}({params})" if params else f"{func_name}" - else: - name = name.format( - *map(_as_str, args), - **dict(zip(kwargs.keys(), map(_as_str, kwargs.values()))), - ) - - try: - value = func(*args, **kwargs) - except Exception as e: - raise RuntimeError(f'Indicator "{name}" error') from e - - if isinstance(value, pd.DataFrame): - value = value.values.T - - if value is not None: - value = try_(lambda: np.asarray(value, order="C"), None) - is_arraylike = bool(value is not None and value.shape) - - # Optionally flip the array if the user returned e.g. `df.values` - if is_arraylike and np.argmax(value.shape) == 0: - value = value.T - - if ( - not is_arraylike - or not 1 <= value.ndim <= 2 - or value.shape[-1] != len(self._data.Close) - ): - raise ValueError( - "Indicators must return (optionally a tuple of) numpy.arrays of same " - f'length as `data` (data shape: {self._data.Close.shape}; indicator "{name}" ' - f'shape: {getattr(value, "shape", "")}, returned value: {value})' - ) - - if plot and overlay is None and np.issubdtype(value.dtype, np.number): - x = value / self._data.Close - # By default, overlay if strong majority of indicator values - # is within 30% of Close - with np.errstate(invalid="ignore"): - overlay = ((x < 1.4) & (x > 0.6)).mean() > 0.6 - - value = _Indicator( - value, - name=name, - plot=plot, - overlay=overlay, - color=color, - scatter=scatter, - # _Indicator.s Series accessor uses this: - index=self.data.index, - ) - self._indicators.append(value) - return value - - @abstractmethod - def init(self): - """ - Initialize the strategy. - Override this method. - Declare indicators (with `backtesting.backtesting.Strategy.I`). - Precompute what needs to be precomputed or can be precomputed - in a vectorized fashion before the strategy starts. - - If you extend composable strategies from `backtesting.lib`, - make sure to call: - - super().init() - """ - - @abstractmethod - def next(self): - """ - Main strategy runtime method, called as each new - `backtesting.backtesting.Strategy.data` - instance (row; full candlestick bar) becomes available. - This is the main method where strategy decisions - upon data precomputed in `backtesting.backtesting.Strategy.init` - take place. - - If you extend composable strategies from `backtesting.lib`, - make sure to call: - - super().next() - """ - - class __FULL_EQUITY(float): # noqa: N801 - def __repr__(self): - return ".9999" - - _FULL_EQUITY = __FULL_EQUITY(1 - sys.float_info.epsilon) - - def buy( - self, - *, - size: float = _FULL_EQUITY, - limit: Optional[float] = None, - stop: Optional[float] = None, - sl: Optional[float] = None, - tp: Optional[float] = None, - tag: object = None, - ): - """ - Place a new long order. For explanation of parameters, see `Order` and its properties. - - See `Position.close()` and `Trade.close()` for closing existing positions. - - See also `Strategy.sell()`. - """ - assert ( - 0 < size < 1 or round(size) == size - ), "size must be a positive fraction of equity, or a positive whole number of units" - return self._broker.new_order(size, limit, stop, sl, tp, tag) - - def sell( - self, - *, - size: float = _FULL_EQUITY, - limit: Optional[float] = None, - stop: Optional[float] = None, - sl: Optional[float] = None, - tp: Optional[float] = None, - tag: object = None, - ): - """ - Place a new short order. For explanation of parameters, see `Order` and its properties. - - See also `Strategy.buy()`. - - .. note:: - If you merely want to close an existing long position, - use `Position.close()` or `Trade.close()`. - """ - assert ( - 0 < size < 1 or round(size) == size - ), "size must be a positive fraction of equity, or a positive whole number of units" - return self._broker.new_order(-size, limit, stop, sl, tp, tag) - - @property - def equity(self) -> float: - """Current account equity (cash plus assets).""" - return self._broker.equity - - @property - def data(self) -> _Data: - """ - Price data, roughly as passed into - `backtesting.backtesting.Backtest.__init__`, - but with two significant exceptions: - - * `data` is _not_ a DataFrame, but a custom structure - that serves customized numpy arrays for reasons of performance - and convenience. Besides OHLCV columns, `.index` and length, - it offers `.pip` property, the smallest price unit of change. - * Within `backtesting.backtesting.Strategy.init`, `data` arrays - are available in full length, as passed into - `backtesting.backtesting.Backtest.__init__` - (for precomputing indicators and such). However, within - `backtesting.backtesting.Strategy.next`, `data` arrays are - only as long as the current iteration, simulating gradual - price point revelation. In each call of - `backtesting.backtesting.Strategy.next` (iteratively called by - `backtesting.backtesting.Backtest` internally), - the last array value (e.g. `data.Close[-1]`) - is always the _most recent_ value. - * If you need data arrays (e.g. `data.Close`) to be indexed - **Pandas series**, you can call their `.s` accessor - (e.g. `data.Close.s`). If you need the whole of data - as a **DataFrame**, use `.df` accessor (i.e. `data.df`). - """ - return self._data - - @property - def position(self) -> Position: - """Instance of `backtesting.backtesting.Position`.""" - return self._broker.position - - @property - def orders(self) -> Tuple[Order, ...]: - """List of orders (see `Order`) waiting for execution.""" - return _Orders(self._broker.orders) - - @property - def trades(self) -> Tuple[Trade, ...]: - """List of active trades (see `Trade`).""" - return tuple(self._broker.trades) - - @property - def closed_trades(self) -> Tuple[Trade, ...]: - """List of settled trades (see `Trade`).""" - return tuple(self._broker.closed_trades) - - -class BacktestStrategy(Strategy): - - def init(self): - super().init() - self._indicator_attrs = { - attr: indicator - for attr, indicator in self.__dict__.items() - if isinstance(indicator, _Indicator) - }.items() - - def next(self): - for attr, indicator in self._indicator_attrs: - # Slice indicator on the last dimension (case of 2d indicator) - setattr(self, attr, indicator[..., : len(self.data)]) - super().next() - - -class _Broker(IBroker): - def __init__( - self, - *, - data, - cash, - commission, - margin, - trade_on_close, - hedging, - exclusive_orders, - index, - ): - assert 0 < cash, f"cash should be >0, is {cash}" - assert -0.1 <= commission < 0.1, ( - "commission should be between -10% " - f"(e.g. market-maker's rebates) and 10% (fees), is {commission}" - ) - assert 0 < margin <= 1, f"margin should be between 0 and 1, is {margin}" - self._data: _Data = data - self._cash = cash - self._commission = commission - self._leverage = 1 / margin - self._trade_on_close = trade_on_close - self._hedging = hedging - self._exclusive_orders = exclusive_orders - - self._equity = np.tile(np.nan, len(index)) - self._orders: list[Order] = [] - self._trades: list[Trade] = [] - self.position = Position(self.trades) - self.closed_trades: list[Trade] = [] - - def __repr__(self): - return f"" - - @property - def trades(self) -> list[Trade]: - return self._trades - - @property - def orders(self) -> list[Order]: - return self._orders - - @property - def data(self) -> _Data: - return self._data - - def new_order( - self, - size: float, - limit: Optional[float] = None, - stop: Optional[float] = None, - sl: Optional[float] = None, - tp: Optional[float] = None, - tag: object = None, - *, - trade: Optional[Trade] = None, - ): - """ - Argument size indicates whether the order is long or short - """ - size = float(size) - stop = stop and float(stop) - limit = limit and float(limit) - sl = sl and float(sl) - tp = tp and float(tp) - - is_long = size > 0 - adjusted_price = self._adjusted_price(size) - - if is_long: - if not (sl or -np.inf) < (limit or stop or adjusted_price) < (tp or np.inf): - raise ValueError( - "Long orders require: " - f"SL ({sl}) < LIMIT ({limit or stop or adjusted_price}) < TP ({tp})" - ) - else: - if not (tp or -np.inf) < (limit or stop or adjusted_price) < (sl or np.inf): - raise ValueError( - "Short orders require: " - f"TP ({tp}) < LIMIT ({limit or stop or adjusted_price}) < SL ({sl})" - ) - - order = Order(size, limit, stop, sl, tp, trade, tag) - # Put the new order in the order queue, - # inserting SL/TP/trade-closing orders in-front - if trade: - self.orders.insert(0, order) - else: - # If exclusive orders (each new order auto-closes previous orders/position), - # cancel all non-contingent orders and close all open trades beforehand - if self._exclusive_orders: - for o in self.orders: - if not o.is_contingent: - o.cancel() - self.orders.remove(o) - for t in self.trades: - t.close() - - self.orders.append(order) - - return order - - @property - def last_price(self) -> float: - """Price at the last (current) close.""" - return self._data.Close[-1] - - def _adjusted_price(self, size=None, price=None) -> float: - """ - Long/short `price`, adjusted for commisions. - In long positions, the adjusted price is a fraction higher, and vice versa. - """ - return (price or self.last_price) * (1 + copysign(self._commission, size)) - - @property - def equity(self) -> float: - return self._cash + sum(trade.pl for trade in self.trades) - - @property - def margin_available(self) -> float: - # From https://github.com/QuantConnect/Lean/pull/3768 - margin_used = sum(trade.value / self._leverage for trade in self.trades) - return max(0, self.equity - margin_used) - - def next(self): - i = self._i = len(self._data) - 1 - self._process_orders() - - # Log account equity for the equity curve - equity = self.equity - self._equity[i] = equity - - # If equity is negative, set all to 0 and stop the simulation - if equity <= 0: - assert self.margin_available <= 0 - for trade in self.trades: - self._close_trade(trade, self._data.Close[-1], i) - self._cash = 0 - self._equity[i:] = 0 - raise _OutOfMoneyError - - def _process_orders(self): - data = self._data - open, high, low = data.Open[-1], data.High[-1], data.Low[-1] - prev_close = data.Close[-2] - reprocess_orders = False - - # Process orders - for order in list(self.orders): - # Related SL/TP order was already removed - if order not in self.orders: - continue - - # Check if stop condition was hit - stop_price = order.stop - if stop_price: - is_stop_hit = ( - (high > stop_price) if order.is_long else (low < stop_price) - ) - if not is_stop_hit: - continue - - # > When the stop price is reached, a stop order becomes a market/limit order. - # https://www.sec.gov/fast-answers/answersstopordhtm.html - order._replace(stop_price=None) - - # Determine purchase price. - # Check if limit order can be filled. - if order.limit: - is_limit_hit = ( - low < order.limit if order.is_long else high > order.limit - ) - # When stop and limit are hit within the same bar, we pessimistically - # assume limit was hit before the stop (i.e. "before it counts") - is_limit_hit_before_stop = is_limit_hit and ( - order.limit < (stop_price or -np.inf) - if order.is_long - else order.limit > (stop_price or np.inf) - ) - if not is_limit_hit or is_limit_hit_before_stop: - continue - - # stop_price, if set, was hit within this bar - price = ( - min(stop_price or open, order.limit) - if order.is_long - else max(stop_price or open, order.limit) - ) - else: - # Market-if-touched / market order - price = prev_close if self._trade_on_close else open - price = ( - max(price, stop_price or -np.inf) - if order.is_long - else min(price, stop_price or np.inf) - ) - - # Determine entry/exit bar index - is_market_order = not order.limit and not stop_price - time_index = ( - (self._i - 1) if is_market_order and self._trade_on_close else self._i - ) - - # If order is a SL/TP order, it should close an existing trade it was contingent upon - if order.parent_trade: - trade = order.parent_trade - _prev_size = trade.size - # If order.size is "greater" than trade.size, this order is a trade.close() - # order and part of the trade was already closed beforehand - size = copysign(min(abs(_prev_size), abs(order.size)), order.size) - # If this trade isn't already closed (e.g. on multiple `trade.close(.5)` calls) - if trade in self.trades: - self._reduce_trade(trade, price, size, time_index) - assert order.size != -_prev_size or trade not in self.trades - if order in (trade._sl_order, trade._tp_order): - assert order.size == -trade.size - assert order not in self.orders # Removed when trade was closed - else: - # It's a trade.close() order, now done - assert abs(_prev_size) >= abs(size) >= 1 - self.orders.remove(order) - continue - - # Else this is a stand-alone trade - - # Adjust price to include commission (or bid-ask spread). - # In long positions, the adjusted price is a fraction higher, and vice versa. - adjusted_price = self._adjusted_price(order.size, price) - - # If order size was specified proportionally, - # precompute true size in units, accounting for margin and spread/commissions - size = order.size - if -1 < size < 1: - size = copysign( - int( - (self.margin_available * self._leverage * abs(size)) - // adjusted_price - ), - size, - ) - # Not enough cash/margin even for a single unit - if not size: - self.orders.remove(order) - continue - assert size == round(size) - need_size = int(size) - - if not self._hedging: - # Fill position by FIFO closing/reducing existing opposite-facing trades. - # Existing trades are closed at unadjusted price, because the adjustment - # was already made when buying. - for trade in list(self.trades): - if trade.is_long == order.is_long: - continue - assert trade.size * order.size < 0 - - # Order size greater than this opposite-directed existing trade, - # so it will be closed completely - if abs(need_size) >= abs(trade.size): - self._close_trade(trade, price, time_index) - need_size += trade.size - else: - # The existing trade is larger than the new order, - # so it will only be closed partially - self._reduce_trade(trade, price, need_size, time_index) - need_size = 0 - - if not need_size: - break - - # If we don't have enough liquidity to cover for the order, cancel it - if abs(need_size) * adjusted_price > self.margin_available * self._leverage: - self.orders.remove(order) - continue - - # Open a new trade - if need_size: - self._open_trade( - adjusted_price, need_size, order.sl, order.tp, time_index, order.tag - ) - - # We need to reprocess the SL/TP orders newly added to the queue. - # This allows e.g. SL hitting in the same bar the order was open. - # See https://github.com/kernc/backtesting.py/issues/119 - if order.sl or order.tp: - if is_market_order: - reprocess_orders = True - elif ( - low <= (order.sl or -np.inf) <= high - or low <= (order.tp or -np.inf) <= high - ): - warnings.warn( - f"({data.index[-1]}) A contingent SL/TP order would execute in the " - "same bar its parent stop/limit order was turned into a trade. " - "Since we can't assert the precise intra-candle " - "price movement, the affected SL/TP order will instead be executed on " - "the next (matching) price/bar, making the result (of this trade) " - "somewhat dubious. " - "See https://github.com/kernc/backtesting.py/issues/119", - UserWarning, - ) - - # Order processed - self.orders.remove(order) - - if reprocess_orders: - self._process_orders() - - def _reduce_trade(self, trade: Trade, price: float, size: float, time_index: int): - assert trade.size * size < 0 - assert abs(trade.size) >= abs(size) - - size_left = trade.size + size - assert size_left * trade.size >= 0 - if not size_left: - close_trade = trade - else: - # Reduce existing trade ... - trade._replace(size=size_left) - if trade._sl_order: - trade._sl_order._replace(size=-trade.size) - if trade._tp_order: - trade._tp_order._replace(size=-trade.size) - - # ... by closing a reduced copy of it - close_trade = trade._copy(size=-size, sl_order=None, tp_order=None) - self.trades.append(close_trade) - - self._close_trade(close_trade, price, time_index) - - def _close_trade(self, trade: Trade, price: float, time_index: int): - self.trades.remove(trade) - if trade._sl_order: - self.orders.remove(trade._sl_order) - if trade._tp_order: - self.orders.remove(trade._tp_order) - - self.closed_trades.append(trade._replace(exit_price=price, exit_bar=time_index)) - self._cash += trade.pl - - def _open_trade( - self, - price: float, - size: int, - sl: Optional[float], - tp: Optional[float], - time_index: int, - tag, - ): - trade = Trade(self, size, price, time_index, tag) - self.trades.append(trade) - # Create SL/TP (bracket) orders. - # Make sure SL order is created first so it gets adversarially processed before TP order - # in case of an ambiguous tie (both hit within a single bar). - # Note, sl/tp orders are inserted at the front of the list, thus order reversed. - if tp: - trade.tp = tp - if sl: - trade.sl = sl - - -class Backtest: - """ - Backtest a particular (parameterized) strategy - on particular data. - - Upon initialization, call method - `backtesting.backtesting.Backtest.run` to run a backtest - instance, or `backtesting.backtesting.Backtest.optimize` to - optimize it. - """ - - def __init__( - self, - data: pd.DataFrame, - strategy: Type[Strategy], - *, - cash: float = 10_000, - commission: float = 0.0, - margin: float = 1.0, - trade_on_close=False, - hedging=False, - exclusive_orders=False, - ): - """ - Initialize a backtest. Requires data and a strategy to test. - - `data` is a `pd.DataFrame` with columns: - `Open`, `High`, `Low`, `Close`, and (optionally) `Volume`. - If any columns are missing, set them to what you have available, - e.g. - - df['Open'] = df['High'] = df['Low'] = df['Close'] - - The passed data frame can contain additional columns that - can be used by the strategy (e.g. sentiment info). - DataFrame index can be either a datetime index (timestamps) - or a monotonic range index (i.e. a sequence of periods). - - `strategy` is a `backtesting.backtesting.Strategy` - _subclass_ (not an instance). - - `cash` is the initial cash to start with. - - `commission` is the commission ratio. E.g. if your broker's commission - is 1% of trade value, set commission to `0.01`. Note, if you wish to - account for bid-ask spread, you can approximate doing so by increasing - the commission, e.g. set it to `0.0002` for commission-less forex - trading where the average spread is roughly 0.2‰ of asking price. - - `margin` is the required margin (ratio) of a leveraged account. - No difference is made between initial and maintenance margins. - To run the backtest using e.g. 50:1 leverge that your broker allows, - set margin to `0.02` (1 / leverage). - - If `trade_on_close` is `True`, market orders will be filled - with respect to the current bar's closing price instead of the - next bar's open. - - If `hedging` is `True`, allow trades in both directions simultaneously. - If `False`, the opposite-facing orders first close existing trades in - a [FIFO] manner. - - If `exclusive_orders` is `True`, each new order auto-closes the previous - trade/position, making at most a single trade (long or short) in effect - at each time. - - [FIFO]: https://www.investopedia.com/terms/n/nfa-compliance-rule-2-43b.asp - """ - - if not (isinstance(strategy, type) and issubclass(strategy, Strategy)): - raise TypeError("`strategy` must be a Strategy sub-type") - if not isinstance(data, pd.DataFrame): - raise TypeError("`data` must be a pandas.DataFrame with columns") - if not isinstance(commission, Number): - raise TypeError( - "`commission` must be a float value, percent of " "entry order price" - ) - - data = data.copy(deep=False) - - # Convert index to datetime index - if ( - not isinstance(data.index, pd.DatetimeIndex) - and not isinstance(data.index, pd.RangeIndex) - and - # Numeric index with most large numbers - ( - data.index.is_numeric() - and (data.index > pd.Timestamp("1975").timestamp()).mean() > 0.8 - ) - ): - try: - data.index = pd.to_datetime(data.index, infer_datetime_format=True) - except ValueError: - pass - - if "Volume" not in data: - data["Volume"] = np.nan - - if len(data) == 0: - raise ValueError("OHLC `data` is empty") - if ( - len(data.columns.intersection(["Open", "High", "Low", "Close", "Volume"])) - != 5 - ): - raise ValueError( - "`data` must be a pandas.DataFrame with columns " - "'Open', 'High', 'Low', 'Close', and (optionally) 'Volume'" - ) - if data[["Open", "High", "Low", "Close"]].isnull().values.any(): - raise ValueError( - "Some OHLC values are missing (NaN). " - "Please strip those lines with `df.dropna()` or " - "fill them in with `df.interpolate()` or whatever." - ) - if np.any(data["Close"] > cash): - warnings.warn( - "Some prices are larger than initial cash value. Note that fractional " - "trading is not supported. If you want to trade Bitcoin, " - "increase initial cash, or trade μBTC or satoshis instead (GH-134).", - stacklevel=2, - ) - if not data.index.is_monotonic_increasing: - warnings.warn( - "Data index is not sorted in ascending order. Sorting.", stacklevel=2 - ) - data = data.sort_index() - if not isinstance(data.index, pd.DatetimeIndex): - warnings.warn( - "Data index is not datetime. Assuming simple periods, " - "but `pd.DateTimeIndex` is advised.", - stacklevel=2, - ) - - self._data: pd.DataFrame = data - self._broker = partial( - _Broker, - cash=cash, - commission=commission, - margin=margin, - trade_on_close=trade_on_close, - hedging=hedging, - exclusive_orders=exclusive_orders, - index=data.index, - ) - self._strategy = strategy - self._results: Optional[pd.Series] = None - - def run(self, **kwargs) -> pd.Series: - """ - Run the backtest. Returns `pd.Series` with results and statistics. - - Keyword arguments are interpreted as strategy parameters. - - >>> Backtest(GOOG, SmaCross).run() - Start 2004-08-19 00:00:00 - End 2013-03-01 00:00:00 - Duration 3116 days 00:00:00 - Exposure Time [%] 93.9944 - Equity Final [$] 51959.9 - Equity Peak [$] 75787.4 - Return [%] 419.599 - Buy & Hold Return [%] 703.458 - Return (Ann.) [%] 21.328 - Volatility (Ann.) [%] 36.5383 - Sharpe Ratio 0.583718 - Sortino Ratio 1.09239 - Calmar Ratio 0.444518 - Max. Drawdown [%] -47.9801 - Avg. Drawdown [%] -5.92585 - Max. Drawdown Duration 584 days 00:00:00 - Avg. Drawdown Duration 41 days 00:00:00 - # Trades 65 - Win Rate [%] 46.1538 - Best Trade [%] 53.596 - Worst Trade [%] -18.3989 - Avg. Trade [%] 2.35371 - Max. Trade Duration 183 days 00:00:00 - Avg. Trade Duration 46 days 00:00:00 - Profit Factor 2.08802 - Expectancy [%] 8.79171 - SQN 0.916893 - Kelly Criterion 0.6134 - _strategy SmaCross - _equity_curve Eq... - _trades Size EntryB... - dtype: object - - .. warning:: - You may obtain different results for different strategy parameters. - E.g. if you use 50- and 200-bar SMA, the trading simulation will - begin on bar 201. The actual length of delay is equal to the lookback - period of the `Strategy.I` indicator which lags the most. - Obviously, this can affect results. - """ - data = _Data(self._data.copy(deep=False)) - broker: _Broker = self._broker(data=data) - strategy: Strategy = self._strategy(broker, data, kwargs) - - strategy.init() - data._update() # Strategy.init might have changed/added to data.df - - # Indicators used in Strategy.next() - indicator_attrs = { - attr: indicator - for attr, indicator in strategy.__dict__.items() - if isinstance(indicator, _Indicator) - }.items() - - # Skip first few candles where indicators are still "warming up" - # +1 to have at least two entries available - start = 1 + max( - ( - np.isnan(indicator.astype(float)).argmin(axis=-1).max() - for _, indicator in indicator_attrs - ), - default=0, - ) - - # Disable "invalid value encountered in ..." warnings. Comparison - # np.nan >= 3 is not invalid; it's False. - with np.errstate(invalid="ignore"): - - for i in range(start, len(self._data)): - # Prepare data and indicators for `next` call - data._set_length(i + 1) - - # Handle orders processing and broker stuff - try: - broker.next() - except _OutOfMoneyError: - break - - # Next tick, a moment before bar close - strategy.next() - else: - # Close any remaining open trades so they produce some stats - for trade in broker.trades: - broker.orders.insert(0, trade.close()) - - # Re-run broker one last time to handle orders placed in the last strategy - # iteration. Use the same OHLC values as in the last broker iteration. - if start < len(self._data): - try_(broker.next, exception=_OutOfMoneyError) - - # Set data back to full length - # for future `indicator._opts['data'].index` calls to work - data._set_length(len(self._data)) - - equity = pd.Series(broker._equity).bfill().fillna(broker._cash).values - self._results = compute_stats( - trades=broker.closed_trades, - equity=equity, - ohlc_data=self._data, - risk_free_rate=0.0, - strategy_instance=strategy, - ) - - return self._results - - def optimize( - self, - *, - maximize: Union[str, Callable[[pd.Series], float]] = "SQN", - method: str = "grid", - max_tries: Optional[Union[int, float]] = None, - constraint: Optional[Callable[[dict], bool]] = None, - return_heatmap: bool = False, - return_optimization: bool = False, - random_state: Optional[int] = None, - **kwargs, - ) -> Union[ - pd.Series, Tuple[pd.Series, pd.Series], Tuple[pd.Series, pd.Series, dict] - ]: - """ - Optimize strategy parameters to an optimal combination. - Returns result `pd.Series` of the best run. - - `maximize` is a string key from the - `backtesting.backtesting.Backtest.run`-returned results series, - or a function that accepts this series object and returns a number; - the higher the better. By default, the method maximizes - Van Tharp's [System Quality Number](https://google.com/search?q=System+Quality+Number). - - `method` is the optimization method. Currently two methods are supported: - - * `"grid"` which does an exhaustive (or randomized) search over the - cartesian product of parameter combinations, and - * `"skopt"` which finds close-to-optimal strategy parameters using - [model-based optimization], making at most `max_tries` evaluations. - - [model-based optimization]: \ - https://scikit-optimize.github.io/stable/auto_examples/bayesian-optimization.html - - `max_tries` is the maximal number of strategy runs to perform. - If `method="grid"`, this results in randomized grid search. - If `max_tries` is a floating value between (0, 1], this sets the - number of runs to approximately that fraction of full grid space. - Alternatively, if integer, it denotes the absolute maximum number - of evaluations. If unspecified (default), grid search is exhaustive, - whereas for `method="skopt"`, `max_tries` is set to 200. - - `constraint` is a function that accepts a dict-like object of - parameters (with values) and returns `True` when the combination - is admissible to test with. By default, any parameters combination - is considered admissible. - - If `return_heatmap` is `True`, besides returning the result - series, an additional `pd.Series` is returned with a multiindex - of all admissible parameter combinations, which can be further - inspected or projected onto 2D to plot a heatmap - (see `backtesting.lib.plot_heatmaps()`). - - If `return_optimization` is True and `method = 'skopt'`, - in addition to result series (and maybe heatmap), return raw - [`scipy.optimize.OptimizeResult`][OptimizeResult] for further - inspection, e.g. with [scikit-optimize]\ - [plotting tools]. - - [OptimizeResult]: \ - https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.OptimizeResult.html - [scikit-optimize]: https://scikit-optimize.github.io - [plotting tools]: https://scikit-optimize.github.io/stable/modules/plots.html - - If you want reproducible optimization results, set `random_state` - to a fixed integer random seed. - - Additional keyword arguments represent strategy arguments with - list-like collections of possible values. For example, the following - code finds and returns the "best" of the 7 admissible (of the - 9 possible) parameter combinations: - - backtest.optimize(sma1=[5, 10, 15], sma2=[10, 20, 40], - constraint=lambda p: p.sma1 < p.sma2) - - .. TODO:: - Improve multiprocessing/parallel execution on Windos with start method 'spawn'. - """ - if not kwargs: - raise ValueError("Need some strategy parameters to optimize") - - maximize_key = None - if isinstance(maximize, str): - maximize_key = str(maximize) - stats = self._results if self._results is not None else self.run() - if maximize not in stats: - raise ValueError( - "`maximize`, if str, must match a key in pd.Series " - "result of backtest.run()" - ) - - def maximize(stats: pd.Series, _key=maximize): - return stats[_key] - - elif not callable(maximize): - raise TypeError( - "`maximize` must be str (a field of backtest.run() result " - "Series) or a function that accepts result Series " - "and returns a number; the higher the better" - ) - assert callable(maximize), maximize - - have_constraint = bool(constraint) - if constraint is None: - - def constraint(_): - return True - - elif not callable(constraint): - raise TypeError( - "`constraint` must be a function that accepts a dict " - "of strategy parameters and returns a bool whether " - "the combination of parameters is admissible or not" - ) - assert callable(constraint), constraint - - if return_optimization and method != "skopt": - raise ValueError("return_optimization=True only valid if method='skopt'") - - def _tuple(x): - return x if isinstance(x, Sequence) and not isinstance(x, str) else (x,) - - for k, v in kwargs.items(): - if len(_tuple(v)) == 0: - raise ValueError( - f"Optimization variable '{k}' is passed no " - f"optimization values: {k}={v}" - ) - - class AttrDict(dict): - def __getattr__(self, item): - return self[item] - - def _grid_size(): - size = int(np.prod([len(_tuple(v)) for v in kwargs.values()])) - if size < 10_000 and have_constraint: - size = sum( - 1 - for p in product( - *(zip(repeat(k), _tuple(v)) for k, v in kwargs.items()) - ) - if constraint(AttrDict(p)) - ) - return size - - def _optimize_grid() -> Union[pd.Series, Tuple[pd.Series, pd.Series]]: - rand = default_rng(random_state).random - grid_frac = ( - 1 - if max_tries is None - else max_tries if 0 < max_tries <= 1 else max_tries / _grid_size() - ) - param_combos = [ - dict(params) # back to dict so it pickles - for params in ( - AttrDict(params) - for params in product( - *(zip(repeat(k), _tuple(v)) for k, v in kwargs.items()) - ) - ) - if constraint(params) and rand() <= grid_frac # type: ignore - ] - if not param_combos: - raise ValueError("No admissible parameter combinations to test") - - if len(param_combos) > 300: - warnings.warn( - f"Searching for best of {len(param_combos)} configurations.", - stacklevel=2, - ) - - heatmap = pd.Series( - np.nan, - name=maximize_key, - index=pd.MultiIndex.from_tuples( - [p.values() for p in param_combos], - names=next(iter(param_combos)).keys(), - ), - ) - - def _batch(seq): - n = np.clip(int(len(seq) // (os.cpu_count() or 1)), 1, 300) - for i in range(0, len(seq), n): - yield seq[i : i + n] - - # Save necessary objects into "global" state; pass into concurrent executor - # (and thus pickle) nothing but two numbers; receive nothing but numbers. - # With start method "fork", children processes will inherit parent address space - # in a copy-on-write manner, achieving better performance/RAM benefit. - backtest_uuid = np.random.random() - param_batches = list(_batch(param_combos)) - Backtest._mp_backtests[backtest_uuid] = (self, param_batches, maximize) # type: ignore - try: - # If multiprocessing start method is 'fork' (i.e. on POSIX), use - # a pool of processes to compute results in parallel. - # Otherwise (i.e. on Windos), sequential computation will be "faster". - if mp.get_start_method(allow_none=False) == "fork": - with ProcessPoolExecutor() as executor: - futures = [ - executor.submit(Backtest._mp_task, backtest_uuid, i) - for i in range(len(param_batches)) - ] - for future in _tqdm( - as_completed(futures), - total=len(futures), - desc="Backtest.optimize", - ): - batch_index, values = future.result() - for value, params in zip( - values, param_batches[batch_index] - ): - heatmap[tuple(params.values())] = value - else: - if os.name == "posix": - warnings.warn( - "For multiprocessing support in `Backtest.optimize()` " - "set multiprocessing start method to 'fork'." - ) - for batch_index in _tqdm(range(len(param_batches))): - _, values = Backtest._mp_task(backtest_uuid, batch_index) - for value, params in zip(values, param_batches[batch_index]): - heatmap[tuple(params.values())] = value - finally: - del Backtest._mp_backtests[backtest_uuid] - - best_params = heatmap.idxmax() - - if pd.isnull(best_params): - # No trade was made in any of the runs. Just make a random - # run so we get some, if empty, results - stats = self.run(**param_combos[0]) - else: - stats = self.run(**dict(zip(heatmap.index.names, str(best_params)))) - - if return_heatmap: - return stats, heatmap - return stats - - def _optimize_skopt() -> Union[ - pd.Series, - Tuple[pd.Series, pd.Series], - Tuple[pd.Series, pd.Series, dict], - ]: - nonlocal max_tries - max_tries = ( - 200 - if max_tries is None - else ( - max(1, int(max_tries * _grid_size())) - if 0 < max_tries <= 1 - else max_tries - ) - ) - - dimensions = [] - for key, values in kwargs.items(): - values = np.asarray(values) - if values.dtype.kind in "mM": # timedelta, datetime64 - # these dtypes are unsupported in skopt, so convert to raw int - # TODO: save dtype and convert back later - values = values.astype(int) - - if values.dtype.kind in "iumM": - dimensions.append( - Integer(low=values.min(), high=values.max(), name=key) - ) - elif values.dtype.kind == "f": - dimensions.append( - Real(low=values.min(), high=values.max(), name=key) - ) - else: - dimensions.append( - Categorical(values.tolist(), name=key, transform="onehot") - ) - - # Avoid recomputing re-evaluations: - # "The objective has been evaluated at this point before." - # https://github.com/scikit-optimize/scikit-optimize/issues/302 - memoized_run = lru_cache()(lambda tup: self.run(**dict(tup))) - - # np.inf/np.nan breaks sklearn, np.finfo(float).max breaks skopt.plots.plot_objective - INVALID = 1e300 - progress = iter( - _tqdm(repeat(None), total=max_tries, desc="Backtest.optimize") - ) - - @use_named_args(dimensions=dimensions) - def objective_function(**params): - next(progress) - # Check constraints - # TODO: Adjust after https://github.com/scikit-optimize/scikit-optimize/pull/971 - if not constraint(AttrDict(params)): - return INVALID - res = memoized_run(tuple(params.items())) - value = -maximize(res) - if np.isnan(value): - return INVALID - return value - - with warnings.catch_warnings(): - warnings.filterwarnings( - "ignore", "The objective has been evaluated at this point before." - ) - - res = forest_minimize( - func=objective_function, - dimensions=dimensions, - n_calls=max_tries, - base_estimator=ExtraTreesRegressor( - n_estimators=20, min_samples_leaf=2 - ), - acq_func="LCB", - kappa=3, - n_initial_points=min(max_tries, 20 + 3 * len(kwargs)), - initial_point_generator="lhs", # 'sobel' requires n_initial_points ~ 2**N - callback=DeltaXStopper(9e-7), - random_state=random_state, - ) - - stats = self.run(**dict(zip(kwargs.keys(), res.x))) - output = [stats] - - if return_heatmap: - heatmap = pd.Series( - dict(zip(map(tuple, res.x_iters), -res.func_vals)), - name=maximize_key, - ) - heatmap.index.names = kwargs.keys() - heatmap = heatmap[heatmap != -INVALID] - heatmap.sort_index(inplace=True) - output.append(heatmap) - - if return_optimization: - valid = res.func_vals != INVALID - res.x_iters = list(compress(res.x_iters, valid)) - res.func_vals = res.func_vals[valid] - output.append(res) - - return stats if len(output) == 1 else tuple(output) # type:ignore - - if method == "grid": - output = _optimize_grid() - elif method == "skopt": - output = _optimize_skopt() # type:ignore - else: - raise ValueError(f"Method should be 'grid' or 'skopt', not {method!r}") - return output - - @staticmethod - def _mp_task(backtest_uuid, batch_index): - bt, param_batches, maximize_func = Backtest._mp_backtests[backtest_uuid] - return batch_index, [ - maximize_func(stats) if stats["# Trades"] else np.nan - for stats in (bt.run(**params) for params in param_batches[batch_index]) - ] - - _mp_backtests: Dict[float, Tuple["Backtest", List, Callable]] = {} - - def plot( - self, - *, - results: Optional[pd.Series] = None, - filename=None, - plot_width=None, - plot_equity=True, - plot_return=False, - plot_pl=True, - plot_volume=True, - plot_drawdown=False, - plot_trades=True, - smooth_equity=False, - relative_equity=True, - superimpose: Union[bool, str] = True, - resample=True, - reverse_indicators=False, - show_legend=True, - open_browser=True, - ): - """ - Plot the progression of the last backtest run. - - If `results` is provided, it should be a particular result - `pd.Series` such as returned by - `backtesting.backtesting.Backtest.run` or - `backtesting.backtesting.Backtest.optimize`, otherwise the last - run's results are used. - - `filename` is the path to save the interactive HTML plot to. - By default, a strategy/parameter-dependent file is created in the - current working directory. - - `plot_width` is the width of the plot in pixels. If None (default), - the plot is made to span 100% of browser width. The height is - currently non-adjustable. - - If `plot_equity` is `True`, the resulting plot will contain - an equity (initial cash plus assets) graph section. This is the same - as `plot_return` plus initial 100%. - - If `plot_return` is `True`, the resulting plot will contain - a cumulative return graph section. This is the same - as `plot_equity` minus initial 100%. - - If `plot_pl` is `True`, the resulting plot will contain - a profit/loss (P/L) indicator section. - - If `plot_volume` is `True`, the resulting plot will contain - a trade volume section. - - If `plot_drawdown` is `True`, the resulting plot will contain - a separate drawdown graph section. - - If `plot_trades` is `True`, the stretches between trade entries - and trade exits are marked by hash-marked tractor beams. - - If `smooth_equity` is `True`, the equity graph will be - interpolated between fixed points at trade closing times, - unaffected by any interim asset volatility. - - If `relative_equity` is `True`, scale and label equity graph axis - with return percent, not absolute cash-equivalent values. - - If `superimpose` is `True`, superimpose larger-timeframe candlesticks - over the original candlestick chart. Default downsampling rule is: - monthly for daily data, daily for hourly data, hourly for minute data, - and minute for (sub-)second data. - `superimpose` can also be a valid [Pandas offset string], - such as `'5T'` or `'5min'`, in which case this frequency will be - used to superimpose. - Note, this only works for data with a datetime index. - - If `resample` is `True`, the OHLC data is resampled in a way that - makes the upper number of candles for Bokeh to plot limited to 10_000. - This may, in situations of overabundant data, - improve plot's interactive performance and avoid browser's - `Javascript Error: Maximum call stack size exceeded` or similar. - Equity & dropdown curves and individual trades data is, - likewise, [reasonably _aggregated_][TRADES_AGG]. - `resample` can also be a [Pandas offset string], - such as `'5T'` or `'5min'`, in which case this frequency will be - used to resample, overriding above numeric limitation. - Note, all this only works for data with a datetime index. - - If `reverse_indicators` is `True`, the indicators below the OHLC chart - are plotted in reverse order of declaration. - - [Pandas offset string]: \ - https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#dateoffset-objects - - [TRADES_AGG]: lib.html#backtesting.lib.TRADES_AGG - - If `show_legend` is `True`, the resulting plot graphs will contain - labeled legends. - - If `open_browser` is `True`, the resulting `filename` will be - opened in the default web browser. - """ - if results is None: - if self._results is None: - raise RuntimeError("First issue `backtest.run()` to obtain results.") - results = self._results - - return plot( - results=results, - df=self._data, - indicators=results._strategy._indicators, - filename=filename, - plot_width=plot_width, - plot_equity=plot_equity, - plot_return=plot_return, - plot_pl=plot_pl, - plot_volume=plot_volume, - plot_drawdown=plot_drawdown, - plot_trades=plot_trades, - smooth_equity=smooth_equity, - relative_equity=relative_equity, - superimpose=superimpose, - resample=resample, - reverse_indicators=reverse_indicators, - show_legend=show_legend, - open_browser=open_browser, - ) diff --git a/fx_backtest/broker.py b/fx_backtest/broker.py new file mode 100644 index 0000000..32e6105 --- /dev/null +++ b/fx_backtest/broker.py @@ -0,0 +1,37 @@ +from typing import Callable +from fx_lib.interfaces.broker import IBroker +from fx_lib.models.order import OrderRequest +from fx_lib.models.instruments import Instrument, Granularity, Candlestick + +from fx_backtest.data import MarketData + +class BacktestBroker(IBroker): + + def __init__(self, data: MarketData): + self.data = data + + @property + def equity(self) -> float: + return 0 + return self._cash + sum(trade.pl for trade in self.trades) + + @property + def margin_available(self) -> float: + return 0 + # From https://github.com/QuantConnect/Lean/pull/3768 + margin_used = sum(trade.value / self._leverage for trade in self.trades) + return max(0, self.equity - margin_used) + + def order(self, order: OrderRequest): + pass + + def subscribe( + self, + instrument: Instrument, + granularity: Granularity, + callback: Callable[[Candlestick], None], + ): + pass + + def next(self): + pass \ No newline at end of file diff --git a/fx_backtest/data.py b/fx_backtest/data.py new file mode 100644 index 0000000..89aadb4 --- /dev/null +++ b/fx_backtest/data.py @@ -0,0 +1,165 @@ +from abc import abstractmethod +from typing import Optional, Tuple + +import numpy as np +import pandas as pd +from fx_lib.events.event import Event +from pandas import Timestamp +from pandas import Timedelta +from fx_backtest.utils import load_csv +from fx_lib.models.instruments import CandleData, Instrument, InstrumentCandles, INDEX, COLUMNS +from fx_lib.models.instruments import Granularity + +class DataSource: + + def __init__(self, instrument: Instrument, granularity: Granularity): + self.instrument = instrument + self.granularity = granularity + +class CsvDataSource(DataSource): + + def __init__(self, path: str, instrument: Instrument, granularity: Granularity): + super().__init__(instrument, granularity) + self.path = path + +class MarketDataLoader: + + @abstractmethod + def load(self) -> dict[Tuple[Instrument, Granularity], pd.DataFrame]: + raise NotImplementedError + +class CsvMarketDataLoader(MarketDataLoader): + + def __init__(self, sources: list[CsvDataSource]): + self.sources = sources + + def load(self) -> dict[Tuple[Instrument, Granularity], pd.DataFrame]: + _sources = dict() + + for source in self.sources: + df = load_csv(source.path, parse_dates=["Timestamp"]) + df = df.set_index("Timestamp") + df.replace('', np.nan, inplace=True) + df.dropna(inplace=True) + _sources[(source.instrument, source.granularity)] = df + + return _sources + +class MarketData: + + def __init__(self, loader: MarketDataLoader): + self._sources = loader.load() + # self._candle_events: dict[Tuple[Instrument, Granularity], CandlestickEvent] = {} + self._init_timeframe() + + @property + def universe(self): + return self._sources + + @property + def index(self): + return self._index + + def _init_timeframe(self): + _start = None + _granularity = None + _end = None + for df in self._sources.values(): + start = df.index[0] + end = df.index[-1] + granularity = df.index[1] - df.index[0] + + if start: + if not _start: + _start = start + elif start < _start: + _start = start + + if end: + if not _end: + _end = end + elif end > _end: + _end = end + + if granularity: + if not _granularity: + _granularity = granularity + elif granularity < _granularity: + _granularity = granularity + + if not _start: + raise RuntimeError("Unable to determine start time for market data.") + + if not _granularity: + raise RuntimeError("Unable to determine smallest granularity for market data.") + + if not _end: + raise RuntimeError("Unable to determine end time for market data.") + + self._index: Timestamp = _start - _granularity + self._granularity: Timedelta = _granularity + self._end_index: Timestamp = _end + + def next(self): + + self._index = self._index + self._granularity + return self._index <= self._end_index + +class BacktestInstrumentCandles(InstrumentCandles): + + def __init__( + self, data: pd.DataFrame, instrument: Instrument, granularity: Granularity + ): + super().__init__(data, max_size=-1) + self._index = self._data.index[0] + self._i_index = 0 + + @property + def index(self): + return self._index + + @index.setter + def index(self, value: pd.Timestamp): + if value in self._data.index: + self._index = value + + @property + def i_index(self): + return self._data.index.get_loc(self._index) + + # def next(self): + # while self._i_index < len(self._data.index): + # yield self._data[self._i_index] + # self._i_index += 1 + + +class BacktestCandleData(CandleData): + + def __init__(self): + self._max_size = -1 + self._data: dict[tuple[Instrument, Granularity], BacktestInstrumentCandles] = {} + self._index = None + + def __new__(cls, *args, **kwargs): + if not hasattr(cls, "instance"): + cls.instance = super().__new__(cls) + # Need to handle case where instantiatied and different max size is provided + return cls.instance + + @property + def index(self): + return self._index + + @index.setter + def index(self, value: pd.Timestamp): + self._index = value + for candles in self._data.values(): + candles.index = self._index + + def populate(self, df: pd.DataFrame, instrument: Instrument, granularity: Granularity): + key = (instrument, granularity) + instrument_candles: BacktestInstrumentCandles = self._data.get( + key, + BacktestInstrumentCandles(df, instrument, granularity), + ) + self._data[key] = instrument_candles \ No newline at end of file diff --git a/fx_backtest/exceptions.py b/fx_backtest/exceptions.py new file mode 100644 index 0000000..e69de29 diff --git a/fx_backtest/lib.py b/fx_backtest/lib.py deleted file mode 100644 index a48fbdb..0000000 --- a/fx_backtest/lib.py +++ /dev/null @@ -1,564 +0,0 @@ -""" -Collection of common building blocks, helper auxiliary functions and -composable strategy classes for reuse. - -Intended for simple missing-link procedures, not reinventing -of better-suited, state-of-the-art, fast libraries, -such as TA-Lib, Tulipy, PyAlgoTrade, NumPy, SciPy ... - -Please raise ideas for additions to this collection on the [issue tracker]. - -[issue tracker]: https://github.com/kernc/backtesting.py -""" - -from collections import OrderedDict -from inspect import currentframe -from itertools import compress -from numbers import Number -from typing import Callable, Generator, Optional, Sequence, Union - -import numpy as np -import pandas as pd - -from ._plotting import plot_heatmaps as _plot_heatmaps -from ._stats import compute_stats as _compute_stats -from ._util import _Array, _as_str -from .backtesting import Strategy - -__pdoc__ = {} - - -OHLCV_AGG = OrderedDict( - ( - ("Open", "first"), - ("High", "max"), - ("Low", "min"), - ("Close", "last"), - ("Volume", "sum"), - ) -) -"""Dictionary of rules for aggregating resampled OHLCV data frames, -e.g. - - df.resample('4H', label='right').agg(OHLCV_AGG).dropna() -""" - -TRADES_AGG = OrderedDict( - ( - ("Size", "sum"), - ("EntryBar", "first"), - ("ExitBar", "last"), - ("EntryPrice", "mean"), - ("ExitPrice", "mean"), - ("PnL", "sum"), - ("ReturnPct", "mean"), - ("EntryTime", "first"), - ("ExitTime", "last"), - ("TakeProfit", "mean"), - ("StopLoss", "mean"), - ("Duration", "sum"), - ) -) -"""Dictionary of rules for aggregating resampled trades data, -e.g. - - stats['_trades'].resample('1D', on='ExitTime', - label='right').agg(TRADES_AGG) -""" - -_EQUITY_AGG = { - "Equity": "last", - "DrawdownPct": "max", - "DrawdownDuration": "max", -} - - -def barssince(condition: Sequence[bool], default=np.inf) -> int: - """ - Return the number of bars since `condition` sequence was last `True`, - or if never, return `default`. - - >>> barssince(self.data.Close > self.data.Open) - 3 - """ - return next(compress(range(len(condition)), reversed(condition)), default) - - -def cross(series1: Sequence, series2: Sequence) -> bool: - """ - Return `True` if `series1` and `series2` just crossed - (above or below) each other. - - >>> cross(self.data.Close, self.sma) - True - - """ - return crossover(series1, series2) or crossover(series2, series1) - - -def crossover(series1: Sequence, series2: Sequence) -> bool: - """ - Return `True` if `series1` just crossed over (above) - `series2`. - - >>> crossover(self.data.Close, self.sma) - True - """ - series1 = ( - series1.values # type:ignore - if isinstance(series1, pd.Series) - else (series1, series1) if isinstance(series1, Number) else series1 - ) - series2 = ( - series2.values # type:ignore - if isinstance(series2, pd.Series) - else (series2, series2) if isinstance(series2, Number) else series2 - ) - try: - return series1[-2] < series2[-2] and series1[-1] > series2[-1] - except IndexError: - return False - - -def plot_heatmaps( - heatmap: pd.Series, - agg: Union[str, Callable] = "max", - *, - ncols: int = 3, - plot_width: int = 1200, - filename: str = "", - open_browser: bool = True, -): - """ - Plots a grid of heatmaps, one for every pair of parameters in `heatmap`. - - `heatmap` is a Series as returned by - `backtesting.backtesting.Backtest.optimize` when its parameter - `return_heatmap=True`. - - When projecting the n-dimensional heatmap onto 2D, the values are - aggregated by 'max' function by default. This can be tweaked - with `agg` parameter, which accepts any argument pandas knows - how to aggregate by. - - .. todo:: - Lay heatmaps out lower-triangular instead of in a simple grid. - Like [`skopt.plots.plot_objective()`][plot_objective] does. - - [plot_objective]: \ - https://scikit-optimize.github.io/stable/modules/plots.html#plot-objective - """ - return _plot_heatmaps(heatmap, agg, ncols, filename, plot_width, open_browser) - - -def quantile(series: Sequence, quantile: Union[None, float] = None): - """ - If `quantile` is `None`, return the quantile _rank_ of the last - value of `series` wrt former series values. - - If `quantile` is a value between 0 and 1, return the _value_ of - `series` at this quantile. If used to working with percentiles, just - divide your percentile amount with 100 to obtain quantiles. - - >>> quantile(self.data.Close[-20:], .1) - 162.130 - >>> quantile(self.data.Close) - 0.13 - """ - if quantile is None: - try: - last, series = series[-1], series[:-1] - return np.mean(series < last) - except IndexError: - return np.nan - assert 0 <= quantile <= 1, "quantile must be within [0, 1]" - return np.nanpercentile(series, quantile * 100) - - -def compute_stats( - *, - stats: pd.Series, - data: pd.DataFrame, - trades: Optional[pd.DataFrame] = None, - risk_free_rate: float = 0.0, -) -> pd.Series: - """ - (Re-)compute strategy performance metrics. - - `stats` is the statistics series as returned by `backtesting.backtesting.Backtest.run()`. - `data` is OHLC data as passed to the `backtesting.backtesting.Backtest` - the `stats` were obtained in. - `trades` can be a dataframe subset of `stats._trades` (e.g. only long trades). - You can also tune `risk_free_rate`, used in calculation of Sharpe and Sortino ratios. - - >>> stats = Backtest(GOOG, MyStrategy).run() - >>> only_long_trades = stats._trades[stats._trades.Size > 0] - >>> long_stats = compute_stats(stats=stats, trades=only_long_trades, - ... data=GOOG, risk_free_rate=.02) - """ - equity = stats._equity_curve.Equity - if trades is None: - trades = stats._trades - else: - # XXX: Is this buggy? - equity = equity.copy() - equity[:] = stats._equity_curve.Equity.iloc[0] - for t in trades.itertuples(index=False): - equity.iloc[t.EntryBar :] += t.PnL # type:ignore - return _compute_stats( - trades=trades, - equity=equity, - ohlc_data=data, - risk_free_rate=risk_free_rate, - strategy_instance=stats._strategy, - ) - - -def resample_apply( - rule: str, - func: Optional[Callable[..., Sequence]], - series: Union[pd.Series, pd.DataFrame, _Array], - *args, - group_by: Optional[Union[str, dict]] = None, - **kwargs, -): - """ - Apply `func` (such as an indicator) to `series`, resampled to - a time frame specified by `rule`. When called from inside - `backtesting.backtesting.Strategy.init`, - the result (returned) series will be automatically wrapped in - `backtesting.backtesting.Strategy.I` - wrapper method. - - `rule` is a valid [Pandas offset string] indicating - a time frame to resample `series` to. - - [Pandas offset string]: \ -http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases - - `func` is the indicator function to apply on the resampled series. - - `series` is a data series (or array), such as any of the - `backtesting.backtesting.Strategy.data` series. Due to pandas - resampling limitations, this only works when input series - has a datetime index. - - `agg` is the aggregation function to use on resampled groups of data. - Valid values are anything accepted by `pandas/resample/.agg()`. - Default value for dataframe input is `OHLCV_AGG` dictionary. - Default value for series input is the appropriate entry from `OHLCV_AGG` - if series has a matching name, or otherwise the value `"last"`, - which is suitable for closing prices, - but you might prefer another (e.g. `"max"` for peaks, or similar). - - Finally, any `*args` and `**kwargs` that are not already eaten by - implicit `backtesting.backtesting.Strategy.I` call - are passed to `func`. - - For example, if we have a typical moving average function - `SMA(values, lookback_period)`, _hourly_ data source, and need to - apply the moving average MA(10) on a _daily_ time frame, - but don't want to plot the resulting indicator, we can do: - - class System(Strategy): - def init(self): - self.sma = resample_apply( - 'D', SMA, self.data.Close, 10, plot=False) - - The above short snippet is roughly equivalent to: - - class System(Strategy): - def init(self): - # Strategy exposes `self.data` as raw NumPy arrays. - # Let's convert closing prices back to pandas Series. - close = self.data.Close.s - - # Resample to daily resolution. Aggregate groups - # using their last value (i.e. closing price at the end - # of the day). Notice `label='right'`. If it were set to - # 'left' (default), the strategy would exhibit - # look-ahead bias. - daily = close.resample('D', label='right').agg('last') - - # We apply SMA(10) to daily close prices, - # then reindex it back to original hourly index, - # forward-filling the missing values in each day. - # We make a separate function that returns the final - # indicator array. - def SMA(series, n): - from backtesting.test import SMA - return SMA(series, n).reindex(close.index).ffill() - - # The result equivalent to the short example above: - self.sma = self.I(SMA, daily, 10, plot=False) - - """ - if func is None: - - def func(x, *_, **__): - return x - - if not isinstance(series, (pd.Series, pd.DataFrame)): - assert isinstance(series, _Array), ( - "resample_apply() takes either a `pd.Series`, `pd.DataFrame`, " - "or a `Strategy.data.*` array" - ) - series = series.s - - if group_by is None: - group_by = OHLCV_AGG.get(getattr(series, "name", ""), "last") - if isinstance(series, pd.DataFrame): - group_by = { - column: OHLCV_AGG.get(column, "last") for column in series.columns - } - - resampled = ( - series.resample(rule, label="right").agg(group_by).dropna() # type:ignore - ) # type:ignore - resampled.name = _as_str(series) + "[" + rule + "]" - - # Check first few stack frames if we are being called from - # inside Strategy.init, and if so, extract Strategy.I wrapper. - frame, level = currentframe(), 0 - while frame and level <= 3: - frame = frame.f_back - level += 1 - if isinstance(frame.f_locals.get("self"), Strategy): # type: ignore - strategy_I = frame.f_locals["self"].I # type: ignore - break - else: - - def strategy_I(func, *args, **kwargs): # noqa: F811 - return func(*args, **kwargs) - - def wrap_func(resampled, *args, **kwargs): - result = func(resampled, *args, **kwargs) - if not isinstance(result, pd.DataFrame) and not isinstance(result, pd.Series): - result = np.asarray(result) - if result.ndim == 1: - result = pd.Series(result, name=resampled.name) - elif result.ndim == 2: - result = pd.DataFrame(result.T) - # Resample back to data index - if not isinstance(result.index, pd.DatetimeIndex): - result.index = resampled.index - result = result.reindex( - index=series.index.union(resampled.index), method="ffill" - ).reindex(series.index) - return result - - wrap_func.__name__ = func.__name__ - - array = strategy_I(wrap_func, resampled, *args, **kwargs) - return array - - -def random_ohlc_data( - example_data: pd.DataFrame, *, frac=1.0, random_state: Optional[int] = None -) -> Generator[pd.DataFrame, None, None]: - """ - OHLC data generator. The generated OHLC data has basic - [descriptive statistics](https://en.wikipedia.org/wiki/Descriptive_statistics) - similar to the provided `example_data`. - - `frac` is a fraction of data to sample (with replacement). Values greater - than 1 result in oversampling. - - Such random data can be effectively used for stress testing trading - strategy robustness, Monte Carlo simulations, significance testing, etc. - - >>> from backtesting.test import EURUSD - >>> ohlc_generator = random_ohlc_data(EURUSD) - >>> next(ohlc_generator) # returns new random data - ... - >>> next(ohlc_generator) # returns new random data - ... - """ - - def shuffle(x): - return x.sample(frac=frac, replace=frac > 1, random_state=random_state) - - if len(example_data.columns.intersection(["Open", "High", "Low", "Close"])) != 4: - raise ValueError( - "`data` must be a pandas.DataFrame with columns " - "'Open', 'High', 'Low', 'Close'" - ) - while True: - df = shuffle(example_data) - df.index = example_data.index - padding = df.Close - df.Open.shift(-1) - gaps = shuffle(example_data.Open.shift(-1) - example_data.Close) - deltas = (padding + gaps).shift(1).fillna(0).cumsum() - for key in ("Open", "High", "Low", "Close"): - df[key] += deltas - yield df - - -class SignalStrategy(Strategy): - """ - A simple helper strategy that operates on position entry/exit signals. - This makes the backtest of the strategy simulate a [vectorized backtest]. - See [tutorials] for usage examples. - - [vectorized backtest]: https://www.google.com/search?q=vectorized+backtest - [tutorials]: index.html#tutorials - - To use this helper strategy, subclass it, override its - `backtesting.backtesting.Strategy.init` method, - and set the signal vector by calling - `backtesting.lib.SignalStrategy.set_signal` method from within it. - - class ExampleStrategy(SignalStrategy): - def init(self): - super().init() - self.set_signal(sma1 > sma2, sma1 < sma2) - - Remember to call `super().init()` and `super().next()` in your - overridden methods. - """ - - __entry_signal = (0,) - __exit_signal = (False,) - - def set_signal( - self, - entry_size: Sequence[float], - exit_portion: Optional[Sequence[float]] = None, - *, - plot: bool = True, - ): - """ - Set entry/exit signal vectors (arrays). - - A long entry signal is considered present wherever `entry_size` - is greater than zero, and a short signal wherever `entry_size` - is less than zero, following `backtesting.backtesting.Order.size` semantics. - - If `exit_portion` is provided, a nonzero value closes portion the position - (see `backtesting.backtesting.Trade.close()`) in the respective direction - (positive values close long trades, negative short). - - If `plot` is `True`, the signal entry/exit indicators are plotted when - `backtesting.backtesting.Backtest.plot` is called. - """ - self.__entry_signal = self.I( # type: ignore - lambda: pd.Series(entry_size, dtype=float).replace(0, np.nan), - name="entry size", - plot=plot, - overlay=False, - scatter=True, - color="black", - ) - - if exit_portion is not None: - self.__exit_signal = self.I( # type: ignore - lambda: pd.Series(exit_portion, dtype=float).replace(0, np.nan), - name="exit portion", - plot=plot, - overlay=False, - scatter=True, - color="black", - ) - - def next(self): - super().next() - - exit_portion = self.__exit_signal[-1] - if exit_portion > 0: - for trade in self.trades: - if trade.is_long: - trade.close(exit_portion) - elif exit_portion < 0: - for trade in self.trades: - if trade.is_short: - trade.close(-exit_portion) - - entry_size = self.__entry_signal[-1] - if entry_size > 0: - self.buy(size=entry_size) - elif entry_size < 0: - self.sell(size=-entry_size) - - -class TrailingStrategy(Strategy): - """ - A strategy with automatic trailing stop-loss, trailing the current - price at distance of some multiple of average true range (ATR). Call - `TrailingStrategy.set_trailing_sl()` to set said multiple - (`6` by default). See [tutorials] for usage examples. - - [tutorials]: index.html#tutorials - - Remember to call `super().init()` and `super().next()` in your - overridden methods. - """ - - __n_atr = 6.0 - __atr = None - - def init(self): - super().init() - self.set_atr_periods() - - def set_atr_periods(self, periods: int = 100): - """ - Set the lookback period for computing ATR. The default value - of 100 ensures a _stable_ ATR. - """ - hi, lo, c_prev = ( - self.data.High, - self.data.Low, - pd.Series(self.data.Close).shift(1), # type:ignore - ) - tr = np.max( - [hi - lo, (c_prev - hi).abs(), (c_prev - lo).abs()], axis=0 # type:ignore - ) - atr = pd.Series(tr).rolling(periods).mean().bfill().values - self.__atr = atr - - def set_trailing_sl(self, n_atr: float = 6): - """ - Sets the future trailing stop-loss as some multiple (`n_atr`) - average true bar ranges away from the current price. - """ - self.__n_atr = n_atr - - def next(self): - super().next() - # Can't use index=-1 because self.__atr is not an Indicator type - index = len(self.data) - 1 - for trade in self.trades: - if trade.is_long: - trade.sl = max( - trade.sl or -np.inf, - self.data.Close[index] - self.__atr[index] * self.__n_atr, - ) - else: - trade.sl = min( - trade.sl or np.inf, - self.data.Close[index] + self.__atr[index] * self.__n_atr, - ) - - -# Prevent pdoc3 documenting __init__ signature of Strategy subclasses -for cls in list(globals().values()): - if isinstance(cls, type) and issubclass(cls, Strategy): - __pdoc__[f"{cls.__name__}.__init__"] = False - - -# NOTE: Don't put anything below this __all__ list - -__all__ = [ - getattr(v, "__name__", k) - for k, v in globals().items() # export - if ( - ( - callable(v) - and v.__module__ == __name__ # callables from this module - or k.isupper() - ) # or CONSTANTS - and not getattr(v, "__name__", k).startswith("_") - ) -] # neither marked internal - -# NOTE: Don't put anything below here. See above. diff --git a/fx_backtest/main.py b/fx_backtest/main.py index 022c39c..46d91a0 100644 --- a/fx_backtest/main.py +++ b/fx_backtest/main.py @@ -1,20 +1,17 @@ import pandas as pd from fx_strategy.strategy import SlopeMomentum +from fx_lib.models.instruments import Instrument, Granularity -from fx_backtest.backtesting import Backtest, BacktestStrategy - -with open("/home/kyle/Tick_Data/ohlc/2024/February/EURUSD-2024-02_5Min.csv") as fh: - data = pd.read_csv(fh, parse_dates=["Timestamp"]) - data.rename( - columns={"open": "Open", "high": "High", "low": "Low", "close": "Close"}, - inplace=True, - ) - data = data.dropna() +from fx_backtest.backtest import Backtest +from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData +test_universe = MarketData(CsvMarketDataLoader([ + CsvDataSource("/home/kyle/Tick_Data/ohlc/2024/February/EURUSD-2024-02_5Min.csv", Instrument.EURUSD, Granularity.M5) +])) bt = Backtest( - data, BacktestStrategy, commission=0.000, exclusive_orders=False, margin=0.02 + test_universe, SlopeMomentum, 10000, margin=0.02 ) -stats = bt.run(_klass=SlopeMomentum) +stats = bt.run() bt.plot() print(stats) diff --git a/fx_backtest/stats.py b/fx_backtest/stats.py new file mode 100644 index 0000000..de7db21 --- /dev/null +++ b/fx_backtest/stats.py @@ -0,0 +1,186 @@ +from typing import Any +from fx_lib.models.trade import Trade +from fx_lib.strategy import FxStrategy +import numpy as np +import pandas as pd + +from fx_backtest.data import MarketData + +class Stats: + + def __init__( + self, + trades: list[Trade], + equity: np.ndarray, + market_data: MarketData, + strategy: FxStrategy + ): + self._trades = trades + self._equity = equity + self._market_data = market_data + self._strategy = strategy + self._trades_df = pd.DataFrame({ + 'Size': [t.size for t in trades], + 'EntryBar': [t.entry_bar for t in trades], + 'ExitBar': [t.exit_bar for t in trades], + 'EntryPrice': [t.entry_price for t in trades], + 'ExitPrice': [t.exit_price for t in trades], + 'PnL': [t.pl for t in trades], + 'ReturnPct': [t.pl_pct for t in trades], + 'EntryTime': [t.entry_time for t in trades], + 'ExitTime': [t.exit_time for t in trades], + 'Tag': [t.tag for t in trades], + 'TakeProfit': [t.tp for t in trades], + 'StopLoss': [t.sl for t in trades] + }) + self._trades_df['Duration'] = self._trades_df['ExitTime'] - self._trades_df['EntryTime'] + + @property + def drawdown(self) -> np.ndarray[np.floating[Any]]: + if not self._drawdown: + self._drawdown = 1 - self._equity / np.maximum.accumulate(self._equity) + return self._drawdown + + @property + def drawdown_duration(self): + iloc = np.unique(np.r_[(self.drawdown == 0).values.nonzero()[0], len(self.drawdown) - 1]) + iloc = pd.Series(iloc, index=self.drawdown.index[iloc]) + df = iloc.to_frame('iloc').assign(prev=iloc.shift()) + df = df[df['iloc'] > df['prev'] + 1].astype(int) + + # If no drawdown since no trade, avoid below for pandas sake and return nan series + if not len(df): + return (self.drawdown.replace(0, np.nan),) * 2 + + # df = df.reindex(self.drawdown.index) + return df['iloc'].map(self.drawdown.index.__getitem__) - df['prev'].map(self.drawdown.index.__getitem__) + + @property + def drawdown_peaks(self): + iloc = np.unique(np.r_[(self.drawdown == 0).values.nonzero()[0], len(self.drawdown) - 1]) + iloc = pd.Series(iloc, index=self.drawdown.index[iloc]) + df = iloc.to_frame('iloc').assign(prev=iloc.shift()) + df = df[df['iloc'] > df['prev'] + 1].astype(int) + + # If no drawdown since no trade, avoid below for pandas sake and return nan series + if not len(df): + return (self.drawdown.replace(0, np.nan),) * 2 + + # df = df.reindex(self.drawdown.index) + return df.apply(lambda row: self.drawdown.iloc[row['prev']:row['iloc'] + 1].max(), axis=1) + + @property + def profit_n_loss(self): + return self._trades_df['PnL'] + + @property + def returns(self): + return self._trades_df['ReturnPct'] + + @property + def durations(self): + return self._trades_df['Duration'] + + @property + def positions(self): + pass + + @property + def exposure_time(self): + pass + + @property + def equity_final(self): + pass + + @property + def equity_peak(self): + pass + + @property + def return_pct(self): + pass + + @property + def buy_and_hold_return(self): + pass + + @property + def annualized_return(self): + pass + + @property + def annualized_volatility(self): + pass + + @property + def sharpe_ratio(self): + pass + + @property + def sortino_ratio(self): + pass + + @property + def calmar_ratio(self): + pass + + @property + def max_drawndown(self): + pass + + @property + def avg_drawdown(self): + pass + + @property + def max_drawdown_duration(self): + pass + + @property + def avg_drawdown_duration(self): + pass + + @property + def number_of_trades(self): + pass + + @property + def win_rate(self): + pass + + @property + def best_trade_return(self): + pass + + @property + def worst_trade_return(self): + pass + + @property + def avg_trade_return(self): + pass + + @property + def max_trade_duration(self): + pass + + @property + def avg_trade_duration(self): + pass + + @property + def profit_factor(self): + pass + + @property + def expectancy(self): + pass + + @property + def SQN(self): + pass + + @property + def kelly_criterion(self): + pass \ No newline at end of file diff --git a/fx_backtest/strategy.py b/fx_backtest/strategy.py new file mode 100644 index 0000000..a87f7a1 --- /dev/null +++ b/fx_backtest/strategy.py @@ -0,0 +1,47 @@ +import asyncio +from typing import Type +from fx_lib.interfaces.broker import IBroker +from fx_lib.strategy import FxStrategy +from fx_lib.models.indicator import Indicator + +from fx_backtest.data import BacktestCandleData, BacktestInstrumentCandles, MarketData + +class BacktestStrategyWrapper: + + def __init__(self, broker: IBroker, data: MarketData, kstrategy: Type[FxStrategy]): + self._data = data + self._data_context = BacktestCandleData() + self._strategy = kstrategy(broker, self._data_context) + self._current_index = None + + def init(self): + for key, df in self._data.universe.items(): + self._data_context.populate(df, key[0], key[1]) + + self._strategy.init() + + self._indicators = {attr: indicator + for attr, indicator in self._strategy.__dict__.items() + if isinstance(indicator, Indicator)}.items() + + self._indicator_values = {attr: indicator._values for attr, indicator in self._indicators } + + self._indicator_i_index = {attr: None for attr, indicator in self._indicators} + + async def next(self) -> None: + + self._data_context.index = self._data.index + indicator_updated = False + + # Incrememnt indicators + for attr, indicator in self._indicators: + if isinstance(indicator._data, BacktestInstrumentCandles): + previous_i_index = self._indicator_i_index.get(attr) + if previous_i_index != indicator._data.i_index: + indicator._values = self._indicator_values[attr][:indicator._data.i_index+1] + self._indicator_i_index[attr] = indicator._data.i_index + indicator_updated = True + + if indicator_updated: + # Call _next directly so we don't wait for pending updates + self._strategy._next() \ No newline at end of file diff --git a/fx_backtest/utils.py b/fx_backtest/utils.py new file mode 100644 index 0000000..2413fe9 --- /dev/null +++ b/fx_backtest/utils.py @@ -0,0 +1,9 @@ +from typing import Optional +import pandas as pd + + +def load_csv(path, parse_dates: list[str] = []) -> pd.DataFrame: + with open(path) as fh: + data = pd.read_csv(fh, parse_dates=parse_dates) + + return data \ No newline at end of file diff --git a/makefiles/local.mk b/makefiles/local.mk index ccfb797..ba00ce9 100644 --- a/makefiles/local.mk +++ b/makefiles/local.mk @@ -2,7 +2,7 @@ bandit-local: ##@lint Run bandit bandit-local: files ?= ${SERVICE} bandit-local: - ${POETRY} run bandit -r ${files} -c pyproject.toml + ${POETRY} run bandit -r ${files} .PHONY: black-local black-local: ##@lint Run black diff --git a/poetry.lock b/poetry.lock index 2b48777..4552113 100644 --- a/poetry.lock +++ b/poetry.lock @@ -22,13 +22,13 @@ test = ["matplotlib", "scikit-learn", "scikit-optimize", "seaborn"] [[package]] name = "bandit" -version = "1.7.8" +version = "1.7.9" description = "Security oriented static analyser for python code." optional = false python-versions = ">=3.8" files = [ - {file = "bandit-1.7.8-py3-none-any.whl", hash = "sha256:509f7af645bc0cd8fd4587abc1a038fc795636671ee8204d502b933aee44f381"}, - {file = "bandit-1.7.8.tar.gz", hash = "sha256:36de50f720856ab24a24dbaa5fee2c66050ed97c1477e0a1159deab1775eab6b"}, + {file = "bandit-1.7.9-py3-none-any.whl", hash = "sha256:52077cb339000f337fb25f7e045995c4ad01511e716e5daac37014b9752de8ec"}, + {file = "bandit-1.7.9.tar.gz", hash = "sha256:7c395a436743018f7be0a4cbb0a4ea9b902b6d87264ddecf8cfdc73b4f78ff61"}, ] [package.dependencies] @@ -46,33 +46,33 @@ yaml = ["PyYAML"] [[package]] name = "black" -version = "24.4.2" +version = "24.8.0" description = "The uncompromising code formatter." optional = false 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01:00:00,1.08506,1.08555,1.08366,1.08405,1104 -2017-04-24 02:00:00,1.08403,1.08405,1.08209,1.0838,1030 -2017-04-24 03:00:00,1.08382,1.08513,1.08346,1.08442,623 -2017-04-24 04:00:00,1.0844,1.08605,1.08418,1.08587,650 -2017-04-24 05:00:00,1.08584,1.08773,1.08456,1.0868,1135 -2017-04-24 06:00:00,1.08682,1.08695,1.08319,1.08432,2899 -2017-04-24 07:00:00,1.0843,1.08664,1.0833,1.08555,2608 -2017-04-24 08:00:00,1.08558,1.08752,1.08492,1.08584,1838 -2017-04-24 09:00:00,1.08587,1.08773,1.0855,1.08708,1334 -2017-04-24 10:00:00,1.08706,1.08724,1.08516,1.08584,1087 -2017-04-24 11:00:00,1.08586,1.08631,1.08416,1.08422,1135 -2017-04-24 12:00:00,1.0842,1.08652,1.0842,1.08575,1487 -2017-04-24 13:00:00,1.08573,1.08736,1.0857,1.08656,1653 -2017-04-24 14:00:00,1.08653,1.08705,1.08553,1.08602,1282 -2017-04-24 15:00:00,1.08604,1.08682,1.08474,1.0848,1312 -2017-04-24 16:00:00,1.08478,1.0854,1.08354,1.08416,950 -2017-04-24 17:00:00,1.08414,1.08498,1.08412,1.08483,683 -2017-04-24 18:00:00,1.0848,1.08591,1.08462,1.08582,703 -2017-04-24 19:00:00,1.08585,1.08697,1.08553,1.0868,497 -2017-04-24 20:00:00,1.08678,1.08699,1.08648,1.08674,253 -2017-04-24 21:00:00,1.08684,1.08689,1.08636,1.08649,235 -2017-04-24 22:00:00,1.08651,1.08692,1.0865,1.08678,204 -2017-04-24 23:00:00,1.08675,1.08676,1.08632,1.0865,164 -2017-04-25 00:00:00,1.08652,1.08706,1.08624,1.08624,400 -2017-04-25 01:00:00,1.08626,1.0865,1.08542,1.08552,382 -2017-04-25 02:00:00,1.08554,1.08619,1.08515,1.08619,379 -2017-04-25 03:00:00,1.08617,1.08636,1.08601,1.08602,186 -2017-04-25 04:00:00,1.08599,1.08658,1.08572,1.08632,200 -2017-04-25 05:00:00,1.08634,1.0872,1.08634,1.08652,381 -2017-04-25 06:00:00,1.08655,1.08882,1.08633,1.08827,1302 -2017-04-25 07:00:00,1.08825,1.08933,1.0875,1.08856,1857 -2017-04-25 08:00:00,1.08853,1.08942,1.08838,1.08924,791 -2017-04-25 09:00:00,1.08922,1.08988,1.08822,1.0883,807 -2017-04-25 10:00:00,1.08832,1.08846,1.0871,1.08789,793 -2017-04-25 11:00:00,1.08786,1.08881,1.08768,1.08881,679 -2017-04-25 12:00:00,1.08879,1.08962,1.08866,1.0889,1005 -2017-04-25 13:00:00,1.08888,1.09016,1.08797,1.09,1340 -2017-04-25 14:00:00,1.08997,1.09328,1.08902,1.09281,3642 -2017-04-25 15:00:00,1.09284,1.09412,1.09198,1.09409,1651 -2017-04-25 16:00:00,1.09407,1.09499,1.09386,1.09492,966 -2017-04-25 17:00:00,1.09494,1.095,1.09334,1.09354,669 -2017-04-25 18:00:00,1.09356,1.09411,1.09308,1.0938,575 -2017-04-25 19:00:00,1.09377,1.0938,1.09258,1.09375,476 -2017-04-25 20:00:00,1.09373,1.09373,1.09258,1.09265,450 -2017-04-25 21:00:00,1.093,1.0932,1.0925,1.09282,286 -2017-04-25 22:00:00,1.09279,1.09312,1.09274,1.09298,501 -2017-04-25 23:00:00,1.09296,1.09306,1.09237,1.09278,251 -2017-04-26 00:00:00,1.0928,1.0945,1.09274,1.09379,661 -2017-04-26 01:00:00,1.09376,1.09406,1.09308,1.09374,519 -2017-04-26 02:00:00,1.09377,1.09406,1.09334,1.0939,218 -2017-04-26 03:00:00,1.09393,1.094,1.09356,1.09366,144 -2017-04-26 04:00:00,1.09364,1.09476,1.09364,1.09404,329 -2017-04-26 05:00:00,1.09407,1.09498,1.09407,1.09461,413 -2017-04-26 06:00:00,1.09458,1.09508,1.09221,1.0925,1167 -2017-04-26 07:00:00,1.09252,1.09326,1.0905,1.09137,1635 -2017-04-26 08:00:00,1.09134,1.09184,1.08958,1.09026,1794 -2017-04-26 09:00:00,1.09029,1.09076,1.08922,1.09007,1189 -2017-04-26 10:00:00,1.09004,1.09004,1.08824,1.08926,1120 -2017-04-26 11:00:00,1.08924,1.08982,1.08918,1.08936,868 -2017-04-26 12:00:00,1.08938,1.08972,1.08812,1.0887,1723 -2017-04-26 13:00:00,1.08874,1.08908,1.08737,1.08898,1699 -2017-04-26 14:00:00,1.089,1.08953,1.0876,1.08763,1457 -2017-04-26 15:00:00,1.0876,1.08844,1.08558,1.08725,1926 -2017-04-26 16:00:00,1.08723,1.08788,1.08667,1.08754,1047 -2017-04-26 17:00:00,1.08757,1.08982,1.08614,1.08982,2571 -2017-04-26 18:00:00,1.08984,1.09124,1.08884,1.08978,2112 -2017-04-26 19:00:00,1.08975,1.09106,1.08928,1.09071,819 -2017-04-26 20:00:00,1.09074,1.09095,1.09033,1.09039,247 -2017-04-26 21:00:00,1.09049,1.09056,1.09002,1.09048,126 -2017-04-26 22:00:00,1.09045,1.09088,1.09016,1.09087,236 -2017-04-26 23:00:00,1.0909,1.091,1.09066,1.09086,144 -2017-04-27 00:00:00,1.09083,1.09158,1.09064,1.09068,422 -2017-04-27 01:00:00,1.09065,1.09108,1.09042,1.09096,417 -2017-04-27 02:00:00,1.09094,1.0921,1.09094,1.09104,406 -2017-04-27 03:00:00,1.09106,1.09159,1.09086,1.09089,458 -2017-04-27 04:00:00,1.09086,1.09097,1.09034,1.09052,292 -2017-04-27 05:00:00,1.0905,1.09077,1.08997,1.09002,233 -2017-04-27 06:00:00,1.09005,1.09074,1.08961,1.09066,748 -2017-04-27 07:00:00,1.09069,1.09184,1.09024,1.09056,1300 -2017-04-27 08:00:00,1.09053,1.092,1.09036,1.09076,1179 -2017-04-27 09:00:00,1.09074,1.09096,1.08918,1.08962,878 -2017-04-27 10:00:00,1.08964,1.09074,1.08954,1.08982,616 -2017-04-27 11:00:00,1.08984,1.09017,1.08801,1.08868,1534 -2017-04-27 12:00:00,1.08866,1.09329,1.08802,1.08956,7247 -2017-04-27 13:00:00,1.08958,1.08966,1.08527,1.08622,4136 -2017-04-27 14:00:00,1.08624,1.0872,1.08516,1.08648,1633 -2017-04-27 15:00:00,1.08652,1.08721,1.08609,1.08635,1251 -2017-04-27 16:00:00,1.08632,1.08799,1.08582,1.08756,1014 -2017-04-27 17:00:00,1.08758,1.08873,1.0874,1.08812,823 -2017-04-27 18:00:00,1.08816,1.08852,1.08776,1.08814,524 -2017-04-27 19:00:00,1.08816,1.08846,1.08726,1.08748,480 -2017-04-27 20:00:00,1.0875,1.08798,1.087,1.08726,331 -2017-04-27 21:00:00,1.0873,1.0875,1.08716,1.08739,225 -2017-04-27 22:00:00,1.08736,1.08757,1.08698,1.08704,211 -2017-04-27 23:00:00,1.08702,1.0872,1.08608,1.08654,326 -2017-04-28 00:00:00,1.08658,1.08684,1.08606,1.08608,565 -2017-04-28 01:00:00,1.0861,1.08708,1.08575,1.0868,551 -2017-04-28 02:00:00,1.08676,1.08722,1.08672,1.08683,271 -2017-04-28 03:00:00,1.08685,1.08685,1.08666,1.08671,143 -2017-04-28 04:00:00,1.08669,1.08681,1.08634,1.08644,107 -2017-04-28 05:00:00,1.08646,1.0866,1.08572,1.08628,371 -2017-04-28 06:00:00,1.0863,1.0885,1.0863,1.088,847 -2017-04-28 07:00:00,1.08802,1.08898,1.08802,1.08854,867 -2017-04-28 08:00:00,1.08856,1.0902,1.08834,1.0902,1160 -2017-04-28 09:00:00,1.09024,1.09472,1.09024,1.09375,3378 -2017-04-28 10:00:00,1.09377,1.0945,1.09343,1.09382,804 -2017-04-28 11:00:00,1.0938,1.09396,1.09264,1.09343,1133 -2017-04-28 12:00:00,1.09346,1.09348,1.09072,1.09122,3086 -2017-04-28 13:00:00,1.09119,1.092,1.09007,1.09176,1894 -2017-04-28 14:00:00,1.09173,1.09218,1.08836,1.08914,2613 -2017-04-28 15:00:00,1.08916,1.0902,1.08882,1.08944,1699 -2017-04-28 16:00:00,1.08946,1.09012,1.08854,1.09008,714 -2017-04-28 17:00:00,1.0901,1.0906,1.08988,1.09017,461 -2017-04-28 18:00:00,1.09015,1.09036,1.08934,1.08948,528 -2017-04-28 19:00:00,1.08952,1.09,1.0892,1.08932,490 -2017-04-28 20:00:00,1.08934,1.09003,1.08896,1.08962,423 -2017-04-30 21:00:00,1.0913,1.0913,1.08924,1.08975,339 -2017-04-30 22:00:00,1.08971,1.09034,1.08952,1.09024,396 -2017-04-30 23:00:00,1.09026,1.09112,1.09026,1.09059,258 -2017-05-01 00:00:00,1.09062,1.09079,1.08996,1.08996,241 -2017-05-01 01:00:00,1.08998,1.09008,1.08893,1.08928,475 -2017-05-01 02:00:00,1.0893,1.0897,1.08924,1.08938,201 -2017-05-01 03:00:00,1.08936,1.08946,1.08914,1.08933,65 -2017-05-01 04:00:00,1.0893,1.08937,1.08904,1.08908,74 -2017-05-01 05:00:00,1.08906,1.08922,1.08862,1.0887,106 -2017-05-01 06:00:00,1.08868,1.08904,1.08846,1.08872,213 -2017-05-01 07:00:00,1.0887,1.08948,1.08842,1.08904,171 -2017-05-01 08:00:00,1.08902,1.08992,1.08902,1.08986,185 -2017-05-01 09:00:00,1.08984,1.08992,1.08955,1.0899,86 -2017-05-01 10:00:00,1.08988,1.09012,1.08976,1.08988,160 -2017-05-01 11:00:00,1.08985,1.09057,1.08964,1.09055,246 -2017-05-01 12:00:00,1.09057,1.0922,1.09039,1.09169,622 -2017-05-01 13:00:00,1.09172,1.09176,1.09058,1.09093,724 -2017-05-01 14:00:00,1.09096,1.09238,1.09096,1.09147,1337 -2017-05-01 15:00:00,1.0915,1.09184,1.09082,1.09114,793 -2017-05-01 16:00:00,1.09112,1.09154,1.09016,1.0904,1094 -2017-05-01 17:00:00,1.09038,1.09077,1.08986,1.0905,575 -2017-05-01 18:00:00,1.09048,1.0908,1.09032,1.09052,336 -2017-05-01 19:00:00,1.09054,1.0908,1.08979,1.08984,316 -2017-05-01 20:00:00,1.08986,1.09011,1.08964,1.0899,198 -2017-05-01 21:00:00,1.08982,1.09026,1.08978,1.08985,197 -2017-05-01 22:00:00,1.08982,1.09115,1.08982,1.09115,297 -2017-05-01 23:00:00,1.09112,1.09128,1.09046,1.09086,170 -2017-05-02 00:00:00,1.09088,1.09125,1.09046,1.0907,441 -2017-05-02 01:00:00,1.09072,1.09117,1.09067,1.09082,320 -2017-05-02 02:00:00,1.09084,1.09117,1.09052,1.09113,247 -2017-05-02 03:00:00,1.09116,1.09174,1.09112,1.09154,207 -2017-05-02 04:00:00,1.09156,1.09158,1.09124,1.09128,184 -2017-05-02 05:00:00,1.09125,1.09256,1.09123,1.09187,343 -2017-05-02 06:00:00,1.09185,1.09228,1.09084,1.09175,1042 -2017-05-02 07:00:00,1.09178,1.09199,1.09073,1.09076,1209 -2017-05-02 08:00:00,1.09074,1.09183,1.09049,1.09148,1121 -2017-05-02 09:00:00,1.0915,1.09214,1.09088,1.09182,884 -2017-05-02 10:00:00,1.0918,1.09196,1.09094,1.0917,616 -2017-05-02 11:00:00,1.09168,1.09184,1.09052,1.09056,800 -2017-05-02 12:00:00,1.09058,1.09158,1.09046,1.09077,1143 -2017-05-02 13:00:00,1.0908,1.09132,1.09045,1.09091,1122 -2017-05-02 14:00:00,1.09093,1.091,1.08884,1.09015,1397 -2017-05-02 15:00:00,1.09017,1.09128,1.08984,1.09096,756 -2017-05-02 16:00:00,1.09098,1.09176,1.09043,1.09063,492 -2017-05-02 17:00:00,1.0906,1.09192,1.09036,1.09189,526 -2017-05-02 18:00:00,1.09186,1.09304,1.0916,1.09267,655 -2017-05-02 19:00:00,1.09269,1.09294,1.09222,1.0926,434 -2017-05-02 20:00:00,1.09262,1.09332,1.09244,1.09308,240 -2017-05-02 21:00:00,1.09284,1.09303,1.09262,1.09289,229 -2017-05-02 22:00:00,1.09287,1.09319,1.09258,1.09308,355 -2017-05-02 23:00:00,1.09306,1.09362,1.09275,1.0935,194 -2017-05-03 00:00:00,1.09352,1.09366,1.09307,1.09332,252 -2017-05-03 01:00:00,1.09329,1.09368,1.09322,1.09336,219 -2017-05-03 02:00:00,1.09338,1.0935,1.09317,1.09344,147 -2017-05-03 03:00:00,1.09341,1.0935,1.09294,1.09294,132 -2017-05-03 04:00:00,1.09296,1.09343,1.09292,1.09343,144 -2017-05-03 05:00:00,1.09346,1.09352,1.09244,1.09248,288 -2017-05-03 06:00:00,1.09251,1.09266,1.0916,1.09217,888 -2017-05-03 07:00:00,1.09215,1.09215,1.09106,1.0919,982 -2017-05-03 08:00:00,1.09192,1.09224,1.09082,1.09122,988 -2017-05-03 09:00:00,1.0912,1.09148,1.09063,1.09096,1022 -2017-05-03 10:00:00,1.09098,1.09152,1.09078,1.091,586 -2017-05-03 11:00:00,1.09102,1.09152,1.09067,1.09142,626 -2017-05-03 12:00:00,1.09144,1.09226,1.0911,1.0915,1960 -2017-05-03 13:00:00,1.09152,1.09214,1.091,1.09108,1043 -2017-05-03 14:00:00,1.09104,1.0915,1.0904,1.09078,1592 -2017-05-03 15:00:00,1.0908,1.09195,1.09068,1.09191,979 -2017-05-03 16:00:00,1.09188,1.09232,1.09151,1.09172,456 -2017-05-03 17:00:00,1.0917,1.0921,1.09108,1.0913,694 -2017-05-03 18:00:00,1.09125,1.09272,1.08932,1.0904,4484 -2017-05-03 19:00:00,1.09043,1.09068,1.0887,1.08954,1116 -2017-05-03 20:00:00,1.08951,1.08954,1.08828,1.08852,341 -2017-05-03 21:00:00,1.08868,1.08894,1.08834,1.08844,414 -2017-05-03 22:00:00,1.08846,1.08912,1.08816,1.08892,240 -2017-05-03 23:00:00,1.0889,1.08904,1.08859,1.08883,281 -2017-05-04 00:00:00,1.0888,1.08946,1.08856,1.08867,370 -2017-05-04 01:00:00,1.0887,1.0895,1.0885,1.0893,396 -2017-05-04 02:00:00,1.08933,1.08948,1.08894,1.0892,214 -2017-05-04 03:00:00,1.08916,1.08969,1.08904,1.08966,235 -2017-05-04 04:00:00,1.08964,1.0897,1.08936,1.08962,109 -2017-05-04 05:00:00,1.0896,1.0896,1.08924,1.08935,154 -2017-05-04 06:00:00,1.08932,1.08976,1.0875,1.08832,1093 -2017-05-04 07:00:00,1.08836,1.09178,1.08816,1.0912,1952 -2017-05-04 08:00:00,1.09122,1.09246,1.09104,1.09186,1606 -2017-05-04 09:00:00,1.09184,1.09357,1.09174,1.09332,1596 -2017-05-04 10:00:00,1.09334,1.09412,1.09286,1.09308,1261 -2017-05-04 11:00:00,1.0931,1.09348,1.0924,1.09241,952 -2017-05-04 12:00:00,1.09244,1.09364,1.09186,1.09346,1649 -2017-05-04 13:00:00,1.09344,1.09387,1.09251,1.09371,1487 -2017-05-04 14:00:00,1.09369,1.09531,1.09313,1.09452,2636 -2017-05-04 15:00:00,1.09454,1.09689,1.09354,1.09666,2755 -2017-05-04 16:00:00,1.09664,1.09792,1.09653,1.09735,1664 -2017-05-04 17:00:00,1.09737,1.09768,1.09662,1.09678,1143 -2017-05-04 18:00:00,1.09675,1.09791,1.09663,1.09778,921 -2017-05-04 19:00:00,1.09774,1.09852,1.09772,1.0985,519 -2017-05-04 20:00:00,1.09852,1.09872,1.09818,1.09842,355 -2017-05-04 21:00:00,1.09834,1.09834,1.09786,1.09794,109 -2017-05-04 22:00:00,1.09796,1.0982,1.09786,1.09806,238 -2017-05-04 23:00:00,1.09808,1.09818,1.09797,1.09806,136 -2017-05-05 00:00:00,1.09809,1.09822,1.09756,1.09794,297 -2017-05-05 01:00:00,1.09791,1.09791,1.09734,1.09749,419 -2017-05-05 02:00:00,1.09747,1.0979,1.0973,1.09782,183 -2017-05-05 03:00:00,1.09784,1.09863,1.09784,1.0984,577 -2017-05-05 04:00:00,1.09843,1.09902,1.09832,1.09835,421 -2017-05-05 05:00:00,1.09838,1.09878,1.0979,1.0979,408 -2017-05-05 06:00:00,1.09792,1.09836,1.09698,1.09703,1403 -2017-05-05 07:00:00,1.097,1.09833,1.09658,1.09744,1447 -2017-05-05 08:00:00,1.09741,1.09777,1.09567,1.09584,1334 -2017-05-05 09:00:00,1.09586,1.0966,1.09564,1.09574,808 -2017-05-05 10:00:00,1.09572,1.09635,1.09538,1.09593,860 -2017-05-05 11:00:00,1.09596,1.09644,1.09554,1.09574,993 -2017-05-05 12:00:00,1.09576,1.09918,1.095,1.0979,4022 -2017-05-05 13:00:00,1.09792,1.09826,1.09658,1.09808,2350 -2017-05-05 14:00:00,1.09811,1.09925,1.09778,1.09843,2049 -2017-05-05 15:00:00,1.09846,1.0999,1.0981,1.09952,1433 -2017-05-05 16:00:00,1.0995,1.09987,1.09846,1.09904,946 -2017-05-05 17:00:00,1.09902,1.09936,1.09849,1.09908,729 -2017-05-05 18:00:00,1.09906,1.09919,1.09839,1.09888,698 -2017-05-05 19:00:00,1.09886,1.09982,1.09854,1.09978,654 -2017-05-05 20:00:00,1.09975,1.09996,1.09928,1.09989,781 -2017-05-07 21:00:00,1.102,1.10237,1.1002,1.10132,848 -2017-05-07 22:00:00,1.10134,1.10142,1.09854,1.09932,1061 -2017-05-07 23:00:00,1.0993,1.0996,1.09634,1.0965,709 -2017-05-08 00:00:00,1.09647,1.09744,1.09574,1.0967,1327 -2017-05-08 01:00:00,1.09668,1.09763,1.09636,1.09744,884 -2017-05-08 02:00:00,1.09746,1.09826,1.09718,1.09754,614 -2017-05-08 03:00:00,1.09752,1.0976,1.09658,1.09712,574 -2017-05-08 04:00:00,1.09715,1.0973,1.09614,1.09724,787 -2017-05-08 05:00:00,1.09721,1.09948,1.09708,1.09943,935 -2017-05-08 06:00:00,1.0994,1.09968,1.09744,1.09838,2024 -2017-05-08 07:00:00,1.09836,1.09856,1.0954,1.09564,2498 -2017-05-08 08:00:00,1.09562,1.09654,1.09514,1.09563,1383 -2017-05-08 09:00:00,1.0956,1.09567,1.09353,1.09384,1372 -2017-05-08 10:00:00,1.09386,1.09576,1.09368,1.09504,949 -2017-05-08 11:00:00,1.09506,1.09566,1.09382,1.09384,1015 -2017-05-08 12:00:00,1.09386,1.09508,1.09314,1.09472,1553 -2017-05-08 13:00:00,1.09474,1.09529,1.09394,1.09436,1434 -2017-05-08 14:00:00,1.09434,1.09484,1.09292,1.09312,1348 -2017-05-08 15:00:00,1.09316,1.09332,1.09165,1.0928,1358 -2017-05-08 16:00:00,1.09278,1.09362,1.09246,1.09324,585 -2017-05-08 17:00:00,1.09322,1.0937,1.09248,1.09284,549 -2017-05-08 18:00:00,1.09287,1.09354,1.09266,1.09334,388 -2017-05-08 19:00:00,1.09332,1.09332,1.09274,1.09302,446 -2017-05-08 20:00:00,1.093,1.09304,1.09214,1.09238,250 -2017-05-08 21:00:00,1.09241,1.09274,1.09191,1.09224,302 -2017-05-08 22:00:00,1.09226,1.09268,1.09192,1.09257,260 -2017-05-08 23:00:00,1.09259,1.09314,1.09248,1.09267,254 -2017-05-09 00:00:00,1.0927,1.09326,1.09219,1.0925,519 -2017-05-09 01:00:00,1.09252,1.09314,1.092,1.09282,597 -2017-05-09 02:00:00,1.0928,1.09309,1.09266,1.09271,391 -2017-05-09 03:00:00,1.09274,1.09336,1.09266,1.09293,323 -2017-05-09 04:00:00,1.09296,1.09318,1.09286,1.09307,188 -2017-05-09 05:00:00,1.09305,1.09316,1.09232,1.09232,256 -2017-05-09 06:00:00,1.09234,1.09248,1.09027,1.09063,1395 -2017-05-09 07:00:00,1.09065,1.0924,1.09056,1.09238,1407 -2017-05-09 08:00:00,1.0924,1.09262,1.09058,1.09063,1052 -2017-05-09 09:00:00,1.09065,1.09091,1.08924,1.09056,1456 -2017-05-09 10:00:00,1.09054,1.09064,1.08862,1.08964,1181 -2017-05-09 11:00:00,1.08961,1.0902,1.088,1.08863,1486 -2017-05-09 12:00:00,1.0886,1.08901,1.0874,1.08842,1691 -2017-05-09 13:00:00,1.08844,1.08992,1.08831,1.08965,1289 -2017-05-09 14:00:00,1.08962,1.09066,1.08898,1.08902,1721 -2017-05-09 15:00:00,1.08905,1.08922,1.08716,1.08744,1186 -2017-05-09 16:00:00,1.08746,1.08996,1.08733,1.08959,910 -2017-05-09 17:00:00,1.08962,1.08969,1.08783,1.08848,1192 -2017-05-09 18:00:00,1.08846,1.08846,1.08636,1.08682,569 -2017-05-09 19:00:00,1.08684,1.0878,1.08664,1.08736,802 -2017-05-09 20:00:00,1.08734,1.08778,1.08704,1.08743,267 -2017-05-09 21:00:00,1.0874,1.088,1.08707,1.08781,544 -2017-05-09 22:00:00,1.08778,1.0888,1.08764,1.08822,490 -2017-05-09 23:00:00,1.08824,1.08909,1.0882,1.08865,327 -2017-05-10 00:00:00,1.08862,1.08969,1.08824,1.08947,782 -2017-05-10 01:00:00,1.08944,1.08982,1.08932,1.0895,542 -2017-05-10 02:00:00,1.08948,1.08966,1.08924,1.08931,259 -2017-05-10 03:00:00,1.08934,1.0897,1.08919,1.08936,112 -2017-05-10 04:00:00,1.08939,1.08975,1.08914,1.08914,145 -2017-05-10 05:00:00,1.08916,1.08965,1.0887,1.08916,363 -2017-05-10 06:00:00,1.08918,1.08943,1.08836,1.08879,1095 -2017-05-10 07:00:00,1.08876,1.0898,1.08876,1.08912,1265 -2017-05-10 08:00:00,1.08914,1.08942,1.08703,1.0871,1046 -2017-05-10 09:00:00,1.08712,1.08738,1.08588,1.08676,1189 -2017-05-10 10:00:00,1.08678,1.08724,1.0863,1.08688,751 -2017-05-10 11:00:00,1.0869,1.08796,1.08605,1.08767,1812 -2017-05-10 12:00:00,1.08769,1.08827,1.08724,1.08799,1312 -2017-05-10 13:00:00,1.08796,1.08824,1.08634,1.08716,1286 -2017-05-10 14:00:00,1.08714,1.08765,1.0863,1.08696,1263 -2017-05-10 15:00:00,1.08694,1.08738,1.08626,1.08722,1118 -2017-05-10 16:00:00,1.08724,1.0875,1.08666,1.08676,642 -2017-05-10 17:00:00,1.08678,1.08702,1.08552,1.08586,890 -2017-05-10 18:00:00,1.08589,1.08621,1.08534,1.0861,541 -2017-05-10 19:00:00,1.08612,1.08688,1.08607,1.08661,517 -2017-05-10 20:00:00,1.08658,1.08682,1.08656,1.08676,124 -2017-05-10 21:00:00,1.08674,1.08702,1.08624,1.08676,591 -2017-05-10 22:00:00,1.08674,1.0869,1.0865,1.08665,291 -2017-05-10 23:00:00,1.08663,1.08692,1.08646,1.08672,187 -2017-05-11 00:00:00,1.0867,1.08758,1.08636,1.08742,316 -2017-05-11 01:00:00,1.0874,1.08778,1.08707,1.08717,273 -2017-05-11 02:00:00,1.0872,1.08798,1.08712,1.08776,293 -2017-05-11 03:00:00,1.08774,1.08777,1.08726,1.08726,198 -2017-05-11 04:00:00,1.08724,1.08728,1.087,1.08702,126 -2017-05-11 05:00:00,1.087,1.08762,1.08646,1.08757,321 -2017-05-11 06:00:00,1.08754,1.08864,1.08718,1.0879,924 -2017-05-11 07:00:00,1.08787,1.0893,1.0872,1.0887,1275 -2017-05-11 08:00:00,1.08872,1.08884,1.0878,1.08785,821 -2017-05-11 09:00:00,1.08782,1.08784,1.08685,1.08696,526 -2017-05-11 10:00:00,1.08694,1.08742,1.08674,1.08701,507 -2017-05-11 11:00:00,1.08704,1.08756,1.08564,1.08568,1479 -2017-05-11 12:00:00,1.0857,1.08621,1.08393,1.08519,2108 -2017-05-11 13:00:00,1.08522,1.08711,1.08519,1.08678,1445 -2017-05-11 14:00:00,1.08675,1.08729,1.0865,1.0867,1396 -2017-05-11 15:00:00,1.08668,1.08756,1.08658,1.0869,980 -2017-05-11 16:00:00,1.08688,1.08716,1.08638,1.08668,514 -2017-05-11 17:00:00,1.0867,1.0875,1.0866,1.08702,633 -2017-05-11 18:00:00,1.087,1.08713,1.08657,1.08668,418 -2017-05-11 19:00:00,1.08665,1.08671,1.086,1.08636,406 -2017-05-11 20:00:00,1.08634,1.08674,1.086,1.08609,185 -2017-05-11 21:00:00,1.08613,1.08648,1.08596,1.08617,377 -2017-05-11 22:00:00,1.08614,1.08652,1.08601,1.08638,145 -2017-05-11 23:00:00,1.0864,1.08676,1.08638,1.08644,97 -2017-05-12 00:00:00,1.08642,1.08666,1.08602,1.08651,368 -2017-05-12 01:00:00,1.08654,1.08711,1.08646,1.08704,222 -2017-05-12 02:00:00,1.08702,1.08738,1.08699,1.08718,184 -2017-05-12 03:00:00,1.08714,1.08724,1.08696,1.08696,137 -2017-05-12 04:00:00,1.08694,1.08715,1.08668,1.08711,166 -2017-05-12 05:00:00,1.08713,1.08726,1.08692,1.08714,188 -2017-05-12 06:00:00,1.08712,1.08721,1.08598,1.086,710 -2017-05-12 07:00:00,1.08598,1.08674,1.08557,1.08632,1143 -2017-05-12 08:00:00,1.0863,1.08732,1.08614,1.08656,736 -2017-05-12 09:00:00,1.08654,1.08768,1.08631,1.0873,843 -2017-05-12 10:00:00,1.08728,1.08782,1.08697,1.08762,704 -2017-05-12 11:00:00,1.08764,1.0878,1.08703,1.08709,574 -2017-05-12 12:00:00,1.08711,1.09126,1.08706,1.09061,3273 -2017-05-12 13:00:00,1.09063,1.09254,1.09063,1.09223,3295 -2017-05-12 14:00:00,1.0922,1.09278,1.09151,1.09212,1805 -2017-05-12 15:00:00,1.09214,1.09343,1.09172,1.09256,1227 -2017-05-12 16:00:00,1.09258,1.09286,1.09148,1.09186,599 -2017-05-12 17:00:00,1.09189,1.09233,1.09178,1.09228,405 -2017-05-12 18:00:00,1.0923,1.09276,1.09193,1.09243,284 -2017-05-12 19:00:00,1.0924,1.09311,1.09226,1.093,453 -2017-05-12 20:00:00,1.09297,1.0933,1.09272,1.09314,294 -2017-05-14 21:00:00,1.09304,1.09354,1.09292,1.09324,223 -2017-05-14 22:00:00,1.09326,1.09338,1.09236,1.0926,604 -2017-05-14 23:00:00,1.09262,1.09284,1.09229,1.09282,178 -2017-05-15 00:00:00,1.09279,1.09336,1.09237,1.09246,527 -2017-05-15 01:00:00,1.09248,1.09284,1.09228,1.09275,260 -2017-05-15 02:00:00,1.09272,1.09312,1.09258,1.09274,288 -2017-05-15 03:00:00,1.09278,1.09304,1.09263,1.09293,101 -2017-05-15 04:00:00,1.0929,1.09314,1.09272,1.09302,116 -2017-05-15 05:00:00,1.09304,1.09335,1.09292,1.09292,201 -2017-05-15 06:00:00,1.09294,1.09426,1.0926,1.09358,1173 -2017-05-15 07:00:00,1.09356,1.09473,1.09339,1.09418,1179 -2017-05-15 08:00:00,1.0942,1.09497,1.09384,1.09452,817 -2017-05-15 09:00:00,1.09449,1.09599,1.09449,1.0954,1223 -2017-05-15 10:00:00,1.09542,1.097,1.09526,1.09698,1007 -2017-05-15 11:00:00,1.09696,1.09732,1.09642,1.09659,739 -2017-05-15 12:00:00,1.09661,1.0982,1.09654,1.09784,1371 -2017-05-15 13:00:00,1.09786,1.09894,1.09762,1.09792,1244 -2017-05-15 14:00:00,1.09794,1.0986,1.09728,1.09782,1049 -2017-05-15 15:00:00,1.09785,1.09862,1.09766,1.0979,960 -2017-05-15 16:00:00,1.09788,1.09808,1.09709,1.09742,565 -2017-05-15 17:00:00,1.0974,1.09778,1.09665,1.09696,504 -2017-05-15 18:00:00,1.09698,1.09785,1.0966,1.0978,368 -2017-05-15 19:00:00,1.09783,1.09799,1.09748,1.09778,240 -2017-05-15 20:00:00,1.09776,1.09782,1.09749,1.09751,129 -2017-05-15 21:00:00,1.09747,1.09797,1.09743,1.09771,169 -2017-05-15 22:00:00,1.09774,1.09834,1.0977,1.09811,217 -2017-05-15 23:00:00,1.09808,1.09834,1.09788,1.098,102 -2017-05-16 00:00:00,1.09802,1.09857,1.09792,1.09835,368 -2017-05-16 01:00:00,1.09837,1.099,1.09808,1.0987,317 -2017-05-16 02:00:00,1.09872,1.09883,1.09834,1.09883,277 -2017-05-16 03:00:00,1.0988,1.09892,1.09865,1.09892,101 -2017-05-16 04:00:00,1.0989,1.09938,1.09875,1.0992,189 -2017-05-16 05:00:00,1.09923,1.10005,1.09914,1.09922,467 -2017-05-16 06:00:00,1.09919,1.1018,1.09914,1.10141,1306 -2017-05-16 07:00:00,1.10139,1.10365,1.1012,1.1029,1822 -2017-05-16 08:00:00,1.10288,1.10497,1.10281,1.10456,1476 -2017-05-16 09:00:00,1.10458,1.10475,1.103,1.10444,1341 -2017-05-16 10:00:00,1.10441,1.10589,1.10404,1.10532,1120 -2017-05-16 11:00:00,1.1053,1.10658,1.10508,1.10528,1167 -2017-05-16 12:00:00,1.10531,1.10888,1.10524,1.10778,1955 -2017-05-16 13:00:00,1.10776,1.10786,1.1065,1.10676,1714 -2017-05-16 14:00:00,1.10672,1.10862,1.10668,1.10822,1549 -2017-05-16 15:00:00,1.1082,1.1084,1.1064,1.10716,1477 -2017-05-16 16:00:00,1.10714,1.10812,1.10679,1.10756,873 -2017-05-16 17:00:00,1.10758,1.10923,1.10754,1.10902,595 -2017-05-16 18:00:00,1.109,1.10972,1.109,1.10952,504 -2017-05-16 19:00:00,1.1095,1.1097,1.10846,1.10849,472 -2017-05-16 20:00:00,1.10852,1.10898,1.10802,1.10826,295 -2017-05-16 21:00:00,1.10831,1.10863,1.10802,1.10808,724 -2017-05-16 22:00:00,1.1081,1.10952,1.1081,1.10949,464 -2017-05-16 23:00:00,1.10946,1.10968,1.10896,1.10936,430 -2017-05-17 00:00:00,1.10934,1.1098,1.10867,1.10956,664 -2017-05-17 01:00:00,1.10954,1.10989,1.10944,1.10975,382 -2017-05-17 02:00:00,1.10973,1.1114,1.10959,1.111,527 -2017-05-17 03:00:00,1.11102,1.1117,1.111,1.1113,401 -2017-05-17 04:00:00,1.11134,1.11164,1.1104,1.11061,478 -2017-05-17 05:00:00,1.11063,1.11121,1.10968,1.11089,747 -2017-05-17 06:00:00,1.11092,1.11222,1.11038,1.11084,1312 -2017-05-17 07:00:00,1.11086,1.1118,1.10817,1.10889,2234 -2017-05-17 08:00:00,1.10892,1.10999,1.10844,1.10854,1541 -2017-05-17 09:00:00,1.10856,1.11002,1.10849,1.10958,1137 -2017-05-17 10:00:00,1.1096,1.11128,1.10941,1.11088,1062 -2017-05-17 11:00:00,1.11086,1.11133,1.1101,1.11119,994 -2017-05-17 12:00:00,1.11122,1.11244,1.11115,1.11233,1367 -2017-05-17 13:00:00,1.11231,1.11259,1.11017,1.11258,2651 -2017-05-17 14:00:00,1.11256,1.1147,1.11254,1.11466,2839 -2017-05-17 15:00:00,1.11468,1.11504,1.11302,1.11332,1873 -2017-05-17 16:00:00,1.1133,1.1144,1.11323,1.1138,910 -2017-05-17 17:00:00,1.11382,1.1155,1.11376,1.1155,953 -2017-05-17 18:00:00,1.11548,1.11581,1.1146,1.11476,925 -2017-05-17 19:00:00,1.11474,1.11572,1.11442,1.11528,794 -2017-05-17 20:00:00,1.11526,1.11622,1.11507,1.11599,609 -2017-05-17 21:00:00,1.11574,1.1171,1.11574,1.11652,742 -2017-05-17 22:00:00,1.11654,1.11689,1.11613,1.11618,546 -2017-05-17 23:00:00,1.11616,1.11641,1.11511,1.11542,534 -2017-05-18 00:00:00,1.1154,1.11659,1.1151,1.11648,819 -2017-05-18 01:00:00,1.11645,1.11719,1.11534,1.1155,905 -2017-05-18 02:00:00,1.11552,1.1158,1.1151,1.11559,510 -2017-05-18 03:00:00,1.11562,1.11612,1.1155,1.1161,277 -2017-05-18 04:00:00,1.11612,1.1162,1.11392,1.1144,626 -2017-05-18 05:00:00,1.11442,1.11458,1.11383,1.11388,596 -2017-05-18 06:00:00,1.11391,1.11458,1.11214,1.11304,1713 -2017-05-18 07:00:00,1.11306,1.11454,1.11298,1.11334,1746 -2017-05-18 08:00:00,1.11331,1.1145,1.11271,1.11271,2070 -2017-05-18 09:00:00,1.11273,1.11402,1.11076,1.112,3004 -2017-05-18 10:00:00,1.11198,1.11375,1.11178,1.11363,1437 -2017-05-18 11:00:00,1.11361,1.11397,1.11118,1.1121,1807 -2017-05-18 12:00:00,1.11212,1.11369,1.11042,1.11088,2398 -2017-05-18 13:00:00,1.1109,1.11184,1.11048,1.11131,2555 -2017-05-18 14:00:00,1.11129,1.11282,1.11083,1.11267,2485 -2017-05-18 15:00:00,1.11269,1.11342,1.11208,1.11296,1793 -2017-05-18 16:00:00,1.11299,1.11378,1.11228,1.11256,1394 -2017-05-18 17:00:00,1.11253,1.11302,1.10837,1.10894,2885 -2017-05-18 18:00:00,1.1089,1.1105,1.1076,1.11029,2250 -2017-05-18 19:00:00,1.11026,1.11141,1.10931,1.11131,1211 -2017-05-18 20:00:00,1.11129,1.11129,1.11022,1.11026,339 -2017-05-18 21:00:00,1.11032,1.11035,1.10974,1.11009,347 -2017-05-18 22:00:00,1.11006,1.11113,1.10986,1.11079,272 -2017-05-18 23:00:00,1.11076,1.11148,1.11076,1.11102,254 -2017-05-19 00:00:00,1.111,1.11114,1.11062,1.1109,450 -2017-05-19 01:00:00,1.11092,1.11138,1.11051,1.11076,533 -2017-05-19 02:00:00,1.11074,1.11074,1.10998,1.11026,415 -2017-05-19 03:00:00,1.11023,1.11104,1.11023,1.11089,277 -2017-05-19 04:00:00,1.11091,1.11136,1.11073,1.11119,202 -2017-05-19 05:00:00,1.11122,1.11145,1.11094,1.11137,261 -2017-05-19 06:00:00,1.11134,1.11269,1.11092,1.11227,1073 -2017-05-19 07:00:00,1.1123,1.11433,1.11222,1.11386,1356 -2017-05-19 08:00:00,1.1139,1.1161,1.11354,1.11493,1454 -2017-05-19 09:00:00,1.1149,1.11654,1.1147,1.11584,1179 -2017-05-19 10:00:00,1.11582,1.11678,1.1156,1.11632,775 -2017-05-19 11:00:00,1.11634,1.11835,1.11607,1.1178,1208 -2017-05-19 12:00:00,1.11782,1.11859,1.11751,1.11795,1381 -2017-05-19 13:00:00,1.11792,1.11968,1.11782,1.11889,1648 -2017-05-19 14:00:00,1.11892,1.11971,1.11842,1.11954,1665 -2017-05-19 15:00:00,1.11956,1.11967,1.11875,1.11892,933 -2017-05-19 16:00:00,1.1189,1.11956,1.11852,1.11908,612 -2017-05-19 17:00:00,1.11905,1.12118,1.11898,1.12106,1040 -2017-05-19 18:00:00,1.12103,1.12108,1.12044,1.12044,593 -2017-05-19 19:00:00,1.12046,1.12114,1.11985,1.12044,1029 -2017-05-19 20:00:00,1.12042,1.12084,1.12019,1.12068,264 -2017-05-21 21:00:00,1.11962,1.1209,1.11962,1.12022,378 -2017-05-21 22:00:00,1.12026,1.12077,1.12004,1.12068,388 -2017-05-21 23:00:00,1.12066,1.12101,1.1201,1.12034,626 -2017-05-22 00:00:00,1.12032,1.12032,1.11864,1.11867,676 -2017-05-22 01:00:00,1.1187,1.11938,1.11826,1.11932,541 -2017-05-22 02:00:00,1.11929,1.11929,1.11836,1.11918,317 -2017-05-22 03:00:00,1.11915,1.11962,1.11906,1.11918,196 -2017-05-22 04:00:00,1.1192,1.11942,1.11885,1.11888,171 -2017-05-22 05:00:00,1.1189,1.1194,1.11852,1.1194,308 -2017-05-22 06:00:00,1.11938,1.1201,1.11804,1.11846,1254 -2017-05-22 07:00:00,1.11843,1.11938,1.11642,1.11716,1905 -2017-05-22 08:00:00,1.11714,1.11787,1.11616,1.11682,1130 -2017-05-22 09:00:00,1.1168,1.12067,1.11661,1.12009,1631 -2017-05-22 10:00:00,1.12012,1.12364,1.12012,1.12274,2598 -2017-05-22 11:00:00,1.12272,1.1246,1.12264,1.12352,1577 -2017-05-22 12:00:00,1.12354,1.12498,1.12338,1.12454,1166 -2017-05-22 13:00:00,1.12457,1.12588,1.12408,1.12574,1728 -2017-05-22 14:00:00,1.12572,1.12635,1.1244,1.12468,1646 -2017-05-22 15:00:00,1.1247,1.12518,1.12287,1.12349,1368 -2017-05-22 16:00:00,1.12351,1.12376,1.12291,1.1234,619 -2017-05-22 17:00:00,1.12338,1.12441,1.1233,1.12419,372 -2017-05-22 18:00:00,1.12422,1.12434,1.12344,1.12358,463 -2017-05-22 19:00:00,1.1236,1.12378,1.12295,1.12372,471 -2017-05-22 20:00:00,1.1237,1.12424,1.12362,1.12373,246 -2017-05-22 21:00:00,1.1237,1.12416,1.12365,1.12372,557 -2017-05-22 22:00:00,1.12375,1.12424,1.12306,1.12388,408 -2017-05-22 23:00:00,1.1239,1.1244,1.12367,1.12376,349 -2017-05-23 00:00:00,1.12374,1.12472,1.12366,1.12395,531 -2017-05-23 01:00:00,1.12398,1.12516,1.12394,1.12496,410 -2017-05-23 02:00:00,1.12498,1.12541,1.12473,1.12518,390 -2017-05-23 03:00:00,1.12515,1.12518,1.12438,1.12456,249 -2017-05-23 04:00:00,1.12454,1.12534,1.12424,1.12504,195 -2017-05-23 05:00:00,1.12502,1.12512,1.12438,1.12443,330 -2017-05-23 06:00:00,1.12446,1.12456,1.12222,1.12252,2199 -2017-05-23 07:00:00,1.12254,1.12684,1.12232,1.12524,3432 -2017-05-23 08:00:00,1.12529,1.126,1.12414,1.12485,2420 -2017-05-23 09:00:00,1.12482,1.12629,1.12453,1.12582,1264 -2017-05-23 10:00:00,1.12584,1.12602,1.12376,1.12386,969 -2017-05-23 11:00:00,1.12388,1.12399,1.12164,1.12178,1047 -2017-05-23 12:00:00,1.1218,1.12384,1.12112,1.1234,1698 -2017-05-23 13:00:00,1.12338,1.12434,1.12256,1.12257,1449 -2017-05-23 14:00:00,1.12255,1.12332,1.12132,1.1229,2071 -2017-05-23 15:00:00,1.12287,1.12494,1.11935,1.11968,4542 -2017-05-23 16:00:00,1.11971,1.12074,1.11823,1.11922,2407 -2017-05-23 17:00:00,1.1192,1.12088,1.11892,1.11966,1103 -2017-05-23 18:00:00,1.11968,1.11988,1.11766,1.1185,1025 -2017-05-23 19:00:00,1.11852,1.11855,1.11752,1.11829,982 -2017-05-23 20:00:00,1.11827,1.11854,1.11774,1.11824,381 -2017-05-23 21:00:00,1.11831,1.11857,1.11804,1.11844,367 -2017-05-23 22:00:00,1.11842,1.11894,1.1184,1.11873,275 -2017-05-23 23:00:00,1.1187,1.1187,1.11774,1.11789,213 -2017-05-24 00:00:00,1.11792,1.11918,1.11782,1.11867,694 -2017-05-24 01:00:00,1.1187,1.11912,1.11806,1.11852,575 -2017-05-24 02:00:00,1.1185,1.119,1.11844,1.11856,309 -2017-05-24 03:00:00,1.11854,1.11856,1.1178,1.11806,316 -2017-05-24 04:00:00,1.1181,1.11822,1.11786,1.118,189 -2017-05-24 05:00:00,1.11802,1.11809,1.1173,1.11783,381 -2017-05-24 06:00:00,1.11781,1.11832,1.11715,1.11775,1247 -2017-05-24 07:00:00,1.11777,1.11849,1.117,1.11758,1567 -2017-05-24 08:00:00,1.11755,1.11968,1.11734,1.11856,1727 -2017-05-24 09:00:00,1.11854,1.11888,1.11754,1.11763,1023 -2017-05-24 10:00:00,1.11766,1.1193,1.1175,1.1191,1254 -2017-05-24 11:00:00,1.11908,1.11926,1.1179,1.11877,1044 -2017-05-24 12:00:00,1.11874,1.12022,1.1185,1.11978,1846 -2017-05-24 13:00:00,1.11982,1.12047,1.11824,1.1187,2326 -2017-05-24 14:00:00,1.11872,1.11968,1.11815,1.11839,1921 -2017-05-24 15:00:00,1.11842,1.11873,1.11687,1.11746,1165 -2017-05-24 16:00:00,1.11748,1.11822,1.1174,1.11778,530 -2017-05-24 17:00:00,1.11776,1.11898,1.1176,1.11872,848 -2017-05-24 18:00:00,1.11868,1.12163,1.11795,1.11974,5268 -2017-05-24 19:00:00,1.11971,1.12176,1.11937,1.12152,1554 -2017-05-24 20:00:00,1.12149,1.12201,1.12122,1.12187,361 -2017-05-24 21:00:00,1.12192,1.12198,1.12122,1.12136,215 -2017-05-24 22:00:00,1.12138,1.12235,1.1211,1.12174,370 -2017-05-24 23:00:00,1.12176,1.12334,1.12176,1.12306,343 -2017-05-25 00:00:00,1.12308,1.12308,1.12207,1.12231,374 -2017-05-25 01:00:00,1.12229,1.1231,1.12188,1.12238,558 -2017-05-25 02:00:00,1.12236,1.124,1.12228,1.12393,533 -2017-05-25 03:00:00,1.12391,1.12446,1.12384,1.12388,452 -2017-05-25 04:00:00,1.1239,1.12436,1.12364,1.12409,240 -2017-05-25 05:00:00,1.12412,1.12449,1.12346,1.12436,383 -2017-05-25 06:00:00,1.12434,1.12438,1.12268,1.12297,1228 -2017-05-25 07:00:00,1.12295,1.12448,1.12255,1.12434,1458 -2017-05-25 08:00:00,1.12432,1.12504,1.12351,1.12422,1656 -2017-05-25 09:00:00,1.12419,1.12419,1.1218,1.12251,1231 -2017-05-25 10:00:00,1.12249,1.12249,1.1209,1.12172,1161 -2017-05-25 11:00:00,1.1217,1.1219,1.12062,1.12142,969 -2017-05-25 12:00:00,1.12145,1.12157,1.11936,1.12029,1312 -2017-05-25 13:00:00,1.12026,1.12154,1.12007,1.12143,1091 -2017-05-25 14:00:00,1.1214,1.12224,1.1205,1.12131,1396 -2017-05-25 15:00:00,1.12134,1.12234,1.12116,1.12174,1132 -2017-05-25 16:00:00,1.12176,1.12262,1.1215,1.12182,723 -2017-05-25 17:00:00,1.12179,1.12209,1.12008,1.12082,835 -2017-05-25 18:00:00,1.1208,1.1208,1.11986,1.12048,597 -2017-05-25 19:00:00,1.12046,1.1214,1.12028,1.1211,549 -2017-05-25 20:00:00,1.12108,1.12116,1.12038,1.12104,275 -2017-05-25 21:00:00,1.12086,1.12128,1.12074,1.12088,266 -2017-05-25 22:00:00,1.12092,1.12161,1.12078,1.12127,271 -2017-05-25 23:00:00,1.12129,1.12129,1.1208,1.12102,146 -2017-05-26 00:00:00,1.12104,1.12124,1.11966,1.12059,590 -2017-05-26 01:00:00,1.12061,1.12078,1.11872,1.11886,533 -2017-05-26 02:00:00,1.11888,1.11992,1.11852,1.1199,647 -2017-05-26 03:00:00,1.11992,1.12056,1.1199,1.12014,433 -2017-05-26 04:00:00,1.12012,1.12024,1.11974,1.12002,195 -2017-05-26 05:00:00,1.12004,1.12039,1.11912,1.1195,355 -2017-05-26 06:00:00,1.11948,1.12128,1.11912,1.12112,1567 -2017-05-26 07:00:00,1.12114,1.12243,1.1208,1.12186,1169 -2017-05-26 08:00:00,1.12188,1.12345,1.12174,1.12238,1480 -2017-05-26 09:00:00,1.12241,1.12252,1.12114,1.12172,1053 -2017-05-26 10:00:00,1.12175,1.12268,1.12139,1.12216,792 -2017-05-26 11:00:00,1.12214,1.1223,1.1191,1.11912,1379 -2017-05-26 12:00:00,1.11914,1.12002,1.11779,1.11803,2180 -2017-05-26 13:00:00,1.11806,1.11812,1.11606,1.11678,2016 -2017-05-26 14:00:00,1.1168,1.11875,1.11648,1.1185,1665 -2017-05-26 15:00:00,1.11848,1.11865,1.11662,1.11691,1347 -2017-05-26 16:00:00,1.11693,1.11797,1.11616,1.11774,782 -2017-05-26 17:00:00,1.11776,1.11832,1.11759,1.11768,597 -2017-05-26 18:00:00,1.11766,1.11778,1.11732,1.11762,337 -2017-05-26 19:00:00,1.11764,1.11786,1.1169,1.11712,372 -2017-05-26 20:00:00,1.1171,1.11837,1.1168,1.11813,497 -2017-05-28 21:00:00,1.11738,1.11768,1.11685,1.11758,80 -2017-05-28 22:00:00,1.11761,1.11826,1.1176,1.11826,318 -2017-05-28 23:00:00,1.11828,1.11848,1.11728,1.11761,202 -2017-05-29 00:00:00,1.11758,1.11758,1.11619,1.11723,542 -2017-05-29 01:00:00,1.11726,1.11733,1.11654,1.11673,277 -2017-05-29 02:00:00,1.11671,1.11692,1.11634,1.11638,191 -2017-05-29 03:00:00,1.11641,1.1165,1.11628,1.11648,124 -2017-05-29 04:00:00,1.11646,1.1166,1.11626,1.11637,179 -2017-05-29 05:00:00,1.11639,1.11732,1.11636,1.11656,252 -2017-05-29 06:00:00,1.11653,1.11771,1.11653,1.11712,564 -2017-05-29 07:00:00,1.11714,1.11822,1.11666,1.1179,704 -2017-05-29 08:00:00,1.11793,1.11898,1.11774,1.11835,585 -2017-05-29 09:00:00,1.11838,1.11882,1.11774,1.11871,497 -2017-05-29 10:00:00,1.11868,1.11868,1.1181,1.1184,562 -2017-05-29 11:00:00,1.11837,1.11883,1.11832,1.11869,397 -2017-05-29 12:00:00,1.11871,1.11899,1.11842,1.1185,458 -2017-05-29 13:00:00,1.11852,1.11885,1.117,1.11716,846 -2017-05-29 14:00:00,1.11719,1.1179,1.11676,1.11762,640 -2017-05-29 15:00:00,1.11764,1.11832,1.11762,1.11798,495 -2017-05-29 16:00:00,1.118,1.1182,1.11738,1.1174,282 -2017-05-29 17:00:00,1.11738,1.11767,1.11694,1.11711,266 -2017-05-29 18:00:00,1.11708,1.11715,1.11685,1.11709,117 -2017-05-29 19:00:00,1.11712,1.11734,1.11698,1.11716,173 -2017-05-29 20:00:00,1.11718,1.11724,1.11622,1.1163,408 -2017-05-29 21:00:00,1.11633,1.1169,1.11511,1.11522,342 -2017-05-29 22:00:00,1.11525,1.1153,1.11353,1.11387,779 -2017-05-29 23:00:00,1.11389,1.11398,1.11274,1.11292,437 -2017-05-30 00:00:00,1.11294,1.11378,1.11282,1.11336,626 -2017-05-30 01:00:00,1.11333,1.11336,1.11221,1.11236,587 -2017-05-30 02:00:00,1.11234,1.113,1.11226,1.11292,222 -2017-05-30 03:00:00,1.1129,1.11308,1.11256,1.11256,140 -2017-05-30 04:00:00,1.11258,1.11293,1.11232,1.11276,187 -2017-05-30 05:00:00,1.11278,1.1132,1.1116,1.11162,487 -2017-05-30 06:00:00,1.11164,1.11312,1.11096,1.1131,1324 -2017-05-30 07:00:00,1.11312,1.11449,1.11271,1.1141,1958 -2017-05-30 08:00:00,1.11407,1.1149,1.11388,1.11401,1351 -2017-05-30 09:00:00,1.11403,1.11668,1.11366,1.11648,1383 -2017-05-30 10:00:00,1.11645,1.11684,1.11531,1.11538,973 -2017-05-30 11:00:00,1.11536,1.11937,1.11463,1.11742,3278 -2017-05-30 12:00:00,1.11745,1.1176,1.11543,1.11624,2448 -2017-05-30 13:00:00,1.11626,1.11919,1.11626,1.1191,2111 -2017-05-30 14:00:00,1.11912,1.12054,1.11752,1.11775,2240 -2017-05-30 15:00:00,1.11778,1.11894,1.1176,1.11824,1072 -2017-05-30 16:00:00,1.11826,1.11838,1.1172,1.11744,623 -2017-05-30 17:00:00,1.11746,1.11838,1.11744,1.11806,406 -2017-05-30 18:00:00,1.11803,1.11902,1.11792,1.11886,379 -2017-05-30 19:00:00,1.11882,1.11936,1.11842,1.11886,398 -2017-05-30 20:00:00,1.11883,1.11968,1.11851,1.11858,358 -2017-05-30 21:00:00,1.11867,1.119,1.1178,1.11798,474 -2017-05-30 22:00:00,1.118,1.11809,1.11732,1.11735,310 -2017-05-30 23:00:00,1.11733,1.11738,1.11702,1.11729,187 -2017-05-31 00:00:00,1.11732,1.1182,1.11695,1.11712,566 -2017-05-31 01:00:00,1.11714,1.118,1.11707,1.1175,483 -2017-05-31 02:00:00,1.11752,1.11794,1.11708,1.11756,334 -2017-05-31 03:00:00,1.11758,1.11786,1.11736,1.11765,183 -2017-05-31 04:00:00,1.11768,1.11782,1.11718,1.11728,129 -2017-05-31 05:00:00,1.1173,1.1176,1.11646,1.11682,381 -2017-05-31 06:00:00,1.11679,1.11897,1.11649,1.11883,1185 -2017-05-31 07:00:00,1.11881,1.1197,1.11798,1.11851,1233 -2017-05-31 08:00:00,1.11849,1.11854,1.117,1.11746,1502 -2017-05-31 09:00:00,1.11748,1.11922,1.11712,1.11904,1674 -2017-05-31 10:00:00,1.11906,1.12181,1.11852,1.12128,1709 -2017-05-31 11:00:00,1.12126,1.12288,1.12126,1.12216,1306 -2017-05-31 12:00:00,1.12219,1.1225,1.12112,1.12223,1339 -2017-05-31 13:00:00,1.12226,1.12422,1.12176,1.12334,1984 -2017-05-31 14:00:00,1.12336,1.12464,1.12212,1.12459,2528 -2017-05-31 15:00:00,1.12461,1.12524,1.12306,1.1237,2619 -2017-05-31 16:00:00,1.12368,1.1238,1.12282,1.12368,791 -2017-05-31 17:00:00,1.12371,1.12424,1.12281,1.12394,978 -2017-05-31 18:00:00,1.12392,1.12474,1.12348,1.12458,674 -2017-05-31 19:00:00,1.1246,1.12472,1.12302,1.12336,649 -2017-05-31 20:00:00,1.12338,1.12443,1.12322,1.12433,413 -2017-05-31 21:00:00,1.12466,1.12491,1.1241,1.12433,364 -2017-05-31 22:00:00,1.1243,1.12434,1.12358,1.12388,432 -2017-05-31 23:00:00,1.1239,1.1245,1.12388,1.12391,249 -2017-06-01 00:00:00,1.12388,1.12422,1.12336,1.12345,398 -2017-06-01 01:00:00,1.12342,1.12556,1.12338,1.12471,653 -2017-06-01 02:00:00,1.12468,1.12566,1.12416,1.12423,520 -2017-06-01 03:00:00,1.1242,1.12492,1.12374,1.12468,407 -2017-06-01 04:00:00,1.12466,1.12476,1.12436,1.12466,238 -2017-06-01 05:00:00,1.12463,1.12478,1.12376,1.12376,429 -2017-06-01 06:00:00,1.12378,1.12488,1.12276,1.1244,1263 -2017-06-01 07:00:00,1.12438,1.12458,1.1229,1.12324,1404 -2017-06-01 08:00:00,1.12327,1.12378,1.12229,1.12262,1086 -2017-06-01 09:00:00,1.12265,1.1237,1.12222,1.12356,1216 -2017-06-01 10:00:00,1.12354,1.12368,1.12241,1.12278,804 -2017-06-01 11:00:00,1.12276,1.12281,1.12168,1.12182,754 -2017-06-01 12:00:00,1.12184,1.12246,1.12023,1.12148,2078 -2017-06-01 13:00:00,1.1215,1.1226,1.12132,1.12222,1165 -2017-06-01 14:00:00,1.12225,1.12344,1.1216,1.12256,1591 -2017-06-01 15:00:00,1.12258,1.12259,1.12091,1.12134,904 -2017-06-01 16:00:00,1.12132,1.12172,1.12062,1.12095,530 -2017-06-01 17:00:00,1.12098,1.12134,1.12068,1.12112,388 -2017-06-01 18:00:00,1.12109,1.12194,1.12069,1.12147,615 -2017-06-01 19:00:00,1.12144,1.1218,1.12113,1.12147,410 -2017-06-01 20:00:00,1.12144,1.12164,1.12105,1.12124,210 -2017-06-01 21:00:00,1.12142,1.12172,1.12122,1.1214,253 -2017-06-01 22:00:00,1.12143,1.12195,1.12136,1.1219,155 -2017-06-01 23:00:00,1.12188,1.1219,1.12124,1.12128,140 -2017-06-02 00:00:00,1.12131,1.12181,1.12122,1.1217,357 -2017-06-02 01:00:00,1.12167,1.12222,1.12157,1.12172,330 -2017-06-02 02:00:00,1.12176,1.12204,1.12158,1.1217,152 -2017-06-02 03:00:00,1.12168,1.12188,1.12153,1.12186,134 -2017-06-02 04:00:00,1.12184,1.12202,1.12168,1.12194,114 -2017-06-02 05:00:00,1.12198,1.12204,1.12159,1.12175,191 -2017-06-02 06:00:00,1.12177,1.12216,1.12158,1.12184,579 -2017-06-02 07:00:00,1.12182,1.1228,1.1215,1.1215,927 -2017-06-02 08:00:00,1.12152,1.12268,1.12146,1.12211,708 -2017-06-02 09:00:00,1.12208,1.12237,1.12168,1.1221,568 -2017-06-02 10:00:00,1.12208,1.1224,1.12156,1.12186,771 -2017-06-02 11:00:00,1.12183,1.12202,1.12052,1.1206,919 -2017-06-02 12:00:00,1.12062,1.12825,1.12057,1.12694,5016 -2017-06-02 13:00:00,1.12697,1.12774,1.12548,1.12759,2905 -2017-06-02 14:00:00,1.12762,1.12794,1.12562,1.12754,1670 -2017-06-02 15:00:00,1.12757,1.12816,1.12673,1.12696,1272 -2017-06-02 16:00:00,1.12698,1.12765,1.1266,1.12698,762 -2017-06-02 17:00:00,1.12701,1.12764,1.1267,1.12756,598 -2017-06-02 18:00:00,1.12758,1.12795,1.12742,1.1277,436 -2017-06-02 19:00:00,1.12772,1.12852,1.12752,1.12821,613 -2017-06-02 20:00:00,1.12819,1.12848,1.12797,1.12825,319 -2017-06-04 21:00:00,1.12736,1.12831,1.12736,1.12792,206 -2017-06-04 22:00:00,1.12787,1.12838,1.12733,1.12792,611 -2017-06-04 23:00:00,1.1279,1.1281,1.1276,1.12776,323 -2017-06-05 00:00:00,1.12778,1.12783,1.1269,1.12727,505 -2017-06-05 01:00:00,1.12724,1.1277,1.12688,1.12694,313 -2017-06-05 02:00:00,1.12697,1.12738,1.12652,1.12738,248 -2017-06-05 03:00:00,1.12735,1.12748,1.12669,1.12706,239 -2017-06-05 04:00:00,1.12708,1.12712,1.12634,1.12666,177 -2017-06-05 05:00:00,1.12663,1.1267,1.12615,1.1265,337 -2017-06-05 06:00:00,1.12647,1.127,1.12624,1.12636,769 -2017-06-05 07:00:00,1.12634,1.12788,1.12604,1.12651,1259 -2017-06-05 08:00:00,1.12649,1.12722,1.12631,1.1272,1043 -2017-06-05 09:00:00,1.12718,1.12718,1.12618,1.12648,804 -2017-06-05 10:00:00,1.1265,1.12671,1.12352,1.1243,1246 -2017-06-05 11:00:00,1.12428,1.12474,1.12364,1.12471,875 -2017-06-05 12:00:00,1.12468,1.12516,1.12407,1.1242,1069 -2017-06-05 13:00:00,1.12423,1.12556,1.12343,1.12496,1127 -2017-06-05 14:00:00,1.12492,1.12554,1.1243,1.12504,1473 -2017-06-05 15:00:00,1.12507,1.1255,1.12474,1.125,797 -2017-06-05 16:00:00,1.12498,1.12548,1.12479,1.1253,412 -2017-06-05 17:00:00,1.12532,1.12644,1.12532,1.12575,452 -2017-06-05 18:00:00,1.12577,1.1258,1.12512,1.12573,351 -2017-06-05 19:00:00,1.12575,1.12577,1.1253,1.12554,301 -2017-06-05 20:00:00,1.12552,1.1259,1.12538,1.12544,153 -2017-06-05 21:00:00,1.12542,1.12599,1.12536,1.12546,322 -2017-06-05 22:00:00,1.12542,1.12598,1.12542,1.12584,138 -2017-06-05 23:00:00,1.12586,1.12596,1.12552,1.12572,110 -2017-06-06 00:00:00,1.12576,1.12656,1.12574,1.12626,331 -2017-06-06 01:00:00,1.12624,1.12728,1.12624,1.12724,595 -2017-06-06 02:00:00,1.12728,1.12749,1.12705,1.12722,341 -2017-06-06 03:00:00,1.12724,1.12742,1.12684,1.12689,180 -2017-06-06 04:00:00,1.12686,1.12686,1.12652,1.12679,218 -2017-06-06 05:00:00,1.12682,1.12778,1.1266,1.12734,329 -2017-06-06 06:00:00,1.12732,1.12765,1.1266,1.12694,950 -2017-06-06 07:00:00,1.12692,1.12702,1.12424,1.12497,1424 -2017-06-06 08:00:00,1.125,1.1257,1.12476,1.12516,754 -2017-06-06 09:00:00,1.12518,1.12532,1.12442,1.12486,814 -2017-06-06 10:00:00,1.12488,1.12529,1.12438,1.12499,654 -2017-06-06 11:00:00,1.12496,1.12595,1.12404,1.12486,1297 -2017-06-06 12:00:00,1.12488,1.1258,1.12474,1.12552,1388 -2017-06-06 13:00:00,1.12554,1.12759,1.1254,1.12677,1530 -2017-06-06 14:00:00,1.1268,1.12766,1.12612,1.12658,1865 -2017-06-06 15:00:00,1.1266,1.1273,1.12626,1.12661,1043 -2017-06-06 16:00:00,1.12658,1.12718,1.12646,1.127,548 -2017-06-06 17:00:00,1.12703,1.12842,1.12701,1.12821,634 -2017-06-06 18:00:00,1.12819,1.12821,1.12681,1.12693,779 -2017-06-06 19:00:00,1.12696,1.12788,1.12696,1.12782,566 -2017-06-06 20:00:00,1.1278,1.12784,1.12722,1.12772,194 -2017-06-06 21:00:00,1.12769,1.1281,1.12766,1.12778,251 -2017-06-06 22:00:00,1.12776,1.1282,1.12774,1.12782,227 -2017-06-06 23:00:00,1.12784,1.12784,1.127,1.12703,158 -2017-06-07 00:00:00,1.127,1.12766,1.1268,1.12726,336 -2017-06-07 01:00:00,1.12724,1.12738,1.12678,1.12696,422 -2017-06-07 02:00:00,1.12694,1.12694,1.12622,1.12654,245 -2017-06-07 03:00:00,1.12652,1.12657,1.12625,1.12646,125 -2017-06-07 04:00:00,1.12644,1.12656,1.12602,1.12646,186 -2017-06-07 05:00:00,1.12644,1.12683,1.12642,1.12652,146 -2017-06-07 06:00:00,1.1265,1.12769,1.12632,1.12724,772 -2017-06-07 07:00:00,1.12726,1.12731,1.12464,1.1254,1452 -2017-06-07 08:00:00,1.12542,1.1268,1.12532,1.12624,796 -2017-06-07 09:00:00,1.12626,1.12769,1.12624,1.127,849 -2017-06-07 10:00:00,1.12703,1.12705,1.12052,1.12124,3547 -2017-06-07 11:00:00,1.12122,1.12272,1.12044,1.12159,1598 -2017-06-07 12:00:00,1.12156,1.12336,1.12134,1.12302,1313 -2017-06-07 13:00:00,1.123,1.12634,1.12248,1.12617,2929 -2017-06-07 14:00:00,1.1262,1.12824,1.12587,1.1263,2078 -2017-06-07 15:00:00,1.12628,1.12637,1.12302,1.12376,1543 -2017-06-07 16:00:00,1.12374,1.12656,1.1223,1.12649,1974 -2017-06-07 17:00:00,1.12647,1.12722,1.12628,1.12656,1026 -2017-06-07 18:00:00,1.12653,1.1268,1.12518,1.12536,1260 -2017-06-07 19:00:00,1.12534,1.12678,1.12518,1.12678,651 -2017-06-07 20:00:00,1.12676,1.1269,1.12564,1.12566,280 -2017-06-07 21:00:00,1.12609,1.1266,1.12556,1.12593,497 -2017-06-07 22:00:00,1.12596,1.12616,1.1255,1.12581,174 -2017-06-07 23:00:00,1.12584,1.12612,1.12548,1.12558,169 -2017-06-08 00:00:00,1.12556,1.12571,1.12479,1.12506,445 -2017-06-08 01:00:00,1.12504,1.12569,1.12472,1.12552,441 -2017-06-08 02:00:00,1.12554,1.12612,1.12536,1.12612,328 -2017-06-08 03:00:00,1.1261,1.1261,1.12534,1.12539,254 -2017-06-08 04:00:00,1.12536,1.12586,1.12504,1.12575,405 -2017-06-08 05:00:00,1.12573,1.12634,1.12524,1.12634,535 -2017-06-08 06:00:00,1.12632,1.12692,1.12508,1.12524,1035 -2017-06-08 07:00:00,1.12522,1.12648,1.12502,1.12596,1112 -2017-06-08 08:00:00,1.12599,1.12632,1.12432,1.12492,922 -2017-06-08 09:00:00,1.12489,1.12538,1.12301,1.12328,1131 -2017-06-08 10:00:00,1.12331,1.12375,1.12305,1.12347,788 -2017-06-08 11:00:00,1.12344,1.12632,1.12178,1.12247,3883 -2017-06-08 12:00:00,1.1225,1.12508,1.11948,1.12263,8353 -2017-06-08 13:00:00,1.12261,1.12299,1.12076,1.12187,3562 -2017-06-08 14:00:00,1.12189,1.12238,1.11958,1.12212,3352 -2017-06-08 15:00:00,1.12215,1.12243,1.12132,1.1217,1401 -2017-06-08 16:00:00,1.12167,1.12202,1.12076,1.12116,971 -2017-06-08 17:00:00,1.12113,1.12139,1.12017,1.12118,685 -2017-06-08 18:00:00,1.12116,1.12286,1.12089,1.12224,803 -2017-06-08 19:00:00,1.12222,1.12258,1.12097,1.12175,752 -2017-06-08 20:00:00,1.12172,1.12183,1.12128,1.12142,329 -2017-06-08 21:00:00,1.12137,1.12367,1.12,1.12052,3689 -2017-06-08 22:00:00,1.1205,1.12143,1.12024,1.12034,887 -2017-06-08 23:00:00,1.12036,1.12036,1.11801,1.11886,1067 -2017-06-09 00:00:00,1.11888,1.11948,1.11794,1.11824,1416 -2017-06-09 01:00:00,1.11822,1.12012,1.11808,1.1199,753 -2017-06-09 02:00:00,1.11993,1.12004,1.11906,1.11959,644 -2017-06-09 03:00:00,1.11962,1.12064,1.11918,1.12004,666 -2017-06-09 04:00:00,1.12002,1.12146,1.1199,1.1204,572 -2017-06-09 05:00:00,1.12038,1.12135,1.12014,1.12038,1107 -2017-06-09 06:00:00,1.1204,1.12158,1.11865,1.11892,3068 -2017-06-09 07:00:00,1.11894,1.11991,1.11854,1.11898,2326 -2017-06-09 08:00:00,1.119,1.11934,1.11698,1.11761,2773 -2017-06-09 09:00:00,1.11763,1.11874,1.1173,1.1173,1231 -2017-06-09 10:00:00,1.11733,1.11851,1.11733,1.11809,1152 -2017-06-09 11:00:00,1.11807,1.11834,1.1175,1.11796,851 -2017-06-09 12:00:00,1.11798,1.11806,1.1167,1.11688,1387 -2017-06-09 13:00:00,1.1169,1.11814,1.11664,1.11744,1309 -2017-06-09 14:00:00,1.11746,1.1189,1.11743,1.11834,1090 -2017-06-09 15:00:00,1.11837,1.11928,1.11826,1.11892,855 -2017-06-09 16:00:00,1.11894,1.12008,1.11873,1.11978,795 -2017-06-09 17:00:00,1.1198,1.1204,1.1194,1.11943,684 -2017-06-09 18:00:00,1.11946,1.11992,1.1191,1.11964,645 -2017-06-09 19:00:00,1.11962,1.11996,1.11926,1.11954,776 -2017-06-09 20:00:00,1.1195,1.11978,1.1194,1.11959,332 -2017-06-11 21:00:00,1.12088,1.12088,1.12049,1.1205,105 -2017-06-11 22:00:00,1.12052,1.12095,1.12026,1.1204,258 -2017-06-11 23:00:00,1.12042,1.1206,1.11974,1.1202,279 -2017-06-12 00:00:00,1.12018,1.1208,1.11994,1.1205,494 -2017-06-12 01:00:00,1.12052,1.12077,1.11978,1.11978,334 -2017-06-12 02:00:00,1.1198,1.12118,1.1198,1.12102,399 -2017-06-12 03:00:00,1.12104,1.12104,1.12041,1.12067,325 -2017-06-12 04:00:00,1.1207,1.12086,1.12023,1.12064,113 -2017-06-12 05:00:00,1.12067,1.12167,1.12065,1.12126,264 -2017-06-12 06:00:00,1.12124,1.12166,1.1209,1.1211,680 -2017-06-12 07:00:00,1.12113,1.12237,1.12044,1.12212,929 -2017-06-12 08:00:00,1.12214,1.12276,1.12152,1.12254,1011 -2017-06-12 09:00:00,1.12257,1.12262,1.12158,1.12166,837 -2017-06-12 10:00:00,1.12169,1.12264,1.12082,1.12164,1195 -2017-06-12 11:00:00,1.12167,1.1232,1.12144,1.12192,814 -2017-06-12 12:00:00,1.1219,1.1225,1.12136,1.12148,994 -2017-06-12 13:00:00,1.1215,1.12201,1.12033,1.12086,1133 -2017-06-12 14:00:00,1.12084,1.12104,1.1192,1.1203,1463 -2017-06-12 15:00:00,1.12032,1.12052,1.11972,1.12032,1172 -2017-06-12 16:00:00,1.1203,1.12051,1.11966,1.11981,613 -2017-06-12 17:00:00,1.11984,1.12067,1.1196,1.12039,831 -2017-06-12 18:00:00,1.12042,1.12086,1.11988,1.1208,527 -2017-06-12 19:00:00,1.12083,1.121,1.1201,1.12047,461 -2017-06-12 20:00:00,1.12049,1.12081,1.12015,1.12036,339 -2017-06-12 21:00:00,1.12038,1.12074,1.12028,1.12058,488 -2017-06-12 22:00:00,1.1206,1.1206,1.12011,1.12019,251 -2017-06-12 23:00:00,1.12017,1.12021,1.11956,1.11976,267 -2017-06-13 00:00:00,1.11974,1.1201,1.11937,1.11947,344 -2017-06-13 01:00:00,1.11944,1.11962,1.11902,1.11925,422 -2017-06-13 02:00:00,1.11923,1.11988,1.11914,1.11964,214 -2017-06-13 03:00:00,1.11966,1.11966,1.11893,1.11903,232 -2017-06-13 04:00:00,1.11905,1.11937,1.11903,1.1193,108 -2017-06-13 05:00:00,1.11932,1.11936,1.11854,1.11876,260 -2017-06-13 06:00:00,1.11874,1.11985,1.11855,1.11942,810 -2017-06-13 07:00:00,1.11944,1.12182,1.119,1.12174,1587 -2017-06-13 08:00:00,1.12172,1.1225,1.1209,1.12124,1245 -2017-06-13 09:00:00,1.12127,1.12172,1.12041,1.12075,678 -2017-06-13 10:00:00,1.12078,1.12121,1.12008,1.12066,621 -2017-06-13 11:00:00,1.12068,1.12204,1.12022,1.12178,679 -2017-06-13 12:00:00,1.1218,1.12202,1.12066,1.12072,1064 -2017-06-13 13:00:00,1.12076,1.1211,1.1201,1.12079,1022 -2017-06-13 14:00:00,1.12081,1.12186,1.12061,1.12064,1224 -2017-06-13 15:00:00,1.12067,1.12116,1.11924,1.11932,1048 -2017-06-13 16:00:00,1.11934,1.1203,1.11922,1.12018,538 -2017-06-13 17:00:00,1.1202,1.1207,1.12017,1.12022,510 -2017-06-13 18:00:00,1.12024,1.12127,1.12022,1.12114,366 -2017-06-13 19:00:00,1.12112,1.12116,1.12065,1.1207,236 -2017-06-13 20:00:00,1.12073,1.12116,1.12066,1.12105,211 -2017-06-13 21:00:00,1.1207,1.12152,1.12068,1.12087,325 -2017-06-13 22:00:00,1.1209,1.12116,1.12067,1.12086,170 -2017-06-13 23:00:00,1.12083,1.12111,1.12072,1.12093,105 -2017-06-14 00:00:00,1.12091,1.12154,1.12072,1.12138,357 -2017-06-14 01:00:00,1.12136,1.12176,1.12124,1.12156,323 -2017-06-14 02:00:00,1.12159,1.12198,1.12116,1.12124,457 -2017-06-14 03:00:00,1.12126,1.1217,1.12126,1.12152,188 -2017-06-14 04:00:00,1.12154,1.1216,1.12128,1.12151,110 -2017-06-14 05:00:00,1.12154,1.12194,1.12148,1.12194,157 -2017-06-14 06:00:00,1.12191,1.12252,1.12125,1.12215,1187 -2017-06-14 07:00:00,1.12213,1.12213,1.1208,1.1209,1112 -2017-06-14 08:00:00,1.12088,1.12156,1.12054,1.12073,936 -2017-06-14 09:00:00,1.12076,1.12154,1.12029,1.12062,1048 -2017-06-14 10:00:00,1.1206,1.12081,1.12015,1.12046,524 -2017-06-14 11:00:00,1.12048,1.12076,1.11978,1.12014,713 -2017-06-14 12:00:00,1.12016,1.12676,1.11993,1.1263,3788 -2017-06-14 13:00:00,1.12626,1.12788,1.12622,1.12719,3552 -2017-06-14 14:00:00,1.12716,1.12958,1.12702,1.12793,3141 -2017-06-14 15:00:00,1.12796,1.12858,1.12724,1.12766,1592 -2017-06-14 16:00:00,1.12768,1.12796,1.12658,1.1273,795 -2017-06-14 17:00:00,1.12732,1.12746,1.1263,1.1271,976 -2017-06-14 18:00:00,1.12704,1.12892,1.12077,1.12154,10454 -2017-06-14 19:00:00,1.12156,1.12234,1.11932,1.12184,4215 -2017-06-14 20:00:00,1.12182,1.12232,1.12142,1.12182,502 -2017-06-14 21:00:00,1.12179,1.12208,1.12156,1.12177,261 -2017-06-14 22:00:00,1.12174,1.12186,1.12056,1.121,535 -2017-06-14 23:00:00,1.12102,1.12162,1.12096,1.1213,280 -2017-06-15 00:00:00,1.12132,1.12221,1.12099,1.12185,692 -2017-06-15 01:00:00,1.12182,1.12285,1.12173,1.122,687 -2017-06-15 02:00:00,1.12202,1.1224,1.12166,1.12167,313 -2017-06-15 03:00:00,1.12164,1.12237,1.12152,1.12232,372 -2017-06-15 04:00:00,1.1223,1.12242,1.12201,1.12215,220 -2017-06-15 05:00:00,1.12212,1.12219,1.12144,1.12181,330 -2017-06-15 06:00:00,1.12179,1.12203,1.12057,1.12124,1128 -2017-06-15 07:00:00,1.12121,1.12124,1.11795,1.1194,2701 -2017-06-15 08:00:00,1.11938,1.1194,1.11754,1.11798,1694 -2017-06-15 09:00:00,1.11796,1.11851,1.1156,1.11602,1830 -2017-06-15 10:00:00,1.11605,1.11696,1.11585,1.11664,1154 -2017-06-15 11:00:00,1.11662,1.11721,1.11536,1.11626,2317 -2017-06-15 12:00:00,1.11624,1.11688,1.11494,1.1152,2409 -2017-06-15 13:00:00,1.11518,1.11554,1.11434,1.1148,2561 -2017-06-15 14:00:00,1.11478,1.11522,1.11323,1.11487,2441 -2017-06-15 15:00:00,1.1149,1.1158,1.11488,1.11512,1216 -2017-06-15 16:00:00,1.11515,1.11515,1.11396,1.11483,735 -2017-06-15 17:00:00,1.11481,1.11502,1.11422,1.1143,517 -2017-06-15 18:00:00,1.11432,1.11548,1.11429,1.1154,349 -2017-06-15 19:00:00,1.11538,1.11579,1.11442,1.11455,665 -2017-06-15 20:00:00,1.11452,1.11504,1.11424,1.11452,510 -2017-06-15 21:00:00,1.11466,1.1151,1.1144,1.11473,389 -2017-06-15 22:00:00,1.1147,1.11508,1.11452,1.11464,203 -2017-06-15 23:00:00,1.11467,1.11496,1.11449,1.11489,131 -2017-06-16 00:00:00,1.11491,1.11556,1.11453,1.1154,431 -2017-06-16 01:00:00,1.11538,1.11553,1.11515,1.11533,216 -2017-06-16 02:00:00,1.1153,1.11534,1.11458,1.1151,299 -2017-06-16 03:00:00,1.11506,1.11506,1.11462,1.11462,264 -2017-06-16 04:00:00,1.1146,1.11466,1.11418,1.11442,242 -2017-06-16 05:00:00,1.1144,1.11462,1.11386,1.11424,295 -2017-06-16 06:00:00,1.11426,1.1159,1.11396,1.11539,1172 -2017-06-16 07:00:00,1.11537,1.11672,1.11516,1.1167,1064 -2017-06-16 08:00:00,1.11672,1.1175,1.11651,1.11728,976 -2017-06-16 09:00:00,1.11726,1.11838,1.11698,1.117,909 -2017-06-16 10:00:00,1.11703,1.11816,1.11703,1.11778,703 -2017-06-16 11:00:00,1.1178,1.1181,1.11574,1.11599,1018 -2017-06-16 12:00:00,1.11602,1.11831,1.11602,1.11724,1219 -2017-06-16 13:00:00,1.11726,1.1177,1.11654,1.11764,1307 -2017-06-16 14:00:00,1.11767,1.12,1.11742,1.11988,1844 -2017-06-16 15:00:00,1.11986,1.11999,1.1187,1.11934,1000 -2017-06-16 16:00:00,1.11931,1.11933,1.11862,1.11887,610 -2017-06-16 17:00:00,1.11884,1.11954,1.11876,1.11954,440 -2017-06-16 18:00:00,1.11957,1.11992,1.1193,1.11937,387 -2017-06-16 19:00:00,1.11939,1.12014,1.11937,1.12005,348 -2017-06-16 20:00:00,1.12007,1.12018,1.11928,1.11966,418 -2017-06-18 21:00:00,1.12078,1.12103,1.11992,1.11992,244 -2017-06-18 22:00:00,1.11995,1.12043,1.1196,1.12038,298 -2017-06-18 23:00:00,1.1204,1.12066,1.12015,1.1204,168 -2017-06-19 00:00:00,1.12038,1.12051,1.11896,1.11907,407 -2017-06-19 01:00:00,1.1191,1.11995,1.11902,1.11976,331 -2017-06-19 02:00:00,1.11974,1.12002,1.11956,1.11972,165 -2017-06-19 03:00:00,1.11974,1.1199,1.11952,1.11976,123 -2017-06-19 04:00:00,1.11974,1.11987,1.11936,1.11936,155 -2017-06-19 05:00:00,1.11938,1.11965,1.11928,1.1193,166 -2017-06-19 06:00:00,1.11928,1.12075,1.11906,1.12046,831 -2017-06-19 07:00:00,1.12044,1.12044,1.11824,1.11945,1150 -2017-06-19 08:00:00,1.11942,1.1198,1.11908,1.11953,711 -2017-06-19 09:00:00,1.11951,1.12016,1.1188,1.11926,669 -2017-06-19 10:00:00,1.11923,1.12066,1.11918,1.12065,605 -2017-06-19 11:00:00,1.12067,1.12127,1.11908,1.11911,1094 -2017-06-19 12:00:00,1.11908,1.11996,1.11771,1.1182,1800 -2017-06-19 13:00:00,1.11823,1.11846,1.1173,1.11768,1385 -2017-06-19 14:00:00,1.1177,1.11797,1.11656,1.11661,1178 -2017-06-19 15:00:00,1.11664,1.11712,1.1159,1.116,1022 -2017-06-19 16:00:00,1.11598,1.11635,1.11558,1.11588,561 -2017-06-19 17:00:00,1.11591,1.11598,1.11472,1.11517,531 -2017-06-19 18:00:00,1.11514,1.11536,1.11432,1.11485,512 -2017-06-19 19:00:00,1.11488,1.11494,1.11454,1.11486,303 -2017-06-19 20:00:00,1.11484,1.11504,1.11474,1.11481,141 -2017-06-19 21:00:00,1.1149,1.11544,1.11476,1.11499,447 -2017-06-19 22:00:00,1.11496,1.11531,1.11469,1.11519,407 -2017-06-19 23:00:00,1.11516,1.11518,1.11412,1.11446,274 -2017-06-20 00:00:00,1.11443,1.11492,1.11436,1.11449,399 -2017-06-20 01:00:00,1.11451,1.11561,1.11451,1.11553,341 -2017-06-20 02:00:00,1.11556,1.1158,1.11536,1.11564,232 -2017-06-20 03:00:00,1.11562,1.11586,1.11536,1.11562,196 -2017-06-20 04:00:00,1.11559,1.11562,1.11534,1.11556,141 -2017-06-20 05:00:00,1.11558,1.11602,1.11539,1.1159,235 -2017-06-20 06:00:00,1.11588,1.11649,1.11519,1.11526,632 -2017-06-20 07:00:00,1.11529,1.11627,1.11427,1.11622,1739 -2017-06-20 08:00:00,1.1162,1.11622,1.115,1.11583,917 -2017-06-20 09:00:00,1.1158,1.11599,1.11519,1.11597,608 -2017-06-20 10:00:00,1.11599,1.11648,1.11522,1.11528,750 -2017-06-20 11:00:00,1.1153,1.11532,1.11414,1.11482,903 -2017-06-20 12:00:00,1.11485,1.11627,1.11485,1.11508,1635 -2017-06-20 13:00:00,1.1151,1.11536,1.11344,1.11364,1562 -2017-06-20 14:00:00,1.11361,1.11456,1.11258,1.11266,1685 -2017-06-20 15:00:00,1.11264,1.11278,1.11198,1.11238,1084 -2017-06-20 16:00:00,1.11236,1.11286,1.11191,1.11246,642 -2017-06-20 17:00:00,1.11248,1.11264,1.11203,1.1125,428 -2017-06-20 18:00:00,1.11253,1.11314,1.11236,1.11286,447 -2017-06-20 19:00:00,1.11284,1.11326,1.11255,1.11258,544 -2017-06-20 20:00:00,1.1126,1.11344,1.11258,1.11342,199 -2017-06-20 21:00:00,1.11339,1.1135,1.11314,1.11344,198 -2017-06-20 22:00:00,1.11346,1.11356,1.11322,1.1135,207 -2017-06-20 23:00:00,1.11352,1.1137,1.11336,1.11366,119 -2017-06-21 00:00:00,1.11364,1.11368,1.11329,1.11355,302 -2017-06-21 01:00:00,1.11358,1.11366,1.11336,1.11345,133 -2017-06-21 02:00:00,1.11348,1.11362,1.11339,1.11346,87 -2017-06-21 03:00:00,1.11349,1.11382,1.1134,1.11362,115 -2017-06-21 04:00:00,1.11359,1.11372,1.11328,1.11336,101 -2017-06-21 05:00:00,1.11338,1.11346,1.11284,1.11302,195 -2017-06-21 06:00:00,1.113,1.11366,1.11286,1.11314,649 -2017-06-21 07:00:00,1.11312,1.11369,1.11296,1.11319,841 -2017-06-21 08:00:00,1.11322,1.11457,1.11274,1.11428,1062 -2017-06-21 09:00:00,1.11426,1.115,1.11376,1.11446,1110 -2017-06-21 10:00:00,1.11444,1.115,1.11416,1.11495,844 -2017-06-21 11:00:00,1.11497,1.11559,1.11398,1.11417,1601 -2017-06-21 12:00:00,1.11415,1.1153,1.11404,1.11478,1137 -2017-06-21 13:00:00,1.1148,1.11485,1.11302,1.11396,1136 -2017-06-21 14:00:00,1.11393,1.11478,1.11348,1.1142,1511 -2017-06-21 15:00:00,1.11422,1.11474,1.11384,1.11428,940 -2017-06-21 16:00:00,1.11426,1.11475,1.11409,1.11472,661 -2017-06-21 17:00:00,1.11474,1.11528,1.11448,1.11512,599 -2017-06-21 18:00:00,1.1151,1.11664,1.11503,1.11626,624 -2017-06-21 19:00:00,1.11628,1.11684,1.11618,1.11658,448 -2017-06-21 20:00:00,1.11656,1.1169,1.11622,1.11684,238 -2017-06-21 21:00:00,1.1168,1.1169,1.11639,1.1168,363 -2017-06-21 22:00:00,1.11678,1.11682,1.11654,1.1167,106 -2017-06-21 23:00:00,1.11668,1.11684,1.11648,1.11668,152 -2017-06-22 00:00:00,1.11665,1.11712,1.11604,1.11632,402 -2017-06-22 01:00:00,1.11634,1.11666,1.11624,1.11654,319 -2017-06-22 02:00:00,1.11652,1.11717,1.11644,1.11678,253 -2017-06-22 03:00:00,1.11676,1.11707,1.11675,1.11684,286 -2017-06-22 04:00:00,1.11687,1.11716,1.11678,1.1171,180 -2017-06-22 05:00:00,1.11708,1.11762,1.11687,1.11762,315 -2017-06-22 06:00:00,1.1176,1.11779,1.11682,1.11718,673 -2017-06-22 07:00:00,1.1172,1.1172,1.11546,1.11624,1048 -2017-06-22 08:00:00,1.11622,1.11688,1.11582,1.11681,941 -2017-06-22 09:00:00,1.11684,1.11744,1.11649,1.11652,700 -2017-06-22 10:00:00,1.1165,1.11676,1.11605,1.11656,604 -2017-06-22 11:00:00,1.11653,1.11666,1.1157,1.11655,663 -2017-06-22 12:00:00,1.11653,1.11724,1.11591,1.1161,1082 -2017-06-22 13:00:00,1.11608,1.11641,1.11526,1.11601,1202 -2017-06-22 14:00:00,1.11598,1.11626,1.11508,1.11568,1598 -2017-06-22 15:00:00,1.1157,1.11611,1.11454,1.11469,1061 -2017-06-22 16:00:00,1.11471,1.11561,1.11471,1.11556,482 -2017-06-22 17:00:00,1.11553,1.11575,1.11395,1.11433,632 -2017-06-22 18:00:00,1.1143,1.11504,1.11416,1.11469,350 -2017-06-22 19:00:00,1.11466,1.1155,1.11466,1.11515,425 -2017-06-22 20:00:00,1.11512,1.1154,1.11492,1.11513,107 -2017-06-22 21:00:00,1.11526,1.11536,1.11514,1.11516,71 -2017-06-22 22:00:00,1.11514,1.11523,1.11496,1.11498,93 -2017-06-22 23:00:00,1.115,1.11508,1.11474,1.11498,73 -2017-06-23 00:00:00,1.11496,1.11514,1.11454,1.11495,278 -2017-06-23 01:00:00,1.11497,1.11599,1.1147,1.11599,356 -2017-06-23 02:00:00,1.11597,1.116,1.11547,1.11587,147 -2017-06-23 03:00:00,1.1159,1.11632,1.11578,1.1163,175 -2017-06-23 04:00:00,1.11627,1.1164,1.11614,1.11617,102 -2017-06-23 05:00:00,1.11619,1.11684,1.11619,1.11639,181 -2017-06-23 06:00:00,1.11641,1.11752,1.11637,1.11725,652 -2017-06-23 07:00:00,1.11722,1.118,1.11688,1.11759,1197 -2017-06-23 08:00:00,1.11761,1.11879,1.11712,1.11716,1043 -2017-06-23 09:00:00,1.11714,1.11722,1.11618,1.11704,680 -2017-06-23 10:00:00,1.11707,1.11762,1.11648,1.11666,618 -2017-06-23 11:00:00,1.11664,1.11744,1.11624,1.11732,653 -2017-06-23 12:00:00,1.1173,1.11802,1.11705,1.11761,929 -2017-06-23 13:00:00,1.11763,1.1196,1.11752,1.1196,869 -2017-06-23 14:00:00,1.11958,1.12088,1.11856,1.11998,1579 -2017-06-23 15:00:00,1.12001,1.12038,1.11961,1.11964,677 -2017-06-23 16:00:00,1.11966,1.11995,1.11929,1.11971,317 -2017-06-23 17:00:00,1.11973,1.11992,1.11951,1.1198,365 -2017-06-23 18:00:00,1.11978,1.12024,1.11969,1.11969,324 -2017-06-23 19:00:00,1.11971,1.11994,1.11958,1.11972,218 -2017-06-23 20:00:00,1.11974,1.11982,1.11926,1.11938,181 -2017-06-25 21:00:00,1.12,1.12,1.1191,1.11943,196 -2017-06-25 22:00:00,1.1194,1.11988,1.11935,1.11967,270 -2017-06-25 23:00:00,1.1197,1.11998,1.11958,1.11998,77 -2017-06-26 00:00:00,1.11996,1.12002,1.11953,1.11966,322 -2017-06-26 01:00:00,1.11964,1.11968,1.119,1.11902,437 -2017-06-26 02:00:00,1.11904,1.1197,1.11904,1.11951,280 -2017-06-26 03:00:00,1.11949,1.11978,1.11901,1.11966,263 -2017-06-26 04:00:00,1.11964,1.11964,1.11904,1.11917,128 -2017-06-26 05:00:00,1.11915,1.11936,1.11888,1.11926,169 -2017-06-26 06:00:00,1.11924,1.11951,1.11848,1.1192,651 -2017-06-26 07:00:00,1.11917,1.12078,1.11902,1.1201,1250 -2017-06-26 08:00:00,1.12008,1.12018,1.1182,1.11858,1476 -2017-06-26 09:00:00,1.11856,1.11872,1.11759,1.11772,900 -2017-06-26 10:00:00,1.1177,1.11872,1.11766,1.11798,946 -2017-06-26 11:00:00,1.11796,1.1185,1.1172,1.11816,844 -2017-06-26 12:00:00,1.11819,1.12197,1.11819,1.12112,1933 -2017-06-26 13:00:00,1.12114,1.12158,1.12028,1.12028,1308 -2017-06-26 14:00:00,1.12031,1.12186,1.12,1.12029,1322 -2017-06-26 15:00:00,1.12032,1.12048,1.1189,1.11962,1177 -2017-06-26 16:00:00,1.11964,1.1198,1.11821,1.11876,703 -2017-06-26 17:00:00,1.11872,1.11946,1.11872,1.11914,438 -2017-06-26 18:00:00,1.11917,1.11944,1.11756,1.11811,688 -2017-06-26 19:00:00,1.11814,1.11818,1.11773,1.11804,330 -2017-06-26 20:00:00,1.11802,1.11834,1.11796,1.11817,188 -2017-06-26 21:00:00,1.11828,1.11857,1.11814,1.1183,243 -2017-06-26 22:00:00,1.11832,1.11838,1.11804,1.11806,105 -2017-06-26 23:00:00,1.11808,1.11836,1.11791,1.1183,92 -2017-06-27 00:00:00,1.11828,1.11854,1.11802,1.11842,289 -2017-06-27 01:00:00,1.1184,1.11868,1.11811,1.11827,222 -2017-06-27 02:00:00,1.1183,1.11896,1.11808,1.11878,214 -2017-06-27 03:00:00,1.11875,1.11926,1.11872,1.11911,230 -2017-06-27 04:00:00,1.11908,1.11911,1.11881,1.11902,95 -2017-06-27 05:00:00,1.11904,1.11966,1.11902,1.11958,179 -2017-06-27 06:00:00,1.11956,1.1204,1.11883,1.11911,999 -2017-06-27 07:00:00,1.11909,1.1193,1.11824,1.11872,1074 -2017-06-27 08:00:00,1.11874,1.12548,1.1187,1.12491,4961 -2017-06-27 09:00:00,1.12493,1.12652,1.12442,1.12544,1449 -2017-06-27 10:00:00,1.12541,1.1266,1.12468,1.1262,1252 -2017-06-27 11:00:00,1.12618,1.12748,1.12606,1.12688,1270 -2017-06-27 12:00:00,1.12692,1.12841,1.12689,1.12772,1207 -2017-06-27 13:00:00,1.12774,1.1305,1.12772,1.12884,1893 -2017-06-27 14:00:00,1.12882,1.12898,1.12746,1.12862,1468 -2017-06-27 15:00:00,1.12864,1.13321,1.1284,1.13268,2137 -2017-06-27 16:00:00,1.13264,1.13351,1.13064,1.13118,1948 -2017-06-27 17:00:00,1.1312,1.13379,1.13066,1.13324,2325 -2017-06-27 18:00:00,1.13322,1.13478,1.13316,1.13464,1176 -2017-06-27 19:00:00,1.13462,1.13494,1.13442,1.13488,594 -2017-06-27 20:00:00,1.13485,1.13485,1.13367,1.13388,370 -2017-06-27 21:00:00,1.13384,1.13396,1.13301,1.13351,541 -2017-06-27 22:00:00,1.13354,1.13447,1.13354,1.13432,347 -2017-06-27 23:00:00,1.1343,1.13432,1.13359,1.1337,252 -2017-06-28 00:00:00,1.13368,1.13438,1.1336,1.134,543 -2017-06-28 01:00:00,1.13398,1.13556,1.13372,1.13514,588 -2017-06-28 02:00:00,1.13511,1.13539,1.13469,1.13514,454 -2017-06-28 03:00:00,1.13517,1.13517,1.13476,1.13488,248 -2017-06-28 04:00:00,1.1349,1.13533,1.13466,1.13468,244 -2017-06-28 05:00:00,1.13466,1.13664,1.13454,1.13629,681 -2017-06-28 06:00:00,1.13626,1.13788,1.13526,1.13532,2344 -2017-06-28 07:00:00,1.13534,1.13882,1.13522,1.13784,3222 -2017-06-28 08:00:00,1.13782,1.13864,1.13602,1.13604,2239 -2017-06-28 09:00:00,1.13606,1.1364,1.13536,1.13609,1609 -2017-06-28 10:00:00,1.13606,1.13718,1.13554,1.13586,1006 -2017-06-28 11:00:00,1.13589,1.13764,1.13559,1.13749,1336 -2017-06-28 12:00:00,1.13746,1.13802,1.12918,1.13315,8864 -2017-06-28 13:00:00,1.13318,1.13736,1.13283,1.1366,5895 -2017-06-28 14:00:00,1.13662,1.13908,1.13616,1.13631,4286 -2017-06-28 15:00:00,1.13633,1.1366,1.13494,1.13648,2174 -2017-06-28 16:00:00,1.13646,1.13816,1.13631,1.1378,900 -2017-06-28 17:00:00,1.13784,1.13818,1.13736,1.13768,660 -2017-06-28 18:00:00,1.1377,1.1384,1.13763,1.138,668 -2017-06-28 19:00:00,1.13802,1.13852,1.13762,1.13819,476 -2017-06-28 20:00:00,1.13816,1.13816,1.1376,1.13772,300 -2017-06-28 21:00:00,1.1379,1.13806,1.13756,1.1376,371 -2017-06-28 22:00:00,1.13758,1.13798,1.13746,1.13776,272 -2017-06-28 23:00:00,1.13778,1.13853,1.13774,1.13784,210 -2017-06-29 00:00:00,1.13781,1.13894,1.13768,1.13874,601 -2017-06-29 01:00:00,1.13871,1.14085,1.13852,1.14056,686 -2017-06-29 02:00:00,1.14052,1.14194,1.14032,1.14053,853 -2017-06-29 03:00:00,1.14056,1.141,1.14016,1.14059,423 -2017-06-29 04:00:00,1.14057,1.14078,1.1395,1.14018,423 -2017-06-29 05:00:00,1.14016,1.1408,1.13954,1.14076,400 -2017-06-29 06:00:00,1.14073,1.14152,1.14,1.14061,1718 -2017-06-29 07:00:00,1.14064,1.14324,1.14064,1.14268,3382 -2017-06-29 08:00:00,1.14266,1.14349,1.14153,1.14256,1833 -2017-06-29 09:00:00,1.14254,1.14263,1.13983,1.14138,1479 -2017-06-29 10:00:00,1.1414,1.1416,1.13999,1.14062,1260 -2017-06-29 11:00:00,1.14064,1.14076,1.13923,1.14066,1461 -2017-06-29 12:00:00,1.14068,1.14175,1.13882,1.1401,2759 -2017-06-29 13:00:00,1.14008,1.14158,1.13955,1.13998,2106 -2017-06-29 14:00:00,1.14,1.14281,1.13994,1.14242,2164 -2017-06-29 15:00:00,1.14244,1.1432,1.14201,1.14208,1592 -2017-06-29 16:00:00,1.14206,1.14314,1.14166,1.14298,998 -2017-06-29 17:00:00,1.14296,1.14448,1.14278,1.14422,1101 -2017-06-29 18:00:00,1.14425,1.14452,1.14296,1.14328,880 -2017-06-29 19:00:00,1.14326,1.14454,1.1432,1.14392,652 -2017-06-29 20:00:00,1.14394,1.14427,1.14356,1.14406,233 -2017-06-29 21:00:00,1.1441,1.14434,1.14389,1.14404,237 -2017-06-29 22:00:00,1.14407,1.14454,1.14407,1.14428,313 -2017-06-29 23:00:00,1.14426,1.14429,1.14396,1.14396,117 -2017-06-30 00:00:00,1.14394,1.1443,1.14269,1.14286,794 -2017-06-30 01:00:00,1.14284,1.14442,1.1428,1.1441,725 -2017-06-30 02:00:00,1.14412,1.14444,1.14356,1.1436,598 -2017-06-30 03:00:00,1.14358,1.14432,1.14358,1.14406,268 -2017-06-30 04:00:00,1.14404,1.14427,1.14376,1.14404,187 -2017-06-30 05:00:00,1.14408,1.14414,1.14277,1.14302,455 -2017-06-30 06:00:00,1.143,1.14412,1.14227,1.14232,1475 -2017-06-30 07:00:00,1.14234,1.14298,1.14022,1.1412,2908 -2017-06-30 08:00:00,1.14122,1.14156,1.13958,1.14034,2058 -2017-06-30 09:00:00,1.14036,1.14102,1.13923,1.14096,2271 -2017-06-30 10:00:00,1.14098,1.14117,1.13988,1.14028,1271 -2017-06-30 11:00:00,1.14026,1.14128,1.14026,1.1404,1173 -2017-06-30 12:00:00,1.14042,1.14212,1.1404,1.1413,2213 -2017-06-30 13:00:00,1.14127,1.14235,1.1412,1.14196,1814 -2017-06-30 14:00:00,1.14198,1.14276,1.13957,1.14042,2560 -2017-06-30 15:00:00,1.14046,1.14166,1.14042,1.14113,1406 -2017-06-30 16:00:00,1.14111,1.14163,1.14065,1.14127,770 -2017-06-30 17:00:00,1.14125,1.14171,1.1411,1.14147,416 -2017-06-30 18:00:00,1.14149,1.14228,1.14086,1.14196,577 -2017-06-30 19:00:00,1.14194,1.14232,1.14152,1.14216,610 -2017-06-30 20:00:00,1.14213,1.14252,1.14184,1.14252,313 -2017-07-02 21:00:00,1.14186,1.1422,1.1417,1.14218,127 -2017-07-02 22:00:00,1.1422,1.1427,1.14208,1.14254,245 -2017-07-02 23:00:00,1.14251,1.14257,1.14212,1.14232,188 -2017-07-03 00:00:00,1.14235,1.14248,1.1416,1.14173,410 -2017-07-03 01:00:00,1.14175,1.14202,1.14148,1.14164,304 -2017-07-03 02:00:00,1.14166,1.14199,1.14124,1.14138,327 -2017-07-03 03:00:00,1.14141,1.1417,1.14042,1.14043,413 -2017-07-03 04:00:00,1.14046,1.14156,1.1404,1.14133,248 -2017-07-03 05:00:00,1.1413,1.14152,1.14078,1.14079,353 -2017-07-03 06:00:00,1.14076,1.14142,1.14036,1.14118,1232 -2017-07-03 07:00:00,1.14115,1.14115,1.13926,1.13949,1748 -2017-07-03 08:00:00,1.13946,1.13949,1.13773,1.13793,1487 -2017-07-03 09:00:00,1.1379,1.13858,1.1373,1.13733,1032 -2017-07-03 10:00:00,1.1373,1.13793,1.13707,1.1375,942 -2017-07-03 11:00:00,1.13752,1.13775,1.13616,1.13646,1078 -2017-07-03 12:00:00,1.13648,1.13756,1.1362,1.13678,1197 -2017-07-03 13:00:00,1.1368,1.1373,1.13581,1.13717,1338 -2017-07-03 14:00:00,1.13714,1.13736,1.13594,1.1368,2252 -2017-07-03 15:00:00,1.13682,1.13697,1.13562,1.13668,1167 -2017-07-03 16:00:00,1.13666,1.1372,1.13551,1.13573,926 -2017-07-03 17:00:00,1.13571,1.13686,1.13566,1.13613,298 -2017-07-03 18:00:00,1.13611,1.13611,1.13568,1.13582,111 -2017-07-03 19:00:00,1.13585,1.1363,1.13578,1.1363,100 -2017-07-03 20:00:00,1.13628,1.13669,1.13624,1.1364,176 -2017-07-03 21:00:00,1.13636,1.13658,1.1358,1.13634,401 -2017-07-03 22:00:00,1.13636,1.1371,1.13634,1.13672,196 -2017-07-03 23:00:00,1.13674,1.13735,1.13672,1.13726,143 -2017-07-04 00:00:00,1.13724,1.1377,1.13709,1.1374,379 -2017-07-04 01:00:00,1.13742,1.13742,1.13674,1.1369,340 -2017-07-04 02:00:00,1.13692,1.13702,1.13638,1.1366,231 -2017-07-04 03:00:00,1.13658,1.1374,1.13656,1.13728,195 -2017-07-04 04:00:00,1.13724,1.13742,1.13689,1.13722,355 -2017-07-04 05:00:00,1.13724,1.13726,1.13362,1.13484,1064 -2017-07-04 06:00:00,1.13486,1.13726,1.13436,1.13724,1569 -2017-07-04 07:00:00,1.13722,1.13744,1.13564,1.13616,1712 -2017-07-04 08:00:00,1.13619,1.13636,1.13472,1.13539,1076 -2017-07-04 09:00:00,1.13542,1.13544,1.13425,1.13498,792 -2017-07-04 10:00:00,1.13496,1.13528,1.13468,1.13517,500 -2017-07-04 11:00:00,1.13515,1.13515,1.1342,1.13506,527 -2017-07-04 12:00:00,1.13503,1.13554,1.13401,1.13428,846 -2017-07-04 13:00:00,1.13431,1.13479,1.13384,1.13446,748 -2017-07-04 14:00:00,1.13444,1.13542,1.13416,1.13517,694 -2017-07-04 15:00:00,1.13519,1.13528,1.13455,1.13475,624 -2017-07-04 16:00:00,1.13477,1.1352,1.13434,1.13512,329 -2017-07-04 17:00:00,1.1351,1.13534,1.13466,1.13514,440 -2017-07-04 18:00:00,1.13512,1.1353,1.13477,1.13505,323 -2017-07-04 19:00:00,1.13503,1.13511,1.13458,1.13463,216 -2017-07-04 20:00:00,1.13465,1.13496,1.1344,1.1346,350 -2017-07-04 21:00:00,1.13452,1.13494,1.13443,1.13474,347 -2017-07-04 22:00:00,1.13472,1.13556,1.13452,1.13534,200 -2017-07-04 23:00:00,1.13536,1.13611,1.13517,1.13594,234 -2017-07-05 00:00:00,1.13592,1.13644,1.13546,1.13587,472 -2017-07-05 01:00:00,1.13584,1.13679,1.13557,1.13669,543 -2017-07-05 02:00:00,1.13666,1.13684,1.13612,1.13628,469 -2017-07-05 03:00:00,1.13624,1.13624,1.1357,1.13587,246 -2017-07-05 04:00:00,1.13585,1.13585,1.13534,1.13546,127 -2017-07-05 05:00:00,1.13549,1.13572,1.13497,1.13535,427 -2017-07-05 06:00:00,1.13533,1.13666,1.13533,1.136,1188 -2017-07-05 07:00:00,1.13598,1.1368,1.13582,1.13634,1697 -2017-07-05 08:00:00,1.13636,1.13648,1.13408,1.13418,1209 -2017-07-05 09:00:00,1.1342,1.13441,1.1318,1.13241,2588 -2017-07-05 10:00:00,1.13239,1.13274,1.13126,1.13212,1250 -2017-07-05 11:00:00,1.13215,1.1337,1.13196,1.13324,1023 -2017-07-05 12:00:00,1.13326,1.13348,1.13182,1.13206,1283 -2017-07-05 13:00:00,1.13208,1.13304,1.1318,1.133,1206 -2017-07-05 14:00:00,1.13302,1.1337,1.13256,1.13292,1788 -2017-07-05 15:00:00,1.1329,1.1344,1.13274,1.13356,965 -2017-07-05 16:00:00,1.13358,1.13409,1.13297,1.13383,584 -2017-07-05 17:00:00,1.1338,1.13436,1.13354,1.13412,558 -2017-07-05 18:00:00,1.1341,1.13568,1.13228,1.13411,2820 -2017-07-05 19:00:00,1.13408,1.13518,1.13381,1.1342,762 -2017-07-05 20:00:00,1.13422,1.13524,1.1342,1.13514,251 -2017-07-05 21:00:00,1.13517,1.13524,1.13484,1.13506,276 -2017-07-05 22:00:00,1.13509,1.13549,1.13506,1.13532,191 -2017-07-05 23:00:00,1.1353,1.13538,1.13462,1.13464,207 -2017-07-06 00:00:00,1.13462,1.13462,1.13357,1.13418,635 -2017-07-06 01:00:00,1.1342,1.13448,1.13303,1.1332,588 -2017-07-06 02:00:00,1.13323,1.13398,1.13299,1.13375,458 -2017-07-06 03:00:00,1.13373,1.13426,1.13373,1.13382,225 -2017-07-06 04:00:00,1.13384,1.13395,1.13371,1.13392,89 -2017-07-06 05:00:00,1.1339,1.13421,1.13376,1.13382,243 -2017-07-06 06:00:00,1.13386,1.13419,1.1331,1.13419,752 -2017-07-06 07:00:00,1.13416,1.13571,1.13416,1.13519,1297 -2017-07-06 08:00:00,1.13517,1.13546,1.13442,1.1349,1186 -2017-07-06 09:00:00,1.13488,1.13702,1.13444,1.13644,2725 -2017-07-06 10:00:00,1.13646,1.13738,1.13577,1.13658,1751 -2017-07-06 11:00:00,1.13656,1.13876,1.13614,1.13868,1839 -2017-07-06 12:00:00,1.13866,1.13977,1.1379,1.13906,2259 -2017-07-06 13:00:00,1.13908,1.14018,1.13817,1.14003,1591 -2017-07-06 14:00:00,1.14,1.1406,1.1393,1.14054,1743 -2017-07-06 15:00:00,1.14056,1.14071,1.13983,1.14068,1264 -2017-07-06 16:00:00,1.1407,1.14197,1.14068,1.14197,788 -2017-07-06 17:00:00,1.142,1.14246,1.14158,1.14232,613 -2017-07-06 18:00:00,1.14229,1.14238,1.14191,1.14226,510 -2017-07-06 19:00:00,1.14224,1.14235,1.14179,1.142,430 -2017-07-06 20:00:00,1.14204,1.14248,1.14184,1.14234,226 -2017-07-06 21:00:00,1.14232,1.14244,1.14185,1.14221,353 -2017-07-06 22:00:00,1.14218,1.14245,1.14186,1.14223,479 -2017-07-06 23:00:00,1.14221,1.14256,1.14193,1.14216,322 -2017-07-07 00:00:00,1.14214,1.1422,1.14134,1.14156,539 -2017-07-07 01:00:00,1.14158,1.14243,1.14102,1.14117,1042 -2017-07-07 02:00:00,1.14114,1.14141,1.14084,1.14138,466 -2017-07-07 03:00:00,1.14136,1.14161,1.14117,1.14135,420 -2017-07-07 04:00:00,1.14133,1.14202,1.14133,1.14151,274 -2017-07-07 05:00:00,1.14148,1.14184,1.14072,1.14077,467 -2017-07-07 06:00:00,1.14075,1.14192,1.14072,1.14148,1041 -2017-07-07 07:00:00,1.14146,1.14274,1.14133,1.14196,1277 -2017-07-07 08:00:00,1.14198,1.14246,1.14122,1.14218,1106 -2017-07-07 09:00:00,1.1422,1.14252,1.14127,1.14146,1112 -2017-07-07 10:00:00,1.14143,1.14156,1.14062,1.14115,785 -2017-07-07 11:00:00,1.14112,1.14192,1.14074,1.14079,984 -2017-07-07 12:00:00,1.14082,1.14397,1.13867,1.14018,5387 -2017-07-07 13:00:00,1.1402,1.1405,1.13808,1.13977,2854 -2017-07-07 14:00:00,1.1398,1.14014,1.13797,1.13919,1689 -2017-07-07 15:00:00,1.13922,1.13961,1.13866,1.13961,1088 -2017-07-07 16:00:00,1.13964,1.14086,1.13964,1.14083,670 -2017-07-07 17:00:00,1.1408,1.14108,1.14014,1.14041,524 -2017-07-07 18:00:00,1.14039,1.14059,1.14011,1.1403,277 -2017-07-07 19:00:00,1.14032,1.14078,1.14018,1.14047,370 -2017-07-07 20:00:00,1.14045,1.14049,1.13982,1.14001,257 -2017-07-09 21:00:00,1.13985,1.14004,1.13932,1.13993,300 -2017-07-09 22:00:00,1.13996,1.14022,1.13982,1.14001,187 -2017-07-09 23:00:00,1.14004,1.14038,1.13995,1.14035,122 -2017-07-10 00:00:00,1.14032,1.14036,1.13978,1.14006,266 -2017-07-10 01:00:00,1.14002,1.14084,1.13996,1.14082,312 -2017-07-10 02:00:00,1.14079,1.14084,1.14044,1.14052,195 -2017-07-10 03:00:00,1.1405,1.14061,1.14018,1.14046,173 -2017-07-10 04:00:00,1.14044,1.14054,1.14006,1.14039,136 -2017-07-10 05:00:00,1.14042,1.14091,1.14019,1.14091,220 -2017-07-10 06:00:00,1.14094,1.14096,1.13972,1.13987,887 -2017-07-10 07:00:00,1.1399,1.14181,1.13969,1.1416,1384 -2017-07-10 08:00:00,1.14163,1.14167,1.13929,1.13957,1266 -2017-07-10 09:00:00,1.13959,1.13978,1.13823,1.13853,969 -2017-07-10 10:00:00,1.13856,1.13939,1.13832,1.13912,551 -2017-07-10 11:00:00,1.1391,1.13924,1.13818,1.13885,1071 -2017-07-10 12:00:00,1.13888,1.13939,1.1383,1.13922,903 -2017-07-10 13:00:00,1.13924,1.13939,1.13852,1.13917,938 -2017-07-10 14:00:00,1.13915,1.1396,1.13869,1.1388,1149 -2017-07-10 15:00:00,1.13882,1.1396,1.13848,1.13956,857 -2017-07-10 16:00:00,1.13958,1.14019,1.13946,1.13956,400 -2017-07-10 17:00:00,1.13958,1.14074,1.13956,1.1406,406 -2017-07-10 18:00:00,1.14062,1.1408,1.14025,1.14032,250 -2017-07-10 19:00:00,1.1403,1.14036,1.1398,1.14,315 -2017-07-10 20:00:00,1.13998,1.14005,1.13981,1.13994,109 -2017-07-10 21:00:00,1.13992,1.13996,1.13958,1.13976,352 -2017-07-10 22:00:00,1.13978,1.13984,1.13938,1.13966,308 -2017-07-10 23:00:00,1.13968,1.1398,1.13954,1.13963,114 -2017-07-11 00:00:00,1.1396,1.13979,1.13929,1.13948,274 -2017-07-11 01:00:00,1.13951,1.13974,1.13924,1.13931,328 -2017-07-11 02:00:00,1.13934,1.1396,1.13926,1.13936,199 -2017-07-11 03:00:00,1.13934,1.13952,1.13924,1.13944,133 -2017-07-11 04:00:00,1.13946,1.13946,1.13872,1.13886,186 -2017-07-11 05:00:00,1.13888,1.13888,1.13833,1.13834,398 -2017-07-11 06:00:00,1.13836,1.13918,1.13829,1.13907,807 -2017-07-11 07:00:00,1.1391,1.13991,1.13852,1.13902,1422 -2017-07-11 08:00:00,1.13904,1.14,1.13904,1.13962,1004 -2017-07-11 09:00:00,1.13959,1.1396,1.13918,1.1395,774 -2017-07-11 10:00:00,1.13952,1.13974,1.13901,1.13958,643 -2017-07-11 11:00:00,1.1396,1.13988,1.1394,1.13944,565 -2017-07-11 12:00:00,1.13942,1.1414,1.13942,1.14019,1504 -2017-07-11 13:00:00,1.14017,1.14092,1.13936,1.14082,1182 -2017-07-11 14:00:00,1.14084,1.14249,1.13954,1.14194,1875 -2017-07-11 15:00:00,1.14197,1.14334,1.14147,1.143,1633 -2017-07-11 16:00:00,1.14298,1.1448,1.14286,1.14396,1548 -2017-07-11 17:00:00,1.14398,1.14767,1.14398,1.14666,1834 -2017-07-11 18:00:00,1.14664,1.14797,1.14662,1.14766,1031 -2017-07-11 19:00:00,1.14762,1.14763,1.14626,1.14635,612 -2017-07-11 20:00:00,1.14633,1.14674,1.1461,1.14672,266 -2017-07-11 21:00:00,1.14665,1.14671,1.14629,1.14649,346 -2017-07-11 22:00:00,1.14652,1.14719,1.1463,1.14697,388 -2017-07-11 23:00:00,1.14694,1.14741,1.14666,1.1474,253 -2017-07-12 00:00:00,1.14738,1.14782,1.14722,1.14764,491 -2017-07-12 01:00:00,1.14766,1.14792,1.14706,1.14716,514 -2017-07-12 02:00:00,1.14714,1.14839,1.14704,1.14818,367 -2017-07-12 03:00:00,1.1482,1.1482,1.14734,1.14808,289 -2017-07-12 04:00:00,1.14804,1.14884,1.14748,1.14857,378 -2017-07-12 05:00:00,1.14854,1.14894,1.147,1.14723,589 -2017-07-12 06:00:00,1.14726,1.14765,1.14559,1.1459,1501 -2017-07-12 07:00:00,1.14588,1.14642,1.14469,1.14484,1446 -2017-07-12 08:00:00,1.14482,1.14632,1.14422,1.14576,1124 -2017-07-12 09:00:00,1.14574,1.1461,1.14438,1.14546,1462 -2017-07-12 10:00:00,1.14549,1.14606,1.1449,1.14532,957 -2017-07-12 11:00:00,1.14535,1.1462,1.14514,1.14536,1167 -2017-07-12 12:00:00,1.14534,1.14798,1.1427,1.14676,4996 -2017-07-12 13:00:00,1.14678,1.14689,1.14098,1.1414,5616 -2017-07-12 14:00:00,1.14143,1.14196,1.13919,1.14188,4290 -2017-07-12 15:00:00,1.1419,1.14274,1.14084,1.14103,2198 -2017-07-12 16:00:00,1.14106,1.14222,1.14093,1.14208,1147 -2017-07-12 17:00:00,1.14206,1.14239,1.14122,1.14186,954 -2017-07-12 18:00:00,1.14188,1.14252,1.1414,1.1415,674 -2017-07-12 19:00:00,1.14152,1.14224,1.14126,1.14202,544 -2017-07-12 20:00:00,1.142,1.142,1.14109,1.14117,203 -2017-07-12 21:00:00,1.1413,1.14181,1.14124,1.14131,259 -2017-07-12 22:00:00,1.14128,1.14182,1.14122,1.1416,192 -2017-07-12 23:00:00,1.14162,1.14198,1.14142,1.14186,129 -2017-07-13 00:00:00,1.14184,1.14298,1.14171,1.14296,565 -2017-07-13 01:00:00,1.14294,1.1437,1.14294,1.14346,447 -2017-07-13 02:00:00,1.14348,1.14379,1.14323,1.14372,333 -2017-07-13 03:00:00,1.14374,1.14391,1.14338,1.14341,396 -2017-07-13 04:00:00,1.14344,1.14386,1.14338,1.14377,221 -2017-07-13 05:00:00,1.14374,1.14496,1.14355,1.14472,405 -2017-07-13 06:00:00,1.1447,1.14558,1.14436,1.14468,1411 -2017-07-13 07:00:00,1.1447,1.14529,1.14129,1.14217,1905 -2017-07-13 08:00:00,1.14214,1.14232,1.1396,1.14037,2072 -2017-07-13 09:00:00,1.14034,1.14082,1.13856,1.13961,2260 -2017-07-13 10:00:00,1.13964,1.14054,1.13763,1.13881,2173 -2017-07-13 11:00:00,1.13883,1.1413,1.13706,1.14104,5719 -2017-07-13 12:00:00,1.14107,1.14192,1.14022,1.14163,2685 -2017-07-13 13:00:00,1.1416,1.14178,1.13984,1.13988,1603 -2017-07-13 14:00:00,1.13986,1.14149,1.13904,1.14036,2303 -2017-07-13 15:00:00,1.14039,1.14078,1.1384,1.1384,1405 -2017-07-13 16:00:00,1.13842,1.13919,1.13828,1.13906,661 -2017-07-13 17:00:00,1.13908,1.13994,1.13894,1.13974,708 -2017-07-13 18:00:00,1.13972,1.14063,1.13964,1.14044,574 -2017-07-13 19:00:00,1.14041,1.14068,1.14022,1.14068,408 -2017-07-13 20:00:00,1.14066,1.14066,1.1396,1.13979,247 -2017-07-13 21:00:00,1.13983,1.14022,1.13977,1.14003,161 -2017-07-13 22:00:00,1.14,1.14017,1.13954,1.13956,177 -2017-07-13 23:00:00,1.13958,1.14051,1.13958,1.14045,241 -2017-07-14 00:00:00,1.14042,1.14042,1.13917,1.14018,447 -2017-07-14 01:00:00,1.14016,1.14072,1.13971,1.1402,385 -2017-07-14 02:00:00,1.14022,1.14086,1.14002,1.14084,333 -2017-07-14 03:00:00,1.14082,1.14104,1.14065,1.14104,183 -2017-07-14 04:00:00,1.14102,1.14108,1.14008,1.14008,155 -2017-07-14 05:00:00,1.14011,1.14123,1.14011,1.14098,314 -2017-07-14 06:00:00,1.14096,1.1418,1.14046,1.14158,1253 -2017-07-14 07:00:00,1.14156,1.14239,1.14092,1.14168,1435 -2017-07-14 08:00:00,1.14166,1.14204,1.14076,1.14079,999 -2017-07-14 09:00:00,1.14081,1.1418,1.14076,1.14146,1261 -2017-07-14 10:00:00,1.14149,1.14181,1.14114,1.14142,655 -2017-07-14 11:00:00,1.1414,1.14195,1.14111,1.1417,797 -2017-07-14 12:00:00,1.14172,1.14684,1.14136,1.14618,4788 -2017-07-14 13:00:00,1.1462,1.14632,1.14362,1.14591,3299 -2017-07-14 14:00:00,1.14594,1.14634,1.14357,1.14444,2925 -2017-07-14 15:00:00,1.14448,1.14606,1.14448,1.14516,1434 -2017-07-14 16:00:00,1.14518,1.14601,1.14499,1.14594,764 -2017-07-14 17:00:00,1.14596,1.14688,1.14572,1.14673,673 -2017-07-14 18:00:00,1.1467,1.14688,1.14625,1.14658,374 -2017-07-14 19:00:00,1.1466,1.14712,1.14647,1.14708,377 -2017-07-14 20:00:00,1.14706,1.14718,1.14662,1.14688,279 -2017-07-16 21:00:00,1.14741,1.14741,1.1467,1.14702,172 -2017-07-16 22:00:00,1.14706,1.14742,1.1467,1.147,539 -2017-07-16 23:00:00,1.14702,1.14748,1.147,1.14741,236 -2017-07-17 00:00:00,1.14738,1.14745,1.14639,1.14649,300 -2017-07-17 01:00:00,1.14647,1.14674,1.14604,1.14618,394 -2017-07-17 02:00:00,1.14616,1.14649,1.14569,1.1461,273 -2017-07-17 03:00:00,1.14612,1.1466,1.14596,1.14635,279 -2017-07-17 04:00:00,1.14632,1.14634,1.14584,1.14614,137 -2017-07-17 05:00:00,1.14612,1.14634,1.1457,1.14615,243 -2017-07-17 06:00:00,1.14612,1.14624,1.14468,1.14539,1339 -2017-07-17 07:00:00,1.14536,1.14578,1.1435,1.14408,1674 -2017-07-17 08:00:00,1.14406,1.14514,1.14394,1.14482,937 -2017-07-17 09:00:00,1.14484,1.14601,1.14452,1.14592,958 -2017-07-17 10:00:00,1.1459,1.14644,1.14554,1.1459,848 -2017-07-17 11:00:00,1.14592,1.14702,1.14592,1.14638,724 -2017-07-17 12:00:00,1.14641,1.1471,1.14608,1.1468,1140 -2017-07-17 13:00:00,1.14677,1.1468,1.1461,1.14672,1224 -2017-07-17 14:00:00,1.14674,1.14871,1.14662,1.14708,1648 -2017-07-17 15:00:00,1.1471,1.14771,1.14638,1.14692,1134 -2017-07-17 16:00:00,1.14694,1.14758,1.14687,1.14722,469 -2017-07-17 17:00:00,1.14725,1.14807,1.14725,1.1478,493 -2017-07-17 18:00:00,1.14782,1.14808,1.1476,1.14804,336 -2017-07-17 19:00:00,1.14802,1.14845,1.14762,1.14824,406 -2017-07-17 20:00:00,1.14826,1.14833,1.14778,1.14782,180 -2017-07-17 21:00:00,1.14784,1.14814,1.14756,1.14785,346 -2017-07-17 22:00:00,1.14788,1.14798,1.14757,1.14768,374 -2017-07-17 23:00:00,1.14771,1.14792,1.14732,1.14735,130 -2017-07-18 00:00:00,1.14737,1.14872,1.14717,1.14854,501 -2017-07-18 01:00:00,1.14856,1.1532,1.14852,1.15293,2414 -2017-07-18 02:00:00,1.15295,1.1538,1.15256,1.15292,1128 -2017-07-18 03:00:00,1.15289,1.15354,1.15263,1.15278,588 -2017-07-18 04:00:00,1.15276,1.15302,1.15234,1.15276,582 -2017-07-18 05:00:00,1.15273,1.1535,1.15188,1.15223,891 -2017-07-18 06:00:00,1.1522,1.15314,1.1513,1.15267,2413 -2017-07-18 07:00:00,1.15265,1.15295,1.15113,1.15288,2334 -2017-07-18 08:00:00,1.1529,1.15321,1.15172,1.15255,2072 -2017-07-18 09:00:00,1.15253,1.15601,1.15194,1.15521,2418 -2017-07-18 10:00:00,1.15518,1.15642,1.15499,1.15576,1450 -2017-07-18 11:00:00,1.15574,1.156,1.15454,1.15498,1481 -2017-07-18 12:00:00,1.155,1.15682,1.15452,1.15559,3019 -2017-07-18 13:00:00,1.15562,1.15814,1.1554,1.15798,1930 -2017-07-18 14:00:00,1.158,1.15832,1.15728,1.15807,1634 -2017-07-18 15:00:00,1.1581,1.15824,1.15684,1.1578,1378 -2017-07-18 16:00:00,1.15782,1.15813,1.15584,1.1563,1099 -2017-07-18 17:00:00,1.15632,1.15642,1.15531,1.15625,977 -2017-07-18 18:00:00,1.15623,1.15656,1.1556,1.1561,592 -2017-07-18 19:00:00,1.15612,1.1562,1.15524,1.15574,534 -2017-07-18 20:00:00,1.15577,1.15585,1.15532,1.15538,188 -2017-07-18 21:00:00,1.15558,1.15566,1.15534,1.15537,167 -2017-07-18 22:00:00,1.15539,1.15554,1.15504,1.15506,401 -2017-07-18 23:00:00,1.15509,1.15524,1.1548,1.1548,240 -2017-07-19 00:00:00,1.15482,1.15534,1.15433,1.15448,460 -2017-07-19 01:00:00,1.1545,1.15452,1.15414,1.15422,374 -2017-07-19 02:00:00,1.1542,1.15442,1.15386,1.15392,226 -2017-07-19 03:00:00,1.15394,1.15402,1.15366,1.1539,289 -2017-07-19 04:00:00,1.15392,1.15396,1.1537,1.15376,135 -2017-07-19 05:00:00,1.15378,1.15378,1.15313,1.15328,453 -2017-07-19 06:00:00,1.15326,1.15476,1.15292,1.15296,1578 -2017-07-19 07:00:00,1.15294,1.15391,1.1519,1.15202,2020 -2017-07-19 08:00:00,1.152,1.15276,1.15148,1.15266,1275 -2017-07-19 09:00:00,1.15269,1.15378,1.15268,1.15298,1009 -2017-07-19 10:00:00,1.15296,1.15376,1.15238,1.15256,737 -2017-07-19 11:00:00,1.15254,1.15307,1.1521,1.15298,949 -2017-07-19 12:00:00,1.153,1.15385,1.15238,1.15257,1524 -2017-07-19 13:00:00,1.1526,1.15367,1.15238,1.15238,1797 -2017-07-19 14:00:00,1.1524,1.15288,1.15101,1.15178,1594 -2017-07-19 15:00:00,1.1518,1.15298,1.1513,1.15178,1435 -2017-07-19 16:00:00,1.15176,1.1523,1.15142,1.1521,633 -2017-07-19 17:00:00,1.15212,1.15232,1.15172,1.15174,486 -2017-07-19 18:00:00,1.15171,1.15193,1.15135,1.15182,411 -2017-07-19 19:00:00,1.15184,1.15193,1.15149,1.15174,390 -2017-07-19 20:00:00,1.15176,1.15178,1.1513,1.15154,218 -2017-07-19 21:00:00,1.15145,1.15187,1.1513,1.15179,392 -2017-07-19 22:00:00,1.15177,1.15282,1.15177,1.15276,360 -2017-07-19 23:00:00,1.15278,1.15326,1.15278,1.15288,157 -2017-07-20 00:00:00,1.15286,1.1529,1.15228,1.15231,287 -2017-07-20 01:00:00,1.15233,1.15263,1.15127,1.15166,571 -2017-07-20 02:00:00,1.15169,1.15256,1.15144,1.15235,630 -2017-07-20 03:00:00,1.15238,1.15272,1.15052,1.15067,825 -2017-07-20 04:00:00,1.1507,1.1512,1.15067,1.1512,328 -2017-07-20 05:00:00,1.15118,1.15124,1.15044,1.15114,506 -2017-07-20 06:00:00,1.15111,1.15254,1.15089,1.15227,1455 -2017-07-20 07:00:00,1.15224,1.1523,1.15004,1.15004,1839 -2017-07-20 08:00:00,1.15007,1.15068,1.14962,1.15049,1655 -2017-07-20 09:00:00,1.15047,1.15074,1.1497,1.15038,991 -2017-07-20 10:00:00,1.15036,1.15123,1.15008,1.15063,1165 -2017-07-20 11:00:00,1.15066,1.15132,1.14798,1.14849,3324 -2017-07-20 12:00:00,1.14846,1.15705,1.14794,1.15619,10944 -2017-07-20 13:00:00,1.15622,1.1574,1.15414,1.15619,5055 -2017-07-20 14:00:00,1.15622,1.16582,1.15618,1.16345,6648 -2017-07-20 15:00:00,1.16348,1.1647,1.16274,1.16337,2729 -2017-07-20 16:00:00,1.16334,1.16398,1.16272,1.16344,1182 -2017-07-20 17:00:00,1.16347,1.16376,1.16184,1.16292,1758 -2017-07-20 18:00:00,1.16288,1.16296,1.16178,1.16248,921 -2017-07-20 19:00:00,1.16246,1.16308,1.16212,1.16286,766 -2017-07-20 20:00:00,1.16284,1.16338,1.1624,1.16312,1377 -2017-07-20 21:00:00,1.16298,1.16364,1.1629,1.16327,2436 -2017-07-20 22:00:00,1.16326,1.16361,1.16248,1.1628,896 -2017-07-20 23:00:00,1.1628,1.16319,1.16262,1.16282,596 -2017-07-21 00:00:00,1.16282,1.16302,1.16192,1.16266,1317 -2017-07-21 01:00:00,1.1627,1.16299,1.16231,1.16288,1268 -2017-07-21 02:00:00,1.16289,1.16366,1.1624,1.16249,1591 -2017-07-21 03:00:00,1.16248,1.16298,1.16232,1.16284,896 -2017-07-21 04:00:00,1.1628,1.16304,1.16251,1.1629,602 -2017-07-21 05:00:00,1.1629,1.16402,1.16283,1.16401,757 -2017-07-21 06:00:00,1.16398,1.1677,1.16368,1.1663,5207 -2017-07-21 07:00:00,1.16629,1.16737,1.16378,1.16386,3951 -2017-07-21 08:00:00,1.16388,1.16512,1.1636,1.16495,2343 -2017-07-21 09:00:00,1.16492,1.16584,1.16386,1.16463,2570 -2017-07-21 10:00:00,1.1646,1.1652,1.16378,1.16442,1989 -2017-07-21 11:00:00,1.16444,1.1651,1.16402,1.16416,2383 -2017-07-21 12:00:00,1.16419,1.1648,1.16352,1.16402,2644 -2017-07-21 13:00:00,1.16406,1.16522,1.16358,1.16462,2607 -2017-07-21 14:00:00,1.16463,1.16672,1.1645,1.1655,2916 -2017-07-21 15:00:00,1.16555,1.1658,1.16484,1.16548,1789 -2017-07-21 16:00:00,1.16546,1.16704,1.16538,1.16662,1517 -2017-07-21 17:00:00,1.1666,1.16826,1.16654,1.1676,2229 -2017-07-21 18:00:00,1.16755,1.16812,1.16725,1.16783,1637 -2017-07-21 19:00:00,1.16782,1.16791,1.16647,1.16686,1240 -2017-07-21 20:00:00,1.1668,1.16702,1.16612,1.16642,2862 -2017-07-23 21:00:00,1.16635,1.1672,1.16635,1.1668,350 -2017-07-23 22:00:00,1.16675,1.16742,1.16656,1.16728,1873 -2017-07-23 23:00:00,1.16733,1.1682,1.16716,1.16814,714 -2017-07-24 00:00:00,1.16812,1.16845,1.16678,1.1671,1710 -2017-07-24 01:00:00,1.16706,1.16712,1.16632,1.16688,954 -2017-07-24 02:00:00,1.16691,1.16704,1.16677,1.1668,560 -2017-07-24 03:00:00,1.16682,1.16751,1.1668,1.16716,707 -2017-07-24 04:00:00,1.16716,1.16744,1.16696,1.16708,412 -2017-07-24 05:00:00,1.16707,1.16751,1.16681,1.167,628 -2017-07-24 06:00:00,1.16698,1.16723,1.1642,1.16455,3439 -2017-07-24 07:00:00,1.16454,1.16618,1.16304,1.164,4850 -2017-07-24 08:00:00,1.16397,1.16541,1.16388,1.16527,2841 -2017-07-24 09:00:00,1.1653,1.16576,1.16486,1.16567,2510 -2017-07-24 10:00:00,1.16566,1.16601,1.16457,1.1649,2114 -2017-07-24 11:00:00,1.16487,1.16525,1.16425,1.1645,1740 -2017-07-24 12:00:00,1.16452,1.16577,1.16432,1.16558,2152 -2017-07-24 13:00:00,1.1656,1.16562,1.16333,1.1638,2267 -2017-07-24 14:00:00,1.16388,1.165,1.16342,1.16432,2546 -2017-07-24 15:00:00,1.16436,1.16481,1.16374,1.16426,2333 -2017-07-24 16:00:00,1.16422,1.16438,1.16257,1.1638,1551 -2017-07-24 17:00:00,1.16377,1.1641,1.16304,1.16403,995 -2017-07-24 18:00:00,1.16402,1.16439,1.1637,1.16432,842 -2017-07-24 19:00:00,1.16434,1.16473,1.16424,1.16435,573 -2017-07-24 20:00:00,1.1643,1.16439,1.16402,1.1642,446 -2017-07-24 21:00:00,1.16406,1.16455,1.16315,1.16365,3595 -2017-07-24 22:00:00,1.16366,1.16396,1.16352,1.16376,1515 -2017-07-24 23:00:00,1.16374,1.16404,1.1636,1.1639,603 -2017-07-25 00:00:00,1.1639,1.16402,1.16306,1.1638,1142 -2017-07-25 01:00:00,1.1638,1.16427,1.16347,1.16408,743 -2017-07-25 02:00:00,1.1641,1.16569,1.16391,1.16533,1188 -2017-07-25 03:00:00,1.16532,1.16564,1.16518,1.16564,430 -2017-07-25 04:00:00,1.1656,1.16637,1.1656,1.1662,1140 -2017-07-25 05:00:00,1.16618,1.1663,1.16523,1.1663,688 -2017-07-25 06:00:00,1.16625,1.16692,1.16576,1.16616,2408 -2017-07-25 07:00:00,1.1662,1.1662,1.16434,1.16516,3744 -2017-07-25 08:00:00,1.16516,1.1668,1.16492,1.16536,3766 -2017-07-25 09:00:00,1.16536,1.16583,1.16488,1.16543,1890 -2017-07-25 10:00:00,1.1654,1.16564,1.16473,1.16514,1705 -2017-07-25 11:00:00,1.16514,1.16668,1.16498,1.16668,1756 -2017-07-25 12:00:00,1.1667,1.16994,1.1667,1.1689,4473 -2017-07-25 13:00:00,1.16889,1.17124,1.16808,1.16956,5829 -2017-07-25 14:00:00,1.16958,1.16969,1.16572,1.16612,4799 -2017-07-25 15:00:00,1.16612,1.16712,1.16458,1.16547,3139 -2017-07-25 16:00:00,1.16546,1.16584,1.16496,1.16536,1679 -2017-07-25 17:00:00,1.16538,1.16616,1.16523,1.16582,1023 -2017-07-25 18:00:00,1.16586,1.16593,1.16449,1.16506,1645 -2017-07-25 19:00:00,1.16504,1.16534,1.1644,1.16476,1676 -2017-07-25 20:00:00,1.16476,1.16493,1.16422,1.16472,751 -2017-07-25 21:00:00,1.16507,1.16512,1.16456,1.1648,2851 -2017-07-25 22:00:00,1.16478,1.16489,1.16455,1.16466,487 -2017-07-25 23:00:00,1.16467,1.16472,1.16434,1.16446,473 -2017-07-26 00:00:00,1.16444,1.16455,1.16378,1.16415,1152 -2017-07-26 01:00:00,1.16417,1.16478,1.16388,1.16464,1111 -2017-07-26 02:00:00,1.16462,1.16538,1.16448,1.1652,685 -2017-07-26 03:00:00,1.16524,1.16533,1.16422,1.16436,930 -2017-07-26 04:00:00,1.16434,1.1649,1.16382,1.16388,619 -2017-07-26 05:00:00,1.16392,1.16414,1.16335,1.16388,861 -2017-07-26 06:00:00,1.1639,1.16438,1.16208,1.1638,2927 -2017-07-26 07:00:00,1.1638,1.16458,1.16255,1.16301,2867 -2017-07-26 08:00:00,1.16301,1.16338,1.16128,1.1623,3409 -2017-07-26 09:00:00,1.16234,1.16327,1.16187,1.16326,2393 -2017-07-26 10:00:00,1.16321,1.16516,1.16306,1.16424,2699 -2017-07-26 11:00:00,1.16422,1.16503,1.16376,1.16427,2422 -2017-07-26 12:00:00,1.16431,1.16486,1.16385,1.1641,2334 -2017-07-26 13:00:00,1.16412,1.16556,1.16316,1.16336,3738 -2017-07-26 14:00:00,1.16338,1.16392,1.16218,1.16299,3751 -2017-07-26 15:00:00,1.16304,1.16396,1.16264,1.16324,2947 -2017-07-26 16:00:00,1.16322,1.16376,1.16256,1.16266,1632 -2017-07-26 17:00:00,1.16269,1.16533,1.16265,1.1647,3273 -2017-07-26 18:00:00,1.16469,1.17078,1.16288,1.17041,15025 -2017-07-26 19:00:00,1.1704,1.174,1.1704,1.17218,8638 -2017-07-26 20:00:00,1.17216,1.17397,1.17206,1.17346,2136 -2017-07-26 21:00:00,1.17364,1.17479,1.17324,1.17464,2338 -2017-07-26 22:00:00,1.17464,1.17479,1.17325,1.17344,1470 -2017-07-26 23:00:00,1.17338,1.17346,1.17267,1.1732,738 -2017-07-27 00:00:00,1.17318,1.17392,1.17253,1.17296,2147 -2017-07-27 01:00:00,1.173,1.17426,1.17215,1.17399,1782 -2017-07-27 02:00:00,1.17398,1.1746,1.17372,1.1746,1556 -2017-07-27 03:00:00,1.1746,1.1777,1.17424,1.17564,2583 -2017-07-27 04:00:00,1.17566,1.17624,1.17459,1.17491,1840 -2017-07-27 05:00:00,1.17488,1.17514,1.17349,1.17396,1823 -2017-07-27 06:00:00,1.17396,1.17475,1.17274,1.1729,4166 -2017-07-27 07:00:00,1.1729,1.17338,1.17148,1.17235,4699 -2017-07-27 08:00:00,1.17238,1.17308,1.1712,1.17286,3169 -2017-07-27 09:00:00,1.17281,1.17334,1.17175,1.172,2479 -2017-07-27 10:00:00,1.17198,1.17215,1.17031,1.17048,2883 -2017-07-27 11:00:00,1.17051,1.17131,1.16874,1.16932,2968 -2017-07-27 12:00:00,1.16934,1.17057,1.16897,1.16964,4070 -2017-07-27 13:00:00,1.16967,1.1705,1.16902,1.17049,3432 -2017-07-27 14:00:00,1.17045,1.17063,1.16625,1.16658,5529 -2017-07-27 15:00:00,1.16659,1.16786,1.1654,1.1655,3747 -2017-07-27 16:00:00,1.16554,1.1669,1.16502,1.16644,2731 -2017-07-27 17:00:00,1.16642,1.168,1.16594,1.1675,3511 -2017-07-27 18:00:00,1.1675,1.1689,1.16658,1.16832,4061 -2017-07-27 19:00:00,1.16831,1.1684,1.16719,1.16763,1735 -2017-07-27 20:00:00,1.16763,1.16792,1.16712,1.16774,1741 -2017-07-27 21:00:00,1.16776,1.16794,1.16724,1.16752,2194 -2017-07-27 22:00:00,1.16755,1.16886,1.16752,1.16842,1626 -2017-07-27 23:00:00,1.16844,1.16914,1.16814,1.16898,491 -2017-07-28 00:00:00,1.16898,1.16924,1.16712,1.16764,1846 -2017-07-28 01:00:00,1.16769,1.16844,1.16714,1.16844,2049 -2017-07-28 02:00:00,1.16842,1.16932,1.16803,1.16932,1062 -2017-07-28 03:00:00,1.1693,1.1694,1.1683,1.16838,902 -2017-07-28 04:00:00,1.16838,1.16885,1.16817,1.1685,769 -2017-07-28 05:00:00,1.16852,1.1696,1.16852,1.16943,1204 -2017-07-28 06:00:00,1.16944,1.17015,1.16876,1.1697,2796 -2017-07-28 07:00:00,1.16976,1.17156,1.16916,1.16964,4014 -2017-07-28 08:00:00,1.16966,1.17078,1.16966,1.17056,3269 -2017-07-28 09:00:00,1.17057,1.1718,1.17053,1.17159,2650 -2017-07-28 10:00:00,1.17154,1.17218,1.17042,1.1707,2495 -2017-07-28 11:00:00,1.17066,1.1724,1.17046,1.17185,2363 -2017-07-28 12:00:00,1.17186,1.17538,1.17148,1.1716,7413 -2017-07-28 13:00:00,1.17161,1.17328,1.1715,1.17281,5182 -2017-07-28 14:00:00,1.1728,1.1754,1.17268,1.17472,5513 -2017-07-28 15:00:00,1.17472,1.17644,1.17415,1.17554,5710 -2017-07-28 16:00:00,1.17554,1.17562,1.17382,1.17409,1733 -2017-07-28 17:00:00,1.17416,1.17506,1.17412,1.17469,1301 -2017-07-28 18:00:00,1.17472,1.17624,1.17432,1.17614,1040 -2017-07-28 19:00:00,1.1761,1.17622,1.1753,1.17587,1494 -2017-07-28 20:00:00,1.17582,1.17594,1.17468,1.17498,1783 -2017-07-30 21:00:00,1.17482,1.17594,1.17482,1.17543,793 -2017-07-30 22:00:00,1.17534,1.17623,1.17493,1.17594,4559 -2017-07-30 23:00:00,1.17595,1.176,1.17455,1.17471,909 -2017-07-31 00:00:00,1.17477,1.175,1.17348,1.17428,2217 -2017-07-31 01:00:00,1.17434,1.17463,1.17378,1.17396,1268 -2017-07-31 02:00:00,1.17395,1.1744,1.17354,1.17354,875 -2017-07-31 03:00:00,1.17356,1.17374,1.17317,1.17324,690 -2017-07-31 04:00:00,1.17322,1.1737,1.17314,1.17364,315 -2017-07-31 05:00:00,1.1736,1.17478,1.17316,1.17464,705 -2017-07-31 06:00:00,1.17462,1.17466,1.17243,1.17376,3233 -2017-07-31 07:00:00,1.1737,1.17382,1.17232,1.17247,2672 -2017-07-31 08:00:00,1.17246,1.17345,1.17236,1.17326,1648 -2017-07-31 09:00:00,1.1732,1.17442,1.17278,1.17344,2400 -2017-07-31 10:00:00,1.17343,1.17376,1.173,1.17314,1142 -2017-07-31 11:00:00,1.1731,1.17351,1.17256,1.17278,1358 -2017-07-31 12:00:00,1.17272,1.17354,1.17234,1.1734,1620 -2017-07-31 13:00:00,1.17338,1.17519,1.17318,1.17484,2395 -2017-07-31 14:00:00,1.17484,1.17904,1.17462,1.1789,5104 -2017-07-31 15:00:00,1.17892,1.18304,1.17839,1.18262,5169 -2017-07-31 16:00:00,1.18259,1.1832,1.18056,1.1811,3929 -2017-07-31 17:00:00,1.18108,1.1827,1.18082,1.18143,2422 -2017-07-31 18:00:00,1.18148,1.18355,1.18132,1.18305,1921 -2017-07-31 19:00:00,1.18301,1.18454,1.18288,1.18365,2329 -2017-07-31 20:00:00,1.18364,1.1846,1.1831,1.18424,1648 -2017-07-31 21:00:00,1.18414,1.18446,1.18356,1.1836,2138 -2017-07-31 22:00:00,1.18366,1.1837,1.18294,1.18308,1743 -2017-07-31 23:00:00,1.18309,1.18326,1.18206,1.1821,1023 -2017-08-01 00:00:00,1.18207,1.183,1.18197,1.18272,1762 -2017-08-01 01:00:00,1.18272,1.1831,1.182,1.18298,1469 -2017-08-01 02:00:00,1.18294,1.1834,1.18262,1.18278,1225 -2017-08-01 03:00:00,1.18276,1.1828,1.18228,1.18264,526 -2017-08-01 04:00:00,1.18266,1.18344,1.18243,1.18305,1423 -2017-08-01 05:00:00,1.18301,1.18334,1.18196,1.18206,868 -2017-08-01 06:00:00,1.18206,1.18311,1.18116,1.18208,2227 -2017-08-01 07:00:00,1.18203,1.1823,1.18112,1.18192,2364 -2017-08-01 08:00:00,1.18196,1.18332,1.1815,1.18217,2402 -2017-08-01 09:00:00,1.1822,1.18244,1.18072,1.18144,2651 -2017-08-01 10:00:00,1.18142,1.18176,1.18047,1.18118,1565 -2017-08-01 11:00:00,1.18119,1.18229,1.18094,1.18105,1529 -2017-08-01 12:00:00,1.18107,1.18198,1.18064,1.18174,3624 -2017-08-01 13:00:00,1.18179,1.18291,1.1807,1.18247,3550 -2017-08-01 14:00:00,1.18243,1.18394,1.1785,1.18098,7271 -2017-08-01 15:00:00,1.181,1.18141,1.17916,1.17985,3709 -2017-08-01 16:00:00,1.17984,1.18058,1.17966,1.18045,1222 -2017-08-01 17:00:00,1.18046,1.18377,1.18046,1.1817,3334 -2017-08-01 18:00:00,1.18173,1.18199,1.17986,1.18034,1509 -2017-08-01 19:00:00,1.18034,1.18052,1.17988,1.18004,1181 -2017-08-01 20:00:00,1.18007,1.18032,1.17989,1.18016,844 -2017-08-01 21:00:00,1.1802,1.18098,1.17984,1.18061,2610 -2017-08-01 22:00:00,1.18055,1.18132,1.18048,1.1806,1168 -2017-08-01 23:00:00,1.1806,1.18132,1.18024,1.18109,899 -2017-08-02 00:00:00,1.1811,1.18178,1.18068,1.18136,1352 -2017-08-02 01:00:00,1.18136,1.18143,1.17942,1.18003,1386 -2017-08-02 02:00:00,1.18004,1.18091,1.17974,1.18086,1329 -2017-08-02 03:00:00,1.18083,1.18174,1.18038,1.18112,1240 -2017-08-02 04:00:00,1.18112,1.18287,1.18107,1.1825,2187 -2017-08-02 05:00:00,1.18252,1.18302,1.18208,1.18234,717 -2017-08-02 06:00:00,1.18232,1.18445,1.18174,1.18396,2240 -2017-08-02 07:00:00,1.18392,1.18409,1.18246,1.18333,2475 -2017-08-02 08:00:00,1.18336,1.18688,1.18305,1.18543,4988 -2017-08-02 09:00:00,1.18542,1.18592,1.18374,1.18375,3164 -2017-08-02 10:00:00,1.18376,1.18383,1.18302,1.1833,1525 -2017-08-02 11:00:00,1.18327,1.18376,1.1822,1.1827,1643 -2017-08-02 12:00:00,1.18274,1.1839,1.18185,1.18248,4776 -2017-08-02 13:00:00,1.18249,1.18344,1.1823,1.18334,2993 -2017-08-02 14:00:00,1.18339,1.18582,1.18256,1.18566,5321 -2017-08-02 15:00:00,1.18565,1.18714,1.18551,1.18605,3474 -2017-08-02 16:00:00,1.18604,1.1871,1.18603,1.18681,1593 -2017-08-02 17:00:00,1.18686,1.19108,1.18678,1.18832,4148 -2017-08-02 18:00:00,1.18828,1.18831,1.1857,1.18596,1907 -2017-08-02 19:00:00,1.18602,1.1861,1.185,1.18541,1290 -2017-08-02 20:00:00,1.18546,1.1858,1.18532,1.18558,799 -2017-08-02 21:00:00,1.1856,1.18622,1.18531,1.1855,1321 -2017-08-02 22:00:00,1.18548,1.18584,1.18505,1.18515,1830 -2017-08-02 23:00:00,1.18518,1.18533,1.1846,1.18512,815 -2017-08-03 00:00:00,1.18512,1.1852,1.18358,1.18358,1167 -2017-08-03 01:00:00,1.18363,1.18471,1.1836,1.18368,1243 -2017-08-03 02:00:00,1.1837,1.18438,1.18342,1.18433,1074 -2017-08-03 03:00:00,1.18436,1.18489,1.18414,1.18414,587 -2017-08-03 04:00:00,1.18419,1.18482,1.18419,1.18462,451 -2017-08-03 05:00:00,1.18458,1.1857,1.1844,1.18446,880 -2017-08-03 06:00:00,1.18446,1.18534,1.1838,1.18512,2262 -2017-08-03 07:00:00,1.18518,1.18568,1.18372,1.18408,2334 -2017-08-03 08:00:00,1.1843,1.18437,1.18306,1.18437,2473 -2017-08-03 09:00:00,1.18434,1.18504,1.18415,1.18456,1742 -2017-08-03 10:00:00,1.18455,1.18475,1.18335,1.18376,1223 -2017-08-03 11:00:00,1.18374,1.18586,1.18337,1.18537,5673 -2017-08-03 12:00:00,1.18536,1.18737,1.1848,1.18594,4218 -2017-08-03 13:00:00,1.1859,1.18594,1.18428,1.18498,2702 -2017-08-03 14:00:00,1.18498,1.18932,1.18453,1.18789,7354 -2017-08-03 15:00:00,1.18793,1.1889,1.18737,1.18794,3221 -2017-08-03 16:00:00,1.18792,1.18842,1.18678,1.18694,1891 -2017-08-03 17:00:00,1.18694,1.1872,1.18608,1.1872,1342 -2017-08-03 18:00:00,1.18722,1.18775,1.18644,1.18674,1285 -2017-08-03 19:00:00,1.1867,1.18885,1.1862,1.18751,3266 -2017-08-03 20:00:00,1.18754,1.18812,1.18675,1.18691,776 -2017-08-03 21:00:00,1.18707,1.1876,1.18682,1.18708,2546 -2017-08-03 22:00:00,1.18716,1.18804,1.18702,1.18774,885 -2017-08-03 23:00:00,1.18774,1.18856,1.1875,1.18826,811 -2017-08-04 00:00:00,1.1882,1.18858,1.18759,1.18766,964 -2017-08-04 01:00:00,1.18768,1.18797,1.18712,1.18774,1160 -2017-08-04 02:00:00,1.18774,1.188,1.1872,1.18748,734 -2017-08-04 03:00:00,1.1875,1.18793,1.18743,1.18793,351 -2017-08-04 04:00:00,1.18788,1.18887,1.18774,1.18798,803 -2017-08-04 05:00:00,1.18794,1.18866,1.18776,1.18844,691 -2017-08-04 06:00:00,1.18851,1.18856,1.1874,1.18851,1361 -2017-08-04 07:00:00,1.18846,1.18896,1.18764,1.18822,1939 -2017-08-04 08:00:00,1.18827,1.18882,1.18805,1.1882,1126 -2017-08-04 09:00:00,1.18823,1.18852,1.18776,1.18824,1119 -2017-08-04 10:00:00,1.1882,1.18832,1.18702,1.18704,971 -2017-08-04 11:00:00,1.18702,1.1877,1.18631,1.1877,1592 -2017-08-04 12:00:00,1.18766,1.18766,1.18253,1.18304,11283 -2017-08-04 13:00:00,1.18302,1.1846,1.17915,1.17933,6791 -2017-08-04 14:00:00,1.17934,1.17934,1.17284,1.17502,10580 -2017-08-04 15:00:00,1.17502,1.17645,1.17451,1.17536,3390 -2017-08-04 16:00:00,1.17536,1.17584,1.17362,1.17543,2289 -2017-08-04 17:00:00,1.17544,1.17638,1.175,1.17542,1635 -2017-08-04 18:00:00,1.17543,1.17672,1.17514,1.17645,1265 -2017-08-04 19:00:00,1.1765,1.17817,1.1765,1.17808,1497 -2017-08-04 20:00:00,1.17809,1.17832,1.17684,1.17734,1219 -2017-08-06 21:00:00,1.17738,1.17769,1.17723,1.17754,756 -2017-08-06 22:00:00,1.17751,1.1793,1.17717,1.17862,3326 -2017-08-06 23:00:00,1.1786,1.1792,1.17769,1.1777,1446 -2017-08-07 00:00:00,1.17773,1.17926,1.17767,1.17864,1594 -2017-08-07 01:00:00,1.17863,1.17934,1.17842,1.17927,1123 -2017-08-07 02:00:00,1.1793,1.18003,1.17914,1.17938,549 -2017-08-07 03:00:00,1.1794,1.18022,1.17932,1.17986,342 -2017-08-07 04:00:00,1.17982,1.18004,1.1795,1.17952,232 -2017-08-07 05:00:00,1.17954,1.17966,1.17838,1.17848,439 -2017-08-07 06:00:00,1.17848,1.17931,1.1781,1.17852,1714 -2017-08-07 07:00:00,1.17852,1.18142,1.1778,1.18098,3648 -2017-08-07 08:00:00,1.18102,1.18118,1.1796,1.17981,2456 -2017-08-07 09:00:00,1.17981,1.18056,1.17898,1.18024,1737 -2017-08-07 10:00:00,1.1802,1.1805,1.17948,1.17978,1368 -2017-08-07 11:00:00,1.17973,1.18084,1.17939,1.18025,1795 -2017-08-07 12:00:00,1.18027,1.18046,1.17864,1.17866,2064 -2017-08-07 13:00:00,1.17866,1.17945,1.1783,1.1792,2084 -2017-08-07 14:00:00,1.17926,1.17986,1.17832,1.17946,2431 -2017-08-07 15:00:00,1.1795,1.1796,1.17857,1.17876,1356 -2017-08-07 16:00:00,1.17871,1.17905,1.17816,1.17886,607 -2017-08-07 17:00:00,1.17886,1.17965,1.17886,1.17915,752 -2017-08-07 18:00:00,1.17917,1.17952,1.17872,1.17944,698 -2017-08-07 19:00:00,1.17942,1.17968,1.17888,1.17944,703 -2017-08-07 20:00:00,1.17944,1.17969,1.17922,1.1795,372 -2017-08-07 21:00:00,1.17938,1.1798,1.17902,1.17953,2448 -2017-08-07 22:00:00,1.17959,1.18012,1.17914,1.17922,1143 -2017-08-07 23:00:00,1.17924,1.18018,1.17924,1.17996,328 -2017-08-08 00:00:00,1.17998,1.18052,1.1798,1.18024,620 -2017-08-08 01:00:00,1.18028,1.18242,1.1802,1.18162,1330 -2017-08-08 02:00:00,1.18163,1.18178,1.18068,1.18132,699 -2017-08-08 03:00:00,1.18129,1.18164,1.18068,1.18068,470 -2017-08-08 04:00:00,1.1807,1.18156,1.1807,1.18114,394 -2017-08-08 05:00:00,1.18118,1.18152,1.18048,1.18082,525 -2017-08-08 06:00:00,1.18077,1.1813,1.1802,1.18052,1437 -2017-08-08 07:00:00,1.18054,1.18181,1.18029,1.18072,1727 -2017-08-08 08:00:00,1.18075,1.18156,1.18056,1.18084,1237 -2017-08-08 09:00:00,1.1808,1.18142,1.18068,1.18108,1166 -2017-08-08 10:00:00,1.18104,1.18184,1.18075,1.18158,1076 -2017-08-08 11:00:00,1.18156,1.18167,1.18056,1.18084,1222 -2017-08-08 12:00:00,1.18085,1.18176,1.1807,1.18148,1577 -2017-08-08 13:00:00,1.18146,1.1816,1.18065,1.18102,1664 -2017-08-08 14:00:00,1.18102,1.18124,1.17324,1.17385,7240 -2017-08-08 15:00:00,1.1739,1.17508,1.17154,1.17246,3974 -2017-08-08 16:00:00,1.1725,1.17541,1.17212,1.17525,2626 -2017-08-08 17:00:00,1.17526,1.17697,1.17502,1.17636,2246 -2017-08-08 18:00:00,1.17638,1.17641,1.17512,1.17522,1151 -2017-08-08 19:00:00,1.17521,1.1753,1.17406,1.17493,2202 -2017-08-08 20:00:00,1.1749,1.1759,1.17469,1.17529,1323 -2017-08-08 21:00:00,1.17508,1.17572,1.1746,1.17505,3933 -2017-08-08 22:00:00,1.17502,1.17624,1.1744,1.17595,1512 -2017-08-08 23:00:00,1.17589,1.17642,1.17524,1.17546,612 -2017-08-09 00:00:00,1.17542,1.17552,1.17336,1.17434,1889 -2017-08-09 01:00:00,1.17436,1.17496,1.17292,1.17357,1591 -2017-08-09 02:00:00,1.1736,1.1741,1.17194,1.17346,1796 -2017-08-09 03:00:00,1.17341,1.17364,1.17284,1.17332,957 -2017-08-09 04:00:00,1.17334,1.174,1.17326,1.17375,583 -2017-08-09 05:00:00,1.17376,1.17449,1.17357,1.17411,704 -2017-08-09 06:00:00,1.17406,1.17548,1.17353,1.17452,2469 -2017-08-09 07:00:00,1.1745,1.17619,1.1736,1.1743,3513 -2017-08-09 08:00:00,1.1743,1.1743,1.1722,1.1732,3531 -2017-08-09 09:00:00,1.17316,1.17533,1.173,1.17406,2723 -2017-08-09 10:00:00,1.17405,1.1752,1.1733,1.17366,1968 -2017-08-09 11:00:00,1.17367,1.1742,1.17319,1.17395,2227 -2017-08-09 12:00:00,1.174,1.17474,1.17256,1.1745,5390 -2017-08-09 13:00:00,1.17452,1.1746,1.16888,1.17113,7300 -2017-08-09 14:00:00,1.17114,1.17495,1.17085,1.17433,6682 -2017-08-09 15:00:00,1.17432,1.17486,1.173,1.17482,2526 -2017-08-09 16:00:00,1.17482,1.17496,1.17357,1.17444,1434 -2017-08-09 17:00:00,1.17448,1.17588,1.17397,1.17522,1874 -2017-08-09 18:00:00,1.17524,1.17616,1.17507,1.17524,1237 -2017-08-09 19:00:00,1.1752,1.17564,1.17496,1.17557,774 -2017-08-09 20:00:00,1.17557,1.1761,1.1754,1.1759,934 -2017-08-09 21:00:00,1.17592,1.17616,1.17559,1.17597,1820 -2017-08-09 22:00:00,1.17595,1.17701,1.17566,1.17626,665 -2017-08-09 23:00:00,1.17621,1.17639,1.17578,1.17634,278 -2017-08-10 00:00:00,1.17632,1.1764,1.17516,1.1757,1231 -2017-08-10 01:00:00,1.1757,1.17623,1.17478,1.17534,1202 -2017-08-10 02:00:00,1.17534,1.1755,1.17415,1.17482,849 -2017-08-10 03:00:00,1.17482,1.17486,1.1733,1.17387,853 -2017-08-10 04:00:00,1.17391,1.17395,1.17321,1.1736,787 -2017-08-10 05:00:00,1.17355,1.17388,1.17268,1.17336,1016 -2017-08-10 06:00:00,1.17337,1.17407,1.173,1.17319,1492 -2017-08-10 07:00:00,1.1732,1.17356,1.17156,1.17202,2775 -2017-08-10 08:00:00,1.17204,1.17352,1.17195,1.1723,2175 -2017-08-10 09:00:00,1.17229,1.17229,1.17086,1.17114,2288 -2017-08-10 10:00:00,1.1711,1.17255,1.17042,1.17238,1901 -2017-08-10 11:00:00,1.17234,1.17255,1.17136,1.17255,1705 -2017-08-10 12:00:00,1.1726,1.1748,1.17247,1.17416,4481 -2017-08-10 13:00:00,1.17416,1.17492,1.17304,1.17364,3823 -2017-08-10 14:00:00,1.1736,1.17594,1.17176,1.17502,6918 -2017-08-10 15:00:00,1.17504,1.17578,1.17411,1.1751,2685 -2017-08-10 16:00:00,1.17514,1.1762,1.17483,1.17564,2145 -2017-08-10 17:00:00,1.17567,1.17603,1.17518,1.17554,1294 -2017-08-10 18:00:00,1.17554,1.17752,1.17528,1.177,1600 -2017-08-10 19:00:00,1.17702,1.1785,1.17696,1.17734,2145 -2017-08-10 20:00:00,1.1773,1.17797,1.17715,1.17726,1066 -2017-08-10 21:00:00,1.17733,1.17751,1.17672,1.1772,6568 -2017-08-10 22:00:00,1.17712,1.17716,1.17652,1.17662,666 -2017-08-10 23:00:00,1.17662,1.17706,1.17636,1.177,345 -2017-08-11 00:00:00,1.177,1.17766,1.17682,1.17721,680 -2017-08-11 01:00:00,1.17726,1.17762,1.1765,1.17702,1202 -2017-08-11 02:00:00,1.17697,1.17704,1.17617,1.17688,829 -2017-08-11 03:00:00,1.17684,1.17758,1.17671,1.17754,605 -2017-08-11 04:00:00,1.17752,1.17765,1.17717,1.17746,518 -2017-08-11 05:00:00,1.17746,1.17792,1.17638,1.17644,1074 -2017-08-11 06:00:00,1.1764,1.17694,1.17554,1.17598,2106 -2017-08-11 07:00:00,1.17598,1.17613,1.17496,1.17536,2034 -2017-08-11 08:00:00,1.17532,1.17646,1.17509,1.17556,1590 -2017-08-11 09:00:00,1.17553,1.17584,1.17484,1.17582,1102 -2017-08-11 10:00:00,1.1758,1.1774,1.17554,1.17602,1431 -2017-08-11 11:00:00,1.176,1.17723,1.17581,1.1759,1449 -2017-08-11 12:00:00,1.17588,1.18354,1.17539,1.1816,9521 -2017-08-11 13:00:00,1.1816,1.183,1.17774,1.17984,7655 -2017-08-11 14:00:00,1.17979,1.181,1.17866,1.17927,3898 -2017-08-11 15:00:00,1.17928,1.1811,1.17862,1.18106,2674 -2017-08-11 16:00:00,1.18104,1.18223,1.18054,1.18203,2577 -2017-08-11 17:00:00,1.18203,1.18476,1.18203,1.18374,3727 -2017-08-11 18:00:00,1.18372,1.18393,1.18208,1.18236,1986 -2017-08-11 19:00:00,1.1824,1.1829,1.18202,1.18247,1634 -2017-08-11 20:00:00,1.18247,1.18252,1.18197,1.18219,1029 -2017-08-13 21:00:00,1.1822,1.18288,1.18202,1.1824,766 -2017-08-13 22:00:00,1.18243,1.18248,1.1819,1.18219,797 -2017-08-13 23:00:00,1.18214,1.18265,1.18187,1.18252,588 -2017-08-14 00:00:00,1.18252,1.18292,1.18186,1.1819,1744 -2017-08-14 01:00:00,1.18196,1.18348,1.1817,1.18302,1014 -2017-08-14 02:00:00,1.18302,1.1834,1.18274,1.18275,617 -2017-08-14 03:00:00,1.18276,1.18314,1.18248,1.1827,442 -2017-08-14 04:00:00,1.1827,1.18274,1.18176,1.18184,615 -2017-08-14 05:00:00,1.1818,1.18213,1.18099,1.18196,1013 -2017-08-14 06:00:00,1.18192,1.18331,1.18104,1.18308,2180 -2017-08-14 07:00:00,1.18302,1.18384,1.18007,1.18078,2837 -2017-08-14 08:00:00,1.18074,1.18094,1.17922,1.18034,2480 -2017-08-14 09:00:00,1.18032,1.18072,1.1797,1.17981,1814 -2017-08-14 10:00:00,1.17984,1.1804,1.17912,1.17989,1574 -2017-08-14 11:00:00,1.17991,1.18002,1.17873,1.17923,1817 -2017-08-14 12:00:00,1.17925,1.18,1.17912,1.17956,2030 -2017-08-14 13:00:00,1.17962,1.18018,1.17845,1.17908,2445 -2017-08-14 14:00:00,1.1791,1.1791,1.177,1.17822,3400 -2017-08-14 15:00:00,1.1782,1.17881,1.17745,1.17862,1888 -2017-08-14 16:00:00,1.17858,1.1796,1.17754,1.17933,1066 -2017-08-14 17:00:00,1.1793,1.17952,1.17722,1.17734,1313 -2017-08-14 18:00:00,1.1773,1.17864,1.1773,1.17832,1293 -2017-08-14 19:00:00,1.17836,1.17888,1.17815,1.1785,887 -2017-08-14 20:00:00,1.17846,1.17884,1.17782,1.17804,984 -2017-08-14 21:00:00,1.17799,1.17818,1.17754,1.17761,642 -2017-08-14 22:00:00,1.17766,1.1781,1.17752,1.17785,541 -2017-08-14 23:00:00,1.17782,1.17804,1.17684,1.17756,372 -2017-08-15 00:00:00,1.1776,1.17896,1.17752,1.17814,1495 -2017-08-15 01:00:00,1.17819,1.17928,1.17819,1.17853,1196 -2017-08-15 02:00:00,1.17852,1.1786,1.17816,1.1783,488 -2017-08-15 03:00:00,1.17826,1.17842,1.17802,1.17821,307 -2017-08-15 04:00:00,1.17824,1.17862,1.17768,1.17774,664 -2017-08-15 05:00:00,1.17776,1.17795,1.17598,1.17607,1246 -2017-08-15 06:00:00,1.17605,1.17641,1.17362,1.17429,3132 -2017-08-15 07:00:00,1.17428,1.17474,1.17208,1.17462,3401 -2017-08-15 08:00:00,1.17459,1.17692,1.17442,1.17566,3099 -2017-08-15 09:00:00,1.17562,1.17638,1.17494,1.17496,2251 -2017-08-15 10:00:00,1.17498,1.17524,1.1739,1.17496,1932 -2017-08-15 11:00:00,1.17498,1.17578,1.1734,1.17396,2466 -2017-08-15 12:00:00,1.17396,1.17452,1.16873,1.16918,7711 -2017-08-15 13:00:00,1.16919,1.17243,1.169,1.17072,4514 -2017-08-15 14:00:00,1.1707,1.17194,1.1701,1.17188,3588 -2017-08-15 15:00:00,1.17187,1.17388,1.17142,1.17358,2874 -2017-08-15 16:00:00,1.17354,1.17384,1.17295,1.17371,1378 -2017-08-15 17:00:00,1.17366,1.17434,1.17365,1.17383,1160 -2017-08-15 18:00:00,1.17386,1.1739,1.17274,1.1734,977 -2017-08-15 19:00:00,1.17336,1.17404,1.17328,1.17398,714 -2017-08-15 20:00:00,1.17395,1.17402,1.17324,1.1735,560 -2017-08-15 21:00:00,1.17347,1.17384,1.17336,1.17354,1076 -2017-08-15 22:00:00,1.17357,1.17388,1.17298,1.17374,756 -2017-08-15 23:00:00,1.1737,1.17433,1.17364,1.17406,406 -2017-08-16 00:00:00,1.17404,1.17456,1.17364,1.1738,854 -2017-08-16 01:00:00,1.17384,1.17419,1.17346,1.1739,812 -2017-08-16 02:00:00,1.17391,1.17417,1.1736,1.17364,457 -2017-08-16 03:00:00,1.17362,1.17402,1.17358,1.17396,230 -2017-08-16 04:00:00,1.17394,1.17435,1.1738,1.17426,333 -2017-08-16 05:00:00,1.17424,1.17478,1.17377,1.17417,880 -2017-08-16 06:00:00,1.17418,1.17418,1.1724,1.17308,1612 -2017-08-16 07:00:00,1.1731,1.17582,1.17142,1.17158,4418 -2017-08-16 08:00:00,1.17158,1.17392,1.16914,1.1726,6190 -2017-08-16 09:00:00,1.17258,1.17397,1.17225,1.17235,2450 -2017-08-16 10:00:00,1.17238,1.1724,1.16952,1.17019,2903 -2017-08-16 11:00:00,1.17017,1.1715,1.16984,1.17113,2644 -2017-08-16 12:00:00,1.17114,1.1721,1.17017,1.17031,4292 -2017-08-16 13:00:00,1.17034,1.17066,1.16813,1.16946,4415 -2017-08-16 14:00:00,1.16946,1.17164,1.16934,1.17032,2535 -2017-08-16 15:00:00,1.17032,1.17094,1.16934,1.17018,2475 -2017-08-16 16:00:00,1.17021,1.17044,1.16912,1.17019,1415 -2017-08-16 17:00:00,1.1702,1.17428,1.17006,1.17344,4349 -2017-08-16 18:00:00,1.17346,1.1779,1.1731,1.17684,10190 -2017-08-16 19:00:00,1.1768,1.17736,1.17627,1.17692,1731 -2017-08-16 20:00:00,1.1769,1.17715,1.1766,1.17676,751 -2017-08-16 21:00:00,1.17659,1.17728,1.17656,1.17722,2627 -2017-08-16 22:00:00,1.1772,1.17797,1.17701,1.17772,862 -2017-08-16 23:00:00,1.17768,1.17792,1.177,1.17739,338 -2017-08-17 00:00:00,1.17734,1.17748,1.17648,1.17681,997 -2017-08-17 01:00:00,1.17684,1.17893,1.17668,1.17886,1981 -2017-08-17 02:00:00,1.17889,1.17902,1.17776,1.17824,766 -2017-08-17 03:00:00,1.17819,1.17834,1.17746,1.17776,586 -2017-08-17 04:00:00,1.17776,1.17823,1.17776,1.17792,350 -2017-08-17 05:00:00,1.1779,1.179,1.17755,1.17791,908 -2017-08-17 06:00:00,1.17788,1.17804,1.1763,1.17632,1768 -2017-08-17 07:00:00,1.17628,1.17661,1.17509,1.17558,2359 -2017-08-17 08:00:00,1.17556,1.17561,1.17302,1.17329,2466 -2017-08-17 09:00:00,1.17332,1.17375,1.17038,1.17068,2283 -2017-08-17 10:00:00,1.1707,1.17086,1.169,1.16976,2864 -2017-08-17 11:00:00,1.16972,1.1714,1.16622,1.16996,9062 -2017-08-17 12:00:00,1.16994,1.17045,1.16814,1.16934,5800 -2017-08-17 13:00:00,1.1693,1.17289,1.16924,1.17276,3925 -2017-08-17 14:00:00,1.17276,1.17476,1.17148,1.17452,9502 -2017-08-17 15:00:00,1.17457,1.17458,1.17318,1.17353,3193 -2017-08-17 16:00:00,1.17357,1.1754,1.17321,1.17414,2193 -2017-08-17 17:00:00,1.17412,1.17518,1.17391,1.17418,1855 -2017-08-17 18:00:00,1.17417,1.17514,1.17397,1.17399,1215 -2017-08-17 19:00:00,1.174,1.17472,1.17269,1.17279,2214 -2017-08-17 20:00:00,1.17284,1.17333,1.17179,1.17242,902 -2017-08-17 21:00:00,1.17219,1.17296,1.17182,1.17252,4197 -2017-08-17 22:00:00,1.17252,1.17312,1.17242,1.17267,944 -2017-08-17 23:00:00,1.1727,1.17296,1.17087,1.1716,815 -2017-08-18 00:00:00,1.17163,1.17302,1.17101,1.1728,1937 -2017-08-18 01:00:00,1.17278,1.17352,1.17236,1.17329,920 -2017-08-18 02:00:00,1.17329,1.17364,1.17292,1.17292,531 -2017-08-18 03:00:00,1.17296,1.17359,1.17296,1.17306,446 -2017-08-18 04:00:00,1.17311,1.17397,1.17302,1.17374,626 -2017-08-18 05:00:00,1.17377,1.17408,1.17327,1.17332,896 -2017-08-18 06:00:00,1.1733,1.17413,1.17256,1.17377,2041 -2017-08-18 07:00:00,1.17374,1.17588,1.17213,1.17264,4337 -2017-08-18 08:00:00,1.17265,1.1749,1.17239,1.17472,2435 -2017-08-18 09:00:00,1.17474,1.17749,1.17351,1.17351,4241 -2017-08-18 10:00:00,1.17349,1.17527,1.1734,1.17487,2191 -2017-08-18 11:00:00,1.17491,1.17512,1.17316,1.17346,1962 -2017-08-18 12:00:00,1.1735,1.175,1.1734,1.17484,2714 -2017-08-18 13:00:00,1.17486,1.17551,1.1736,1.17426,4128 -2017-08-18 14:00:00,1.17423,1.17615,1.1737,1.1749,6696 -2017-08-18 15:00:00,1.1749,1.17552,1.17296,1.17478,6549 -2017-08-18 16:00:00,1.17482,1.17552,1.17434,1.17494,4132 -2017-08-18 17:00:00,1.17494,1.17545,1.17405,1.17532,2466 -2017-08-18 18:00:00,1.17536,1.17608,1.17518,1.17586,1193 -2017-08-18 19:00:00,1.17588,1.17676,1.17584,1.17636,1329 -2017-08-18 20:00:00,1.17634,1.1766,1.17588,1.17607,1836 -2017-08-20 21:00:00,1.1755,1.17642,1.17534,1.17583,483 -2017-08-20 22:00:00,1.17588,1.17601,1.17536,1.1754,588 -2017-08-20 23:00:00,1.17533,1.17571,1.17502,1.17558,591 -2017-08-21 00:00:00,1.1756,1.17576,1.1751,1.17516,1149 -2017-08-21 01:00:00,1.1752,1.17598,1.17508,1.17584,965 -2017-08-21 02:00:00,1.17584,1.17628,1.17567,1.17597,624 -2017-08-21 03:00:00,1.17594,1.17598,1.17514,1.17544,503 -2017-08-21 04:00:00,1.17544,1.1758,1.1751,1.17513,374 -2017-08-21 05:00:00,1.17508,1.17552,1.17452,1.17457,604 -2017-08-21 06:00:00,1.17458,1.17483,1.17353,1.17378,1681 -2017-08-21 07:00:00,1.17378,1.17422,1.17314,1.17402,2092 -2017-08-21 08:00:00,1.174,1.17494,1.17386,1.1741,1275 -2017-08-21 09:00:00,1.17408,1.17456,1.17365,1.17398,1058 -2017-08-21 10:00:00,1.17401,1.17584,1.17376,1.17584,1271 -2017-08-21 11:00:00,1.17588,1.177,1.17575,1.17645,1985 -2017-08-21 12:00:00,1.17648,1.1783,1.17594,1.17802,2398 -2017-08-21 13:00:00,1.178,1.17901,1.17774,1.17886,2392 -2017-08-21 14:00:00,1.17886,1.18198,1.17882,1.1815,5162 -2017-08-21 15:00:00,1.1815,1.18252,1.18111,1.18127,2664 -2017-08-21 16:00:00,1.18126,1.18242,1.18094,1.18238,1312 -2017-08-21 17:00:00,1.18241,1.1828,1.18162,1.18186,1208 -2017-08-21 18:00:00,1.18186,1.18226,1.18096,1.18128,1186 -2017-08-21 19:00:00,1.18127,1.18134,1.18072,1.18096,759 -2017-08-21 20:00:00,1.18094,1.18176,1.18072,1.18146,789 -2017-08-21 21:00:00,1.18157,1.18173,1.18103,1.18136,1989 -2017-08-21 22:00:00,1.18139,1.18176,1.18082,1.18093,1066 -2017-08-21 23:00:00,1.18091,1.18157,1.18083,1.18116,412 -2017-08-22 00:00:00,1.18116,1.18174,1.18104,1.18146,940 -2017-08-22 01:00:00,1.18143,1.18244,1.18116,1.1813,1294 -2017-08-22 02:00:00,1.18132,1.18132,1.18044,1.18054,648 -2017-08-22 03:00:00,1.18056,1.18084,1.18028,1.18084,555 -2017-08-22 04:00:00,1.18088,1.18102,1.18062,1.18066,395 -2017-08-22 05:00:00,1.18068,1.1807,1.17958,1.18019,953 -2017-08-22 06:00:00,1.18024,1.18068,1.17906,1.17906,1900 -2017-08-22 07:00:00,1.17902,1.17943,1.17841,1.17934,2028 -2017-08-22 08:00:00,1.17932,1.17932,1.17658,1.17716,2597 -2017-08-22 09:00:00,1.1771,1.17722,1.17548,1.17552,2233 -2017-08-22 10:00:00,1.17554,1.17588,1.17454,1.17532,1645 -2017-08-22 11:00:00,1.17532,1.17692,1.17478,1.17682,2489 -2017-08-22 12:00:00,1.17681,1.17729,1.17531,1.17615,2336 -2017-08-22 13:00:00,1.1761,1.1769,1.17514,1.17538,3010 -2017-08-22 14:00:00,1.1754,1.17668,1.17501,1.17628,3083 -2017-08-22 15:00:00,1.17626,1.17718,1.17613,1.17621,2136 -2017-08-22 16:00:00,1.17618,1.1771,1.17603,1.1764,1133 -2017-08-22 17:00:00,1.17638,1.17647,1.17524,1.17529,1100 -2017-08-22 18:00:00,1.17531,1.17546,1.1748,1.17516,746 -2017-08-22 19:00:00,1.17512,1.17608,1.17496,1.176,974 -2017-08-22 20:00:00,1.17598,1.17642,1.17576,1.17615,938 -2017-08-22 21:00:00,1.17613,1.1766,1.17596,1.1765,2757 -2017-08-22 22:00:00,1.17653,1.17661,1.17596,1.17646,614 -2017-08-22 23:00:00,1.17644,1.17662,1.17612,1.17616,470 -2017-08-23 00:00:00,1.17621,1.17621,1.17492,1.17494,980 -2017-08-23 01:00:00,1.17492,1.17589,1.17476,1.17578,710 -2017-08-23 02:00:00,1.17582,1.17648,1.1754,1.17644,799 -2017-08-23 03:00:00,1.17644,1.17662,1.1759,1.17606,796 -2017-08-23 04:00:00,1.17604,1.17621,1.1757,1.1758,404 -2017-08-23 05:00:00,1.17583,1.1762,1.17574,1.17588,425 -2017-08-23 06:00:00,1.17588,1.176,1.17512,1.17567,1408 -2017-08-23 07:00:00,1.1757,1.17838,1.17402,1.17814,5824 -2017-08-23 08:00:00,1.17812,1.1792,1.17754,1.17901,2482 -2017-08-23 09:00:00,1.17898,1.17942,1.17757,1.17792,1643 -2017-08-23 10:00:00,1.17797,1.17852,1.1777,1.17815,1064 -2017-08-23 11:00:00,1.17815,1.1801,1.17815,1.18,2196 -2017-08-23 12:00:00,1.18006,1.18079,1.17924,1.17948,2399 -2017-08-23 13:00:00,1.17953,1.1799,1.1787,1.17979,2762 -2017-08-23 14:00:00,1.17984,1.182,1.1798,1.18156,3942 -2017-08-23 15:00:00,1.18155,1.1817,1.17998,1.18016,1883 -2017-08-23 16:00:00,1.18014,1.1805,1.17982,1.1801,1015 -2017-08-23 17:00:00,1.18013,1.1816,1.18013,1.18121,1371 -2017-08-23 18:00:00,1.18121,1.18232,1.18073,1.18204,1689 -2017-08-23 19:00:00,1.18199,1.18232,1.18151,1.1818,1348 -2017-08-23 20:00:00,1.1818,1.182,1.18056,1.18071,768 -2017-08-23 21:00:00,1.18088,1.1812,1.18072,1.18092,2328 -2017-08-23 22:00:00,1.18092,1.18134,1.18076,1.18113,790 -2017-08-23 23:00:00,1.18112,1.18182,1.18111,1.18158,612 -2017-08-24 00:00:00,1.18156,1.1817,1.18078,1.18096,1000 -2017-08-24 01:00:00,1.18094,1.18097,1.18006,1.18012,827 -2017-08-24 02:00:00,1.1801,1.18065,1.17946,1.18056,665 -2017-08-24 03:00:00,1.18052,1.18054,1.17967,1.18026,574 -2017-08-24 04:00:00,1.18026,1.18037,1.17988,1.18024,442 -2017-08-24 05:00:00,1.18028,1.18079,1.18009,1.18051,637 -2017-08-24 06:00:00,1.18053,1.18066,1.17876,1.17912,1809 -2017-08-24 07:00:00,1.17906,1.17968,1.17879,1.17936,2066 -2017-08-24 08:00:00,1.17934,1.17984,1.17842,1.17872,1744 -2017-08-24 09:00:00,1.1787,1.1796,1.17858,1.17912,1284 -2017-08-24 10:00:00,1.17914,1.17926,1.17847,1.1792,1179 -2017-08-24 11:00:00,1.1792,1.18104,1.17903,1.18073,1736 -2017-08-24 12:00:00,1.18074,1.18103,1.17946,1.17992,2570 -2017-08-24 13:00:00,1.17992,1.18052,1.17914,1.1801,2049 -2017-08-24 14:00:00,1.18007,1.18058,1.17878,1.18044,3058 -2017-08-24 15:00:00,1.18044,1.18074,1.17983,1.18011,2902 -2017-08-24 16:00:00,1.1801,1.18104,1.1798,1.18042,1451 -2017-08-24 17:00:00,1.18042,1.1815,1.18042,1.18116,1131 -2017-08-24 18:00:00,1.18111,1.18137,1.18022,1.18052,726 -2017-08-24 19:00:00,1.18054,1.1806,1.17982,1.18012,966 -2017-08-24 20:00:00,1.18014,1.18028,1.17984,1.18002,539 -2017-08-24 21:00:00,1.18017,1.18018,1.17984,1.18001,1980 -2017-08-24 22:00:00,1.17999,1.18038,1.17999,1.18038,745 -2017-08-24 23:00:00,1.1804,1.1804,1.17961,1.17978,883 -2017-08-25 00:00:00,1.17972,1.17994,1.17926,1.17964,679 -2017-08-25 01:00:00,1.17964,1.17978,1.17878,1.17898,731 -2017-08-25 02:00:00,1.17898,1.17952,1.17886,1.17945,390 -2017-08-25 03:00:00,1.17948,1.17998,1.17926,1.17972,730 -2017-08-25 04:00:00,1.17977,1.17988,1.1795,1.17981,287 -2017-08-25 05:00:00,1.17976,1.18004,1.17945,1.17969,435 -2017-08-25 06:00:00,1.17964,1.17974,1.17888,1.17913,1127 -2017-08-25 07:00:00,1.17908,1.17908,1.17736,1.1781,2647 -2017-08-25 08:00:00,1.17811,1.18012,1.17796,1.17964,2124 -2017-08-25 09:00:00,1.17962,1.18048,1.17956,1.1804,853 -2017-08-25 10:00:00,1.1804,1.18285,1.18022,1.18172,2469 -2017-08-25 11:00:00,1.18168,1.1823,1.1813,1.18155,1576 -2017-08-25 12:00:00,1.1816,1.18164,1.17998,1.18054,2613 -2017-08-25 13:00:00,1.18058,1.18148,1.17858,1.17978,3579 -2017-08-25 14:00:00,1.17972,1.18752,1.1793,1.18709,13383 -2017-08-25 15:00:00,1.18712,1.18843,1.18682,1.18727,4400 -2017-08-25 16:00:00,1.18727,1.18868,1.18726,1.18866,2745 -2017-08-25 17:00:00,1.18866,1.18898,1.18808,1.18822,1522 -2017-08-25 18:00:00,1.18821,1.18828,1.1872,1.18788,2117 -2017-08-25 19:00:00,1.18788,1.19415,1.18638,1.19245,14104 -2017-08-25 20:00:00,1.19248,1.19345,1.19168,1.19232,2128 -2017-08-27 21:00:00,1.19458,1.19472,1.19408,1.19448,558 -2017-08-27 22:00:00,1.19449,1.19582,1.1941,1.19518,2359 -2017-08-27 23:00:00,1.19518,1.19596,1.19498,1.19511,859 -2017-08-28 00:00:00,1.19516,1.19518,1.19222,1.193,1860 -2017-08-28 01:00:00,1.19301,1.19307,1.19216,1.1927,941 -2017-08-28 02:00:00,1.19268,1.19276,1.19204,1.19252,658 -2017-08-28 03:00:00,1.19254,1.19254,1.1921,1.19218,471 -2017-08-28 04:00:00,1.19214,1.19234,1.19202,1.19204,467 -2017-08-28 05:00:00,1.19199,1.19346,1.19171,1.19342,1123 -2017-08-28 06:00:00,1.19338,1.19372,1.19247,1.19327,1175 -2017-08-28 07:00:00,1.19323,1.19422,1.19214,1.19256,1743 -2017-08-28 08:00:00,1.19261,1.19374,1.19199,1.19308,1382 -2017-08-28 09:00:00,1.19312,1.1937,1.19285,1.19337,1103 -2017-08-28 10:00:00,1.19338,1.19402,1.19326,1.19368,1210 -2017-08-28 11:00:00,1.19366,1.1937,1.19241,1.19254,1749 -2017-08-28 12:00:00,1.19259,1.19384,1.19221,1.19347,2232 -2017-08-28 13:00:00,1.19343,1.19403,1.1926,1.1936,2610 -2017-08-28 14:00:00,1.19354,1.19578,1.19354,1.19548,2386 -2017-08-28 15:00:00,1.19548,1.19756,1.1952,1.19722,3032 -2017-08-28 16:00:00,1.19719,1.19839,1.19719,1.19763,1764 -2017-08-28 17:00:00,1.19764,1.19806,1.19736,1.19772,1220 -2017-08-28 18:00:00,1.19772,1.19839,1.19772,1.19792,833 -2017-08-28 19:00:00,1.19787,1.19797,1.1973,1.19742,739 -2017-08-28 20:00:00,1.1974,1.19786,1.1974,1.19786,459 -2017-08-28 21:00:00,1.19774,1.19846,1.19734,1.1978,3781 -2017-08-28 22:00:00,1.19788,1.19865,1.19628,1.19684,4289 -2017-08-28 23:00:00,1.19686,1.19696,1.19552,1.1964,1947 -2017-08-29 00:00:00,1.19638,1.19725,1.19627,1.19649,2042 -2017-08-29 01:00:00,1.19648,1.19726,1.19624,1.19688,1267 -2017-08-29 02:00:00,1.19688,1.19714,1.19656,1.19698,639 -2017-08-29 03:00:00,1.19696,1.1973,1.19664,1.1969,604 -2017-08-29 04:00:00,1.19694,1.19772,1.19689,1.19746,556 -2017-08-29 05:00:00,1.19744,1.1982,1.19722,1.1982,588 -2017-08-29 06:00:00,1.19822,1.20184,1.19737,1.20167,4793 -2017-08-29 07:00:00,1.20169,1.2047,1.2011,1.20467,8174 -2017-08-29 08:00:00,1.2047,1.20705,1.20409,1.20602,5617 -2017-08-29 09:00:00,1.20598,1.20664,1.2037,1.20392,3508 -2017-08-29 10:00:00,1.20391,1.20536,1.20316,1.20345,2613 -2017-08-29 11:00:00,1.20344,1.20475,1.20326,1.20424,2736 -2017-08-29 12:00:00,1.20428,1.20591,1.20279,1.20291,4561 -2017-08-29 13:00:00,1.20295,1.20341,1.20202,1.20254,4002 -2017-08-29 14:00:00,1.20254,1.20277,1.20094,1.20255,6116 -2017-08-29 15:00:00,1.20254,1.2038,1.2017,1.2025,4022 -2017-08-29 16:00:00,1.20248,1.20251,1.20104,1.20158,2039 -2017-08-29 17:00:00,1.20158,1.20202,1.19956,1.20012,2508 -2017-08-29 18:00:00,1.20016,1.20018,1.1982,1.19912,3104 -2017-08-29 19:00:00,1.19912,1.19969,1.19676,1.19681,2709 -2017-08-29 20:00:00,1.19682,1.19796,1.19461,1.19718,2037 -2017-08-29 21:00:00,1.19714,1.19758,1.19632,1.19677,2495 -2017-08-29 22:00:00,1.19676,1.19782,1.19674,1.19744,1494 -2017-08-29 23:00:00,1.19746,1.19759,1.19631,1.197,1131 -2017-08-30 00:00:00,1.19703,1.19787,1.19668,1.1975,1023 -2017-08-30 01:00:00,1.19744,1.1978,1.19668,1.1975,2363 -2017-08-30 02:00:00,1.19752,1.19792,1.19738,1.19766,623 -2017-08-30 03:00:00,1.19764,1.19831,1.19756,1.19826,415 -2017-08-30 04:00:00,1.19824,1.19845,1.19726,1.19736,575 -2017-08-30 05:00:00,1.19738,1.1975,1.19643,1.19654,1288 -2017-08-30 06:00:00,1.19651,1.19682,1.19414,1.1955,4062 -2017-08-30 07:00:00,1.19549,1.1969,1.19384,1.19564,5065 -2017-08-30 08:00:00,1.19569,1.19569,1.19405,1.19443,2434 -2017-08-30 09:00:00,1.19438,1.19548,1.19393,1.1951,2070 -2017-08-30 10:00:00,1.19505,1.19528,1.19422,1.19481,1445 -2017-08-30 11:00:00,1.19482,1.195,1.19245,1.1927,2973 -2017-08-30 12:00:00,1.1927,1.19316,1.18929,1.19182,7501 -2017-08-30 13:00:00,1.19182,1.19378,1.19086,1.19128,4198 -2017-08-30 14:00:00,1.1913,1.19206,1.18951,1.19122,4099 -2017-08-30 15:00:00,1.19128,1.19288,1.18991,1.19266,3820 -2017-08-30 16:00:00,1.19264,1.19266,1.18984,1.19047,2389 -2017-08-30 17:00:00,1.19044,1.19044,1.18917,1.18987,2192 -2017-08-30 18:00:00,1.18985,1.19015,1.1883,1.18903,1984 -2017-08-30 19:00:00,1.18903,1.18947,1.18862,1.189,1213 -2017-08-30 20:00:00,1.18896,1.18896,1.1881,1.18842,770 -2017-08-30 21:00:00,1.18842,1.18954,1.18815,1.18935,1653 -2017-08-30 22:00:00,1.18939,1.18966,1.18891,1.18958,830 -2017-08-30 23:00:00,1.18958,1.1897,1.18884,1.18908,724 -2017-08-31 00:00:00,1.1891,1.18966,1.18862,1.18936,1594 -2017-08-31 01:00:00,1.18936,1.18976,1.18716,1.18776,2070 -2017-08-31 02:00:00,1.1877,1.18831,1.18741,1.18778,1166 -2017-08-31 03:00:00,1.18784,1.18812,1.18714,1.1874,1023 -2017-08-31 04:00:00,1.18741,1.18824,1.18736,1.1879,531 -2017-08-31 05:00:00,1.18787,1.18806,1.18706,1.18736,769 -2017-08-31 06:00:00,1.18738,1.18956,1.18668,1.18908,2638 -2017-08-31 07:00:00,1.18912,1.19032,1.1884,1.18913,3257 -2017-08-31 08:00:00,1.18911,1.18972,1.18808,1.18964,1979 -2017-08-31 09:00:00,1.18962,1.1906,1.18712,1.18778,3532 -2017-08-31 10:00:00,1.18777,1.18791,1.18445,1.18605,5518 -2017-08-31 11:00:00,1.18608,1.18624,1.18342,1.18372,2895 -2017-08-31 12:00:00,1.18374,1.18528,1.18232,1.18434,4401 -2017-08-31 13:00:00,1.18436,1.18604,1.18359,1.18536,3044 -2017-08-31 14:00:00,1.1854,1.18978,1.18496,1.18899,6006 -2017-08-31 15:00:00,1.18898,1.19084,1.18728,1.18936,7130 -2017-08-31 16:00:00,1.18933,1.18956,1.18706,1.18808,2710 -2017-08-31 17:00:00,1.18808,1.18942,1.18786,1.18921,1765 -2017-08-31 18:00:00,1.18922,1.191,1.189,1.19034,2398 -2017-08-31 19:00:00,1.19038,1.1906,1.1895,1.19052,1967 -2017-08-31 20:00:00,1.19057,1.19126,1.1903,1.1909,963 -2017-08-31 21:00:00,1.1909,1.19224,1.19076,1.19214,3997 -2017-08-31 22:00:00,1.19212,1.19234,1.19118,1.19135,1837 -2017-08-31 23:00:00,1.19134,1.19151,1.19078,1.19094,973 -2017-09-01 00:00:00,1.19088,1.19109,1.19056,1.19102,1318 -2017-09-01 01:00:00,1.19103,1.19114,1.19042,1.19074,1016 -2017-09-01 02:00:00,1.19072,1.19132,1.1905,1.19058,638 -2017-09-01 03:00:00,1.19056,1.19088,1.19006,1.19014,822 -2017-09-01 04:00:00,1.19018,1.19041,1.18951,1.18972,610 -2017-09-01 05:00:00,1.18972,1.18972,1.18878,1.18948,859 -2017-09-01 06:00:00,1.18948,1.19052,1.18824,1.18848,2025 -2017-09-01 07:00:00,1.18849,1.18904,1.18792,1.1886,1589 -2017-09-01 08:00:00,1.18866,1.19019,1.18826,1.18929,2227 -2017-09-01 09:00:00,1.18934,1.19051,1.18914,1.18946,1887 -2017-09-01 10:00:00,1.18946,1.19302,1.18938,1.1915,4211 -2017-09-01 11:00:00,1.19146,1.19252,1.19101,1.19165,2322 -2017-09-01 12:00:00,1.19165,1.198,1.18934,1.19062,18179 -2017-09-01 13:00:00,1.19062,1.19208,1.18644,1.1867,10987 -2017-09-01 14:00:00,1.18668,1.1895,1.18498,1.18778,8530 -2017-09-01 15:00:00,1.1878,1.18894,1.1863,1.18776,4851 -2017-09-01 16:00:00,1.18772,1.18883,1.18555,1.18578,3065 -2017-09-01 17:00:00,1.18584,1.18704,1.18572,1.1868,2282 -2017-09-01 18:00:00,1.18678,1.18754,1.18628,1.18664,1459 -2017-09-01 19:00:00,1.18667,1.1869,1.1863,1.18651,1025 -2017-09-01 20:00:00,1.18648,1.18653,1.18588,1.18598,835 -2017-09-03 21:00:00,1.18842,1.18897,1.18758,1.18789,887 -2017-09-03 22:00:00,1.18776,1.18848,1.18737,1.18784,1727 -2017-09-03 23:00:00,1.18791,1.18842,1.18772,1.18819,1148 -2017-09-04 00:00:00,1.18818,1.18864,1.1878,1.188,1865 -2017-09-04 01:00:00,1.18802,1.189,1.18781,1.18838,1654 -2017-09-04 02:00:00,1.18836,1.18856,1.1878,1.18838,856 -2017-09-04 03:00:00,1.18832,1.18861,1.18792,1.18799,996 -2017-09-04 04:00:00,1.18797,1.18845,1.18785,1.1882,416 -2017-09-04 05:00:00,1.18825,1.18879,1.18812,1.18851,965 -2017-09-04 06:00:00,1.18851,1.1904,1.18824,1.18944,3830 -2017-09-04 07:00:00,1.18948,1.19013,1.18846,1.18993,1987 -2017-09-04 08:00:00,1.18997,1.19208,1.189,1.19184,2343 -2017-09-04 09:00:00,1.19189,1.19224,1.19076,1.19151,1629 -2017-09-04 10:00:00,1.19148,1.19173,1.19013,1.1911,1189 -2017-09-04 11:00:00,1.19108,1.19154,1.19022,1.19098,963 -2017-09-04 12:00:00,1.19099,1.1911,1.1889,1.18966,1413 -2017-09-04 13:00:00,1.18968,1.19064,1.18958,1.19037,1525 -2017-09-04 14:00:00,1.19036,1.19136,1.18954,1.1912,1558 -2017-09-04 15:00:00,1.1912,1.19199,1.19094,1.19162,1192 -2017-09-04 16:00:00,1.1916,1.19198,1.1889,1.18894,2012 -2017-09-04 17:00:00,1.18892,1.19052,1.18888,1.19018,1982 -2017-09-04 18:00:00,1.19024,1.1903,1.18928,1.19022,2520 -2017-09-04 19:00:00,1.19019,1.1903,1.18944,1.18972,2169 -2017-09-04 20:00:00,1.1897,1.19054,1.18916,1.18961,3297 -2017-09-04 21:00:00,1.18961,1.19005,1.1894,1.18966,736 -2017-09-04 22:00:00,1.18969,1.19002,1.18949,1.1898,835 -2017-09-04 23:00:00,1.18978,1.18984,1.189,1.1893,1069 -2017-09-05 00:00:00,1.18935,1.19018,1.1892,1.19,1498 -2017-09-05 01:00:00,1.18996,1.19052,1.18926,1.18972,2363 -2017-09-05 02:00:00,1.18973,1.191,1.18973,1.19064,2721 -2017-09-05 03:00:00,1.19064,1.19103,1.1904,1.19068,2011 -2017-09-05 04:00:00,1.19066,1.19115,1.19048,1.19058,1510 -2017-09-05 05:00:00,1.19062,1.19088,1.19025,1.19053,1053 -2017-09-05 06:00:00,1.19053,1.19088,1.1892,1.19028,2469 -2017-09-05 07:00:00,1.19033,1.19078,1.18684,1.1879,4515 -2017-09-05 08:00:00,1.18788,1.18884,1.18757,1.18847,2257 -2017-09-05 09:00:00,1.1885,1.18854,1.18764,1.18824,1737 -2017-09-05 10:00:00,1.18824,1.19071,1.18816,1.18974,2591 -2017-09-05 11:00:00,1.18977,1.18978,1.18774,1.1889,2304 -2017-09-05 12:00:00,1.18892,1.19047,1.18892,1.19004,3217 -2017-09-05 13:00:00,1.19007,1.19007,1.18868,1.18881,3087 -2017-09-05 14:00:00,1.1888,1.1941,1.1888,1.19184,6114 -2017-09-05 15:00:00,1.19188,1.19248,1.18994,1.19116,3976 -2017-09-05 16:00:00,1.19112,1.19234,1.19014,1.19034,3283 -2017-09-05 17:00:00,1.19035,1.1915,1.1895,1.18964,2753 -2017-09-05 18:00:00,1.1897,1.19214,1.18958,1.192,2389 -2017-09-05 19:00:00,1.19198,1.19304,1.19163,1.19185,2202 -2017-09-05 20:00:00,1.19188,1.19204,1.19106,1.1915,789 -2017-09-05 21:00:00,1.1915,1.1917,1.19094,1.19144,5650 -2017-09-05 22:00:00,1.19146,1.19226,1.19139,1.19206,1088 -2017-09-05 23:00:00,1.19212,1.19246,1.19178,1.19239,651 -2017-09-06 00:00:00,1.19234,1.1925,1.19152,1.19221,1414 -2017-09-06 01:00:00,1.19222,1.19244,1.19032,1.19088,1711 -2017-09-06 02:00:00,1.19082,1.1914,1.19058,1.19121,1065 -2017-09-06 03:00:00,1.19123,1.19151,1.19091,1.19103,1014 -2017-09-06 04:00:00,1.19106,1.19154,1.19066,1.19143,726 -2017-09-06 05:00:00,1.19138,1.19295,1.19098,1.19266,1394 -2017-09-06 06:00:00,1.19264,1.19264,1.19133,1.19218,2171 -2017-09-06 07:00:00,1.19216,1.1941,1.19203,1.19338,2820 -2017-09-06 08:00:00,1.19338,1.19498,1.19328,1.1944,2820 -2017-09-06 09:00:00,1.19441,1.19496,1.19312,1.19354,3074 -2017-09-06 10:00:00,1.19351,1.19478,1.1924,1.19287,2639 -2017-09-06 11:00:00,1.19285,1.19319,1.19192,1.19318,2345 -2017-09-06 12:00:00,1.19322,1.19409,1.19272,1.1932,2891 -2017-09-06 13:00:00,1.1932,1.19342,1.19203,1.19244,2975 -2017-09-06 14:00:00,1.19246,1.19448,1.19136,1.19393,9266 -2017-09-06 15:00:00,1.19394,1.19491,1.19352,1.19404,3491 -2017-09-06 16:00:00,1.19405,1.19504,1.19119,1.19267,5695 -2017-09-06 17:00:00,1.19263,1.19287,1.19142,1.19182,2878 -2017-09-06 18:00:00,1.19182,1.19254,1.19106,1.1912,2471 -2017-09-06 19:00:00,1.19115,1.19166,1.19078,1.1915,1434 -2017-09-06 20:00:00,1.1915,1.19215,1.19117,1.19177,556 -2017-09-06 21:00:00,1.19177,1.19235,1.19156,1.19204,2091 -2017-09-06 22:00:00,1.1921,1.19262,1.19195,1.19254,606 -2017-09-06 23:00:00,1.19256,1.19278,1.19212,1.19264,971 -2017-09-07 00:00:00,1.19263,1.19351,1.19225,1.19229,2543 -2017-09-07 01:00:00,1.19226,1.19245,1.19194,1.1924,1551 -2017-09-07 02:00:00,1.19237,1.19285,1.19222,1.19258,1206 -2017-09-07 03:00:00,1.19257,1.19282,1.19202,1.19256,1050 -2017-09-07 04:00:00,1.19256,1.1927,1.19232,1.1924,648 -2017-09-07 05:00:00,1.19242,1.19272,1.19222,1.19225,814 -2017-09-07 06:00:00,1.19224,1.19283,1.19144,1.19279,1938 -2017-09-07 07:00:00,1.19276,1.1958,1.19266,1.19536,4177 -2017-09-07 08:00:00,1.19535,1.19704,1.19439,1.1959,3561 -2017-09-07 09:00:00,1.19591,1.19829,1.19577,1.19804,2941 -2017-09-07 10:00:00,1.19802,1.19947,1.1975,1.19864,2216 -2017-09-07 11:00:00,1.19862,1.19936,1.19631,1.19738,5632 -2017-09-07 12:00:00,1.19742,1.20534,1.19302,1.20422,32318 -2017-09-07 13:00:00,1.20428,1.20594,1.19729,1.20002,15936 -2017-09-07 14:00:00,1.2,1.20187,1.19964,1.20106,5675 -2017-09-07 15:00:00,1.20106,1.2032,1.20018,1.20264,4980 -2017-09-07 16:00:00,1.20264,1.20298,1.19848,1.19896,4283 -2017-09-07 17:00:00,1.19901,1.20038,1.199,1.19996,2178 -2017-09-07 18:00:00,1.19992,1.20093,1.19929,1.20038,2051 -2017-09-07 19:00:00,1.20038,1.20203,1.20009,1.202,2024 -2017-09-07 20:00:00,1.20196,1.20295,1.20168,1.20241,1348 -2017-09-07 21:00:00,1.20241,1.20261,1.2017,1.20188,3424 -2017-09-07 22:00:00,1.20186,1.2023,1.20184,1.20188,840 -2017-09-07 23:00:00,1.20194,1.20296,1.20176,1.2028,971 -2017-09-08 00:00:00,1.20282,1.20361,1.20239,1.20347,1988 -2017-09-08 01:00:00,1.20347,1.2036,1.20233,1.2024,1895 -2017-09-08 02:00:00,1.2024,1.20901,1.20236,1.20715,5658 -2017-09-08 03:00:00,1.2071,1.20812,1.20634,1.20714,3189 -2017-09-08 04:00:00,1.20716,1.20726,1.20608,1.20696,1668 -2017-09-08 05:00:00,1.20696,1.20928,1.20696,1.20788,6905 -2017-09-08 06:00:00,1.20788,1.20866,1.20514,1.20652,6379 -2017-09-08 07:00:00,1.2065,1.20666,1.20362,1.20483,5615 -2017-09-08 08:00:00,1.20485,1.20692,1.20415,1.20633,4802 -2017-09-08 09:00:00,1.20628,1.20646,1.20508,1.20602,3573 -2017-09-08 10:00:00,1.20603,1.20737,1.20586,1.2069,3569 -2017-09-08 11:00:00,1.2069,1.20704,1.20519,1.2066,3662 -2017-09-08 12:00:00,1.20666,1.20678,1.20347,1.20422,4456 -2017-09-08 13:00:00,1.20425,1.2051,1.20236,1.20274,4072 -2017-09-08 14:00:00,1.20278,1.20394,1.2015,1.2017,6286 -2017-09-08 15:00:00,1.20174,1.20422,1.20174,1.20393,3494 -2017-09-08 16:00:00,1.20392,1.2044,1.20232,1.20264,2076 -2017-09-08 17:00:00,1.20268,1.20328,1.20254,1.20316,1377 -2017-09-08 18:00:00,1.20314,1.20321,1.20251,1.20268,1212 -2017-09-08 19:00:00,1.20268,1.20381,1.20261,1.20264,1603 -2017-09-08 20:00:00,1.20262,1.20384,1.20262,1.20353,1169 -2017-09-10 21:00:00,1.20179,1.2029,1.20179,1.20232,398 -2017-09-10 22:00:00,1.20242,1.2025,1.20122,1.20189,1912 -2017-09-10 23:00:00,1.20192,1.20208,1.20113,1.20172,980 -2017-09-11 00:00:00,1.2017,1.202,1.20108,1.20122,1755 -2017-09-11 01:00:00,1.20124,1.20168,1.19988,1.20064,2217 -2017-09-11 02:00:00,1.20066,1.20187,1.20043,1.2017,1324 -2017-09-11 03:00:00,1.20172,1.2019,1.20107,1.20139,685 -2017-09-11 04:00:00,1.20141,1.20151,1.20045,1.20075,866 -2017-09-11 05:00:00,1.20075,1.20182,1.20052,1.20154,1041 -2017-09-11 06:00:00,1.20154,1.20186,1.2002,1.20083,2465 -2017-09-11 07:00:00,1.20084,1.20168,1.19931,1.20148,4525 -2017-09-11 08:00:00,1.20144,1.20297,1.20119,1.20216,2169 -2017-09-11 09:00:00,1.20215,1.20256,1.201,1.20134,1717 -2017-09-11 10:00:00,1.20131,1.20218,1.20092,1.20112,1492 -2017-09-11 11:00:00,1.20111,1.20142,1.19903,1.19978,2298 -2017-09-11 12:00:00,1.19978,1.20046,1.19793,1.19844,3564 -2017-09-11 13:00:00,1.19843,1.19913,1.19714,1.19879,3288 -2017-09-11 14:00:00,1.19882,1.19931,1.19794,1.19829,2938 -2017-09-11 15:00:00,1.19827,1.1987,1.19606,1.19631,2950 -2017-09-11 16:00:00,1.19632,1.19701,1.1957,1.19695,1607 -2017-09-11 17:00:00,1.19698,1.19708,1.19592,1.19632,2152 -2017-09-11 18:00:00,1.19635,1.19697,1.1962,1.19625,1112 -2017-09-11 19:00:00,1.19622,1.19635,1.19493,1.19527,1210 -2017-09-11 20:00:00,1.19524,1.19555,1.1948,1.19538,621 -2017-09-11 21:00:00,1.19538,1.1956,1.19514,1.1955,690 -2017-09-11 22:00:00,1.19553,1.19633,1.19546,1.19627,882 -2017-09-11 23:00:00,1.19622,1.19646,1.19578,1.1958,721 -2017-09-12 00:00:00,1.19579,1.1961,1.19454,1.19473,2043 -2017-09-12 01:00:00,1.19476,1.19558,1.19476,1.19548,1092 -2017-09-12 02:00:00,1.19552,1.19622,1.19525,1.19611,788 -2017-09-12 03:00:00,1.1961,1.19634,1.19538,1.19548,769 -2017-09-12 04:00:00,1.19548,1.19596,1.19534,1.19554,526 -2017-09-12 05:00:00,1.19554,1.19602,1.19469,1.19586,964 -2017-09-12 06:00:00,1.19586,1.19776,1.19558,1.1975,3121 -2017-09-12 07:00:00,1.19754,1.19782,1.19654,1.19746,2945 -2017-09-12 08:00:00,1.19748,1.1975,1.19538,1.19581,3477 -2017-09-12 09:00:00,1.19578,1.19646,1.19498,1.19614,2354 -2017-09-12 10:00:00,1.1961,1.19648,1.19318,1.19366,3632 -2017-09-12 11:00:00,1.19366,1.19386,1.19264,1.19319,3104 -2017-09-12 12:00:00,1.19323,1.19424,1.1928,1.19299,4306 -2017-09-12 13:00:00,1.19298,1.19515,1.19298,1.19462,3144 -2017-09-12 14:00:00,1.19462,1.19683,1.19424,1.1954,4194 -2017-09-12 15:00:00,1.19541,1.19724,1.19515,1.19678,2453 -2017-09-12 16:00:00,1.19682,1.19738,1.19562,1.1963,2775 -2017-09-12 17:00:00,1.19634,1.19665,1.19544,1.19601,2156 -2017-09-12 18:00:00,1.19602,1.1973,1.1959,1.19696,1821 -2017-09-12 19:00:00,1.197,1.19716,1.196,1.19666,1691 -2017-09-12 20:00:00,1.1967,1.19681,1.1962,1.19666,825 -2017-09-12 21:00:00,1.19666,1.1969,1.19602,1.19654,3917 -2017-09-12 22:00:00,1.19656,1.19722,1.19642,1.1972,598 -2017-09-12 23:00:00,1.19718,1.1973,1.19644,1.19712,978 -2017-09-13 00:00:00,1.19718,1.19739,1.19663,1.19699,2315 -2017-09-13 01:00:00,1.19697,1.19934,1.19692,1.19842,1547 -2017-09-13 02:00:00,1.19836,1.1988,1.1977,1.19856,1430 -2017-09-13 03:00:00,1.19852,1.19853,1.19759,1.19828,1357 -2017-09-13 04:00:00,1.19823,1.19897,1.19804,1.19832,1155 -2017-09-13 05:00:00,1.19831,1.19839,1.19752,1.19789,945 -2017-09-13 06:00:00,1.19789,1.199,1.19719,1.19737,2801 -2017-09-13 07:00:00,1.19732,1.19897,1.19687,1.19846,2585 -2017-09-13 08:00:00,1.19844,1.19951,1.19787,1.19794,2451 -2017-09-13 09:00:00,1.19799,1.19833,1.19645,1.1972,1922 -2017-09-13 10:00:00,1.19721,1.19866,1.19708,1.19864,1495 -2017-09-13 11:00:00,1.19868,1.19876,1.1979,1.19855,1356 -2017-09-13 12:00:00,1.19856,1.19898,1.19699,1.19738,3457 -2017-09-13 13:00:00,1.19734,1.19748,1.19378,1.19378,4414 -2017-09-13 14:00:00,1.19375,1.19405,1.19044,1.19164,5398 -2017-09-13 15:00:00,1.19161,1.19184,1.18847,1.18984,3794 -2017-09-13 16:00:00,1.18989,1.19011,1.188,1.18811,1721 -2017-09-13 17:00:00,1.1881,1.18957,1.18798,1.18864,3478 -2017-09-13 18:00:00,1.18864,1.18864,1.1873,1.1874,1310 -2017-09-13 19:00:00,1.1874,1.1886,1.18728,1.18844,1178 -2017-09-13 20:00:00,1.1884,1.18876,1.18804,1.18856,676 -2017-09-13 21:00:00,1.18856,1.18914,1.18824,1.18886,2994 -2017-09-13 22:00:00,1.18886,1.18942,1.18846,1.18938,465 -2017-09-13 23:00:00,1.18932,1.18942,1.18865,1.1888,454 -2017-09-14 00:00:00,1.18886,1.18918,1.18814,1.1883,1626 -2017-09-14 01:00:00,1.18828,1.18836,1.18704,1.18764,1794 -2017-09-14 02:00:00,1.18758,1.18852,1.18726,1.18758,1196 -2017-09-14 03:00:00,1.18764,1.18794,1.18706,1.1875,771 -2017-09-14 04:00:00,1.18756,1.18792,1.18728,1.18782,663 -2017-09-14 05:00:00,1.1878,1.1878,1.1866,1.18758,933 -2017-09-14 06:00:00,1.18758,1.1887,1.18683,1.18846,3950 -2017-09-14 07:00:00,1.18844,1.19098,1.188,1.19056,3187 -2017-09-14 08:00:00,1.19062,1.19062,1.18944,1.19045,2004 -2017-09-14 09:00:00,1.1905,1.19075,1.18918,1.18958,1466 -2017-09-14 10:00:00,1.18955,1.19044,1.18944,1.1901,1547 -2017-09-14 11:00:00,1.19011,1.19028,1.18777,1.1892,5752 -2017-09-14 12:00:00,1.18925,1.19088,1.18373,1.18928,16798 -2017-09-14 13:00:00,1.18924,1.18982,1.18684,1.1883,7276 -2017-09-14 14:00:00,1.18833,1.18976,1.18709,1.1873,4456 -2017-09-14 15:00:00,1.1873,1.18886,1.18702,1.1886,3535 -2017-09-14 16:00:00,1.18858,1.18892,1.1875,1.1884,1486 -2017-09-14 17:00:00,1.18842,1.19226,1.18835,1.19184,3456 -2017-09-14 18:00:00,1.1918,1.19199,1.1912,1.19134,1664 -2017-09-14 19:00:00,1.19134,1.19143,1.19025,1.19053,1440 -2017-09-14 20:00:00,1.19055,1.19204,1.19032,1.19182,1179 -2017-09-14 21:00:00,1.19182,1.19216,1.19108,1.19142,2896 -2017-09-14 22:00:00,1.1915,1.19233,1.19066,1.19192,3203 -2017-09-14 23:00:00,1.19192,1.19218,1.19155,1.19213,1391 -2017-09-15 00:00:00,1.19218,1.19242,1.19072,1.19084,1821 -2017-09-15 01:00:00,1.1909,1.19122,1.19008,1.1906,1390 -2017-09-15 02:00:00,1.1906,1.19182,1.19056,1.19153,660 -2017-09-15 03:00:00,1.1915,1.19158,1.19048,1.19084,969 -2017-09-15 04:00:00,1.19089,1.1913,1.19047,1.19126,848 -2017-09-15 05:00:00,1.19126,1.19206,1.19099,1.192,998 -2017-09-15 06:00:00,1.19198,1.19296,1.19054,1.19234,3679 -2017-09-15 07:00:00,1.19228,1.19302,1.19128,1.19208,3028 -2017-09-15 08:00:00,1.19206,1.194,1.19135,1.19296,2985 -2017-09-15 09:00:00,1.19292,1.19558,1.19267,1.1938,5707 -2017-09-15 10:00:00,1.1938,1.19514,1.1937,1.19505,2739 -2017-09-15 11:00:00,1.195,1.19636,1.19487,1.19491,2288 -2017-09-15 12:00:00,1.19496,1.19877,1.19483,1.19741,7045 -2017-09-15 13:00:00,1.19746,1.19866,1.19641,1.19764,3882 -2017-09-15 14:00:00,1.1977,1.19784,1.19595,1.19636,4542 -2017-09-15 15:00:00,1.19636,1.19674,1.1954,1.19584,2551 -2017-09-15 16:00:00,1.19588,1.19731,1.19398,1.19453,2341 -2017-09-15 17:00:00,1.19458,1.19458,1.19307,1.19364,1492 -2017-09-15 18:00:00,1.1937,1.1943,1.19297,1.19408,1408 -2017-09-15 19:00:00,1.19405,1.19464,1.1935,1.19455,995 -2017-09-15 20:00:00,1.19456,1.19608,1.19444,1.19476,1416 -2017-09-17 21:00:00,1.19205,1.19366,1.19205,1.19344,640 -2017-09-17 22:00:00,1.19345,1.195,1.19342,1.19431,1912 -2017-09-17 23:00:00,1.19432,1.19468,1.19337,1.19379,693 -2017-09-18 00:00:00,1.19376,1.19456,1.19365,1.19442,592 -2017-09-18 01:00:00,1.19444,1.19496,1.19426,1.19488,752 -2017-09-18 02:00:00,1.19489,1.19552,1.19451,1.19455,1236 -2017-09-18 03:00:00,1.19458,1.19471,1.19402,1.19442,494 -2017-09-18 04:00:00,1.1944,1.19458,1.1939,1.1941,506 -2017-09-18 05:00:00,1.1941,1.1947,1.19383,1.19436,748 -2017-09-18 06:00:00,1.19441,1.1956,1.19393,1.19482,2268 -2017-09-18 07:00:00,1.19483,1.19514,1.19152,1.19256,3522 -2017-09-18 08:00:00,1.19254,1.19418,1.19229,1.19394,2189 -2017-09-18 09:00:00,1.19396,1.19536,1.19371,1.1951,2118 -2017-09-18 10:00:00,1.19508,1.19611,1.19428,1.19575,1823 -2017-09-18 11:00:00,1.1957,1.19692,1.19423,1.19438,2407 -2017-09-18 12:00:00,1.19436,1.19639,1.19418,1.19614,1959 -2017-09-18 13:00:00,1.19612,1.19634,1.19467,1.19602,2346 -2017-09-18 14:00:00,1.196,1.19668,1.19464,1.19558,2571 -2017-09-18 15:00:00,1.19554,1.19637,1.19349,1.19396,3685 -2017-09-18 16:00:00,1.19394,1.19394,1.19227,1.19344,2457 -2017-09-18 17:00:00,1.19346,1.19423,1.19328,1.19368,1203 -2017-09-18 18:00:00,1.19368,1.19542,1.19276,1.19504,3037 -2017-09-18 19:00:00,1.19503,1.19578,1.19456,1.1953,1580 -2017-09-18 20:00:00,1.19531,1.19588,1.19503,1.19546,707 -2017-09-18 21:00:00,1.19546,1.19564,1.19497,1.19515,1868 -2017-09-18 22:00:00,1.19525,1.19583,1.19518,1.19566,803 -2017-09-18 23:00:00,1.19568,1.19615,1.19562,1.19602,679 -2017-09-19 00:00:00,1.19602,1.19667,1.19586,1.19642,1022 -2017-09-19 01:00:00,1.19644,1.1975,1.1964,1.1968,1818 -2017-09-19 02:00:00,1.19678,1.19705,1.19621,1.19664,833 -2017-09-19 03:00:00,1.19662,1.19707,1.19649,1.19707,825 -2017-09-19 04:00:00,1.19704,1.19796,1.19677,1.19758,1092 -2017-09-19 05:00:00,1.19759,1.19922,1.19742,1.1983,1927 -2017-09-19 06:00:00,1.1983,1.20058,1.1978,1.1995,3640 -2017-09-19 07:00:00,1.1995,1.20067,1.19825,1.19938,3419 -2017-09-19 08:00:00,1.19936,1.20036,1.19718,1.19841,3906 -2017-09-19 09:00:00,1.19842,1.19934,1.1982,1.1989,3139 -2017-09-19 10:00:00,1.19894,1.19948,1.19828,1.19904,2061 -2017-09-19 11:00:00,1.19899,1.19927,1.19537,1.19724,6637 -2017-09-19 12:00:00,1.1972,1.1993,1.19639,1.19844,5105 -2017-09-19 13:00:00,1.19838,1.19908,1.1976,1.19854,3239 -2017-09-19 14:00:00,1.19856,1.19868,1.19726,1.19778,4267 -2017-09-19 15:00:00,1.19778,1.19818,1.1967,1.19805,2471 -2017-09-19 16:00:00,1.19802,1.19876,1.19608,1.1974,2821 -2017-09-19 17:00:00,1.19742,1.20006,1.19705,1.19954,2202 -2017-09-19 18:00:00,1.19952,1.20067,1.19926,1.19957,2303 -2017-09-19 19:00:00,1.19958,1.20002,1.1993,1.19976,1235 -2017-09-19 20:00:00,1.19973,1.19979,1.19924,1.19946,696 -2017-09-19 21:00:00,1.19946,1.19981,1.19909,1.19956,3446 -2017-09-19 22:00:00,1.19959,1.19972,1.19934,1.1995,348 -2017-09-19 23:00:00,1.1995,1.20008,1.19906,1.19926,571 -2017-09-20 00:00:00,1.19922,1.19952,1.19868,1.1992,1121 -2017-09-20 01:00:00,1.19924,1.202,1.19908,1.20144,2952 -2017-09-20 02:00:00,1.20144,1.20178,1.20069,1.2008,1400 -2017-09-20 03:00:00,1.2008,1.2011,1.20062,1.20082,751 -2017-09-20 04:00:00,1.20082,1.20098,1.20038,1.20074,544 -2017-09-20 05:00:00,1.20071,1.20148,1.20055,1.20097,996 -2017-09-20 06:00:00,1.20096,1.2016,1.19968,1.19998,2582 -2017-09-20 07:00:00,1.19996,1.20141,1.19959,1.19992,2257 -2017-09-20 08:00:00,1.19988,1.20124,1.19976,1.20072,2641 -2017-09-20 09:00:00,1.20072,1.2022,1.20058,1.20126,2573 -2017-09-20 10:00:00,1.20128,1.20134,1.20006,1.20055,1672 -2017-09-20 11:00:00,1.20052,1.20088,1.20014,1.20052,1366 -2017-09-20 12:00:00,1.2005,1.20118,1.19891,1.19922,2403 -2017-09-20 13:00:00,1.1992,1.20026,1.19912,1.19958,1876 -2017-09-20 14:00:00,1.19958,1.2002,1.19918,1.19952,3213 -2017-09-20 15:00:00,1.1995,1.20013,1.1984,1.19976,2571 -2017-09-20 16:00:00,1.1998,1.2006,1.19976,1.20044,1392 -2017-09-20 17:00:00,1.20044,1.20159,1.1997,1.20144,1995 -2017-09-20 18:00:00,1.20143,1.20353,1.18616,1.18906,31470 -2017-09-20 19:00:00,1.18906,1.18986,1.1868,1.18916,9391 -2017-09-20 20:00:00,1.18914,1.19021,1.18906,1.18932,2268 -2017-09-20 21:00:00,1.18932,1.1898,1.1884,1.18946,4843 -2017-09-20 22:00:00,1.18944,1.18959,1.18858,1.189,1165 -2017-09-20 23:00:00,1.189,1.18913,1.18662,1.18745,1289 -2017-09-21 00:00:00,1.18741,1.1883,1.1866,1.18775,2150 -2017-09-21 01:00:00,1.18779,1.18836,1.18672,1.18754,2007 -2017-09-21 02:00:00,1.18758,1.18856,1.18711,1.18851,1348 -2017-09-21 03:00:00,1.18852,1.18914,1.18813,1.18852,1505 -2017-09-21 04:00:00,1.18857,1.18871,1.18818,1.18835,688 -2017-09-21 05:00:00,1.18836,1.1887,1.18766,1.1883,1850 -2017-09-21 06:00:00,1.1883,1.19008,1.18794,1.18966,3835 -2017-09-21 07:00:00,1.18966,1.19075,1.18762,1.19023,3603 -2017-09-21 08:00:00,1.19028,1.19184,1.19014,1.19136,2423 -2017-09-21 09:00:00,1.19132,1.19193,1.19078,1.19134,1611 -2017-09-21 10:00:00,1.19138,1.19153,1.19026,1.19028,1856 -2017-09-21 11:00:00,1.19026,1.19049,1.18906,1.19022,2217 -2017-09-21 12:00:00,1.19025,1.19228,1.18984,1.1917,3921 -2017-09-21 13:00:00,1.19169,1.19291,1.19086,1.19248,4113 -2017-09-21 14:00:00,1.19242,1.1926,1.19098,1.19224,3686 -2017-09-21 15:00:00,1.19228,1.19538,1.19168,1.19467,4004 -2017-09-21 16:00:00,1.19464,1.19502,1.19317,1.1933,2429 -2017-09-21 17:00:00,1.19329,1.1939,1.19282,1.19354,1550 -2017-09-21 18:00:00,1.19354,1.19354,1.19302,1.19307,845 -2017-09-21 19:00:00,1.1931,1.1937,1.1931,1.19312,771 -2017-09-21 20:00:00,1.19317,1.19426,1.19317,1.1942,612 -2017-09-21 21:00:00,1.1942,1.19426,1.19366,1.19402,1680 -2017-09-21 22:00:00,1.19399,1.19432,1.19378,1.1941,492 -2017-09-21 23:00:00,1.19406,1.19488,1.194,1.19448,509 -2017-09-22 00:00:00,1.19448,1.19468,1.19396,1.19416,1189 -2017-09-22 01:00:00,1.19416,1.19585,1.19409,1.19544,1702 -2017-09-22 02:00:00,1.19548,1.19597,1.19493,1.19558,1236 -2017-09-22 03:00:00,1.1956,1.19588,1.19529,1.19575,731 -2017-09-22 04:00:00,1.1957,1.19648,1.19541,1.19602,667 -2017-09-22 05:00:00,1.19598,1.197,1.19582,1.19678,1128 -2017-09-22 06:00:00,1.19678,1.19744,1.19577,1.19702,2671 -2017-09-22 07:00:00,1.19704,1.19982,1.1965,1.19924,4304 -2017-09-22 08:00:00,1.19918,1.2003,1.19874,1.19903,2752 -2017-09-22 09:00:00,1.19901,1.19952,1.19769,1.19952,2697 -2017-09-22 10:00:00,1.19954,1.20044,1.1959,1.1966,2944 -2017-09-22 11:00:00,1.19658,1.19805,1.1961,1.19628,3265 -2017-09-22 12:00:00,1.19633,1.1975,1.19588,1.19715,3000 -2017-09-22 13:00:00,1.19714,1.19741,1.19582,1.19682,5007 -2017-09-22 14:00:00,1.19681,1.19838,1.1965,1.1968,3581 -2017-09-22 15:00:00,1.19676,1.19727,1.19592,1.19688,2296 -2017-09-22 16:00:00,1.19692,1.19698,1.19374,1.19448,2640 -2017-09-22 17:00:00,1.19449,1.19493,1.19399,1.19468,1019 -2017-09-22 18:00:00,1.19466,1.1954,1.1941,1.1943,1232 -2017-09-22 19:00:00,1.19431,1.19464,1.19402,1.19442,1157 -2017-09-22 20:00:00,1.1944,1.19544,1.19424,1.19478,2834 -2017-09-24 21:00:00,1.18988,1.19152,1.18963,1.19149,838 -2017-09-24 22:00:00,1.1916,1.19253,1.19141,1.19221,1668 -2017-09-24 23:00:00,1.19221,1.19272,1.19185,1.19266,1450 -2017-09-25 00:00:00,1.19266,1.19348,1.19258,1.19282,1512 -2017-09-25 01:00:00,1.19284,1.19326,1.19186,1.19302,1456 -2017-09-25 02:00:00,1.19296,1.19337,1.19276,1.19312,753 -2017-09-25 03:00:00,1.19315,1.1933,1.19277,1.19326,869 -2017-09-25 04:00:00,1.19324,1.19363,1.19316,1.1933,680 -2017-09-25 05:00:00,1.1933,1.19357,1.19248,1.19279,1040 -2017-09-25 06:00:00,1.19279,1.19312,1.19036,1.19099,2720 -2017-09-25 07:00:00,1.19099,1.19208,1.19002,1.191,3312 -2017-09-25 08:00:00,1.19093,1.1915,1.18987,1.19052,2788 -2017-09-25 09:00:00,1.19048,1.19066,1.188,1.18864,3398 -2017-09-25 10:00:00,1.18868,1.18894,1.18691,1.18764,2309 -2017-09-25 11:00:00,1.18764,1.1881,1.18665,1.18708,2395 -2017-09-25 12:00:00,1.18703,1.18776,1.18642,1.18731,2830 -2017-09-25 13:00:00,1.18732,1.189,1.18621,1.18793,4545 -2017-09-25 14:00:00,1.18798,1.18886,1.18647,1.18662,4265 -2017-09-25 15:00:00,1.18662,1.18726,1.18498,1.18513,5808 -2017-09-25 16:00:00,1.18517,1.18528,1.18318,1.18452,3959 -2017-09-25 17:00:00,1.18454,1.18454,1.1837,1.18406,1392 -2017-09-25 18:00:00,1.18404,1.18467,1.18385,1.1845,889 -2017-09-25 19:00:00,1.18452,1.18556,1.18445,1.18477,1296 -2017-09-25 20:00:00,1.1848,1.18496,1.18452,1.1848,497 -2017-09-25 21:00:00,1.1848,1.18514,1.18442,1.18464,4298 -2017-09-25 22:00:00,1.18458,1.1857,1.18456,1.1856,2150 -2017-09-25 23:00:00,1.18557,1.18576,1.18521,1.18561,892 -2017-09-26 00:00:00,1.18559,1.18595,1.185,1.18543,1434 -2017-09-26 01:00:00,1.18538,1.18603,1.18527,1.18586,988 -2017-09-26 02:00:00,1.18587,1.18612,1.18545,1.18582,724 -2017-09-26 03:00:00,1.18582,1.18616,1.18574,1.18614,458 -2017-09-26 04:00:00,1.18614,1.18615,1.18533,1.18537,477 -2017-09-26 05:00:00,1.18538,1.1854,1.18362,1.18408,1167 -2017-09-26 06:00:00,1.18408,1.1859,1.18398,1.18461,2686 -2017-09-26 07:00:00,1.18458,1.18467,1.18104,1.18127,5594 -2017-09-26 08:00:00,1.18123,1.18195,1.18098,1.1817,2229 -2017-09-26 09:00:00,1.1817,1.1829,1.18129,1.18148,2153 -2017-09-26 10:00:00,1.18143,1.18164,1.17859,1.179,3341 -2017-09-26 11:00:00,1.17902,1.17979,1.17824,1.17888,2342 -2017-09-26 12:00:00,1.17885,1.17958,1.17809,1.17916,2483 -2017-09-26 13:00:00,1.17916,1.17976,1.178,1.1781,2146 -2017-09-26 14:00:00,1.1781,1.17903,1.17642,1.17659,3825 -2017-09-26 15:00:00,1.1766,1.17744,1.17659,1.17704,2203 -2017-09-26 16:00:00,1.17702,1.17956,1.17573,1.17824,6531 -2017-09-26 17:00:00,1.17824,1.18106,1.17817,1.18096,4247 -2017-09-26 18:00:00,1.18096,1.18105,1.1794,1.17988,1860 -2017-09-26 19:00:00,1.17986,1.17991,1.17872,1.17927,1380 -2017-09-26 20:00:00,1.17926,1.17948,1.17854,1.17935,1023 -2017-09-26 21:00:00,1.17921,1.17942,1.17894,1.17914,1975 -2017-09-26 22:00:00,1.17922,1.17928,1.17892,1.17902,607 -2017-09-26 23:00:00,1.17902,1.17904,1.17822,1.17844,1032 -2017-09-27 00:00:00,1.17843,1.1788,1.17768,1.1788,1600 -2017-09-27 01:00:00,1.17886,1.17955,1.17868,1.17891,1157 -2017-09-27 02:00:00,1.17887,1.17902,1.17868,1.17889,785 -2017-09-27 03:00:00,1.17886,1.17921,1.17858,1.17911,787 -2017-09-27 04:00:00,1.17914,1.17922,1.17778,1.17796,884 -2017-09-27 05:00:00,1.1779,1.17841,1.17707,1.17746,1476 -2017-09-27 06:00:00,1.17746,1.17792,1.17564,1.17588,3062 -2017-09-27 07:00:00,1.17593,1.176,1.17422,1.17568,3721 -2017-09-27 08:00:00,1.17566,1.17575,1.1731,1.17359,3468 -2017-09-27 09:00:00,1.17354,1.17496,1.17343,1.17486,2375 -2017-09-27 10:00:00,1.17482,1.1757,1.17452,1.17463,2036 -2017-09-27 11:00:00,1.17468,1.1747,1.17326,1.17448,2240 -2017-09-27 12:00:00,1.17446,1.17457,1.17181,1.172,3458 -2017-09-27 13:00:00,1.172,1.173,1.1717,1.17254,3131 -2017-09-27 14:00:00,1.17254,1.17463,1.17181,1.1732,4794 -2017-09-27 15:00:00,1.17322,1.175,1.17281,1.17467,3269 -2017-09-27 16:00:00,1.17464,1.17765,1.17456,1.17522,3434 -2017-09-27 17:00:00,1.17521,1.17654,1.17479,1.17582,1845 -2017-09-27 18:00:00,1.17584,1.17642,1.17496,1.17572,2151 -2017-09-27 19:00:00,1.17573,1.17576,1.17458,1.17496,2184 -2017-09-27 20:00:00,1.17496,1.17544,1.17442,1.17451,1163 -2017-09-27 21:00:00,1.1747,1.17516,1.17424,1.17446,2137 -2017-09-27 22:00:00,1.17444,1.1748,1.17405,1.1742,1173 -2017-09-27 23:00:00,1.17424,1.17511,1.1742,1.17495,963 -2017-09-28 00:00:00,1.17496,1.17564,1.17468,1.17484,1776 -2017-09-28 01:00:00,1.1749,1.17513,1.17333,1.17385,1826 -2017-09-28 02:00:00,1.1738,1.17434,1.17364,1.17402,876 -2017-09-28 03:00:00,1.17397,1.17414,1.17267,1.17306,1293 -2017-09-28 04:00:00,1.17308,1.17346,1.17268,1.17318,1210 -2017-09-28 05:00:00,1.17317,1.17363,1.17208,1.17256,1796 -2017-09-28 06:00:00,1.17256,1.17516,1.17214,1.17422,3128 -2017-09-28 07:00:00,1.17421,1.17569,1.17241,1.1755,4316 -2017-09-28 08:00:00,1.17544,1.17722,1.17496,1.17664,3769 -2017-09-28 09:00:00,1.17666,1.17748,1.17588,1.17669,2482 -2017-09-28 10:00:00,1.17672,1.17837,1.17636,1.1779,2880 -2017-09-28 11:00:00,1.17786,1.17846,1.17737,1.17738,2165 -2017-09-28 12:00:00,1.17734,1.17846,1.17664,1.1767,3580 -2017-09-28 13:00:00,1.17666,1.17955,1.17664,1.17953,2949 -2017-09-28 14:00:00,1.17954,1.1804,1.17804,1.17843,4300 -2017-09-28 15:00:00,1.17848,1.17925,1.17764,1.17766,3048 -2017-09-28 16:00:00,1.17768,1.17867,1.17728,1.1784,1794 -2017-09-28 17:00:00,1.17838,1.17919,1.17794,1.1789,1217 -2017-09-28 18:00:00,1.17889,1.17934,1.17823,1.17913,1558 -2017-09-28 19:00:00,1.1791,1.17913,1.17782,1.17784,1155 -2017-09-28 20:00:00,1.17779,1.17872,1.17779,1.17862,840 -2017-09-28 21:00:00,1.17862,1.17889,1.1781,1.1784,2164 -2017-09-28 22:00:00,1.17838,1.17848,1.17812,1.17814,624 -2017-09-28 23:00:00,1.17813,1.17832,1.17782,1.1781,831 -2017-09-29 00:00:00,1.17811,1.17891,1.17773,1.17864,1362 -2017-09-29 01:00:00,1.17858,1.17907,1.17794,1.17798,921 -2017-09-29 02:00:00,1.178,1.17826,1.17758,1.17761,1073 -2017-09-29 03:00:00,1.17762,1.17852,1.17758,1.17842,508 -2017-09-29 04:00:00,1.1784,1.17864,1.17784,1.17792,678 -2017-09-29 05:00:00,1.17792,1.17811,1.17732,1.17744,941 -2017-09-29 06:00:00,1.17748,1.18012,1.17728,1.17961,2415 -2017-09-29 07:00:00,1.17956,1.18087,1.17882,1.17944,3293 -2017-09-29 08:00:00,1.17944,1.18059,1.17933,1.17992,1897 -2017-09-29 09:00:00,1.1799,1.18021,1.1789,1.18014,2030 -2017-09-29 10:00:00,1.18014,1.18146,1.17987,1.18129,1550 -2017-09-29 11:00:00,1.18126,1.18187,1.18104,1.18127,1633 -2017-09-29 12:00:00,1.18128,1.18328,1.18022,1.18296,4310 -2017-09-29 13:00:00,1.18295,1.18321,1.17913,1.17956,5025 -2017-09-29 14:00:00,1.17962,1.18248,1.17944,1.18205,6245 -2017-09-29 15:00:00,1.1821,1.1823,1.18088,1.18125,3238 -2017-09-29 16:00:00,1.18126,1.18136,1.17997,1.1803,1650 -2017-09-29 17:00:00,1.18026,1.1811,1.17998,1.18041,1133 -2017-09-29 18:00:00,1.18038,1.18242,1.18031,1.18123,1911 -2017-09-29 19:00:00,1.18124,1.18259,1.1812,1.18194,1850 -2017-09-29 20:00:00,1.18198,1.18237,1.1811,1.1815,2723 -2017-10-01 21:00:00,1.17919,1.1809,1.1789,1.1806,818 -2017-10-01 22:00:00,1.1806,1.18156,1.18018,1.18112,2157 -2017-10-01 23:00:00,1.18107,1.18116,1.1806,1.18082,852 -2017-10-02 00:00:00,1.18076,1.1808,1.1788,1.17896,1537 -2017-10-02 01:00:00,1.17897,1.17911,1.17704,1.17743,1577 -2017-10-02 02:00:00,1.17738,1.17801,1.17719,1.17758,984 -2017-10-02 03:00:00,1.17764,1.1779,1.17734,1.17783,572 -2017-10-02 04:00:00,1.17784,1.17804,1.17736,1.17766,564 -2017-10-02 05:00:00,1.17766,1.17768,1.17606,1.17633,1311 -2017-10-02 06:00:00,1.17633,1.17687,1.17544,1.17644,2179 -2017-10-02 07:00:00,1.1764,1.17659,1.17347,1.17422,3426 -2017-10-02 08:00:00,1.17422,1.17525,1.1734,1.17461,2569 -2017-10-02 09:00:00,1.17462,1.17486,1.17302,1.17316,1897 -2017-10-02 10:00:00,1.17311,1.17463,1.173,1.17456,1416 -2017-10-02 11:00:00,1.17452,1.17513,1.1738,1.17384,1793 -2017-10-02 12:00:00,1.17386,1.17634,1.17374,1.17577,2782 -2017-10-02 13:00:00,1.17574,1.17612,1.17464,1.17519,2446 -2017-10-02 14:00:00,1.17514,1.17584,1.17346,1.17354,4998 -2017-10-02 15:00:00,1.1735,1.1746,1.17306,1.17442,2435 -2017-10-02 16:00:00,1.17446,1.17486,1.17408,1.17434,1295 -2017-10-02 17:00:00,1.17434,1.17443,1.17338,1.17392,987 -2017-10-02 18:00:00,1.17389,1.17499,1.17364,1.17436,1210 -2017-10-02 19:00:00,1.17434,1.17458,1.17333,1.17354,1079 -2017-10-02 20:00:00,1.17354,1.17368,1.17316,1.17323,522 -2017-10-02 21:00:00,1.17334,1.17372,1.17306,1.17337,3674 -2017-10-02 22:00:00,1.17333,1.174,1.17321,1.17386,1670 -2017-10-02 23:00:00,1.17385,1.17402,1.17317,1.17321,785 -2017-10-03 00:00:00,1.17322,1.17344,1.17192,1.172,1697 -2017-10-03 01:00:00,1.17204,1.17204,1.17042,1.17062,3261 -2017-10-03 02:00:00,1.17063,1.17134,1.17016,1.17121,1443 -2017-10-03 03:00:00,1.1712,1.17147,1.17036,1.17049,1071 -2017-10-03 04:00:00,1.17048,1.17092,1.17042,1.17067,491 -2017-10-03 05:00:00,1.17072,1.17094,1.16962,1.17059,1722 -2017-10-03 06:00:00,1.17059,1.1724,1.17024,1.17228,2377 -2017-10-03 07:00:00,1.17228,1.17438,1.17194,1.1743,2853 -2017-10-03 08:00:00,1.17435,1.17479,1.1733,1.1733,2150 -2017-10-03 09:00:00,1.17328,1.175,1.17326,1.17363,1627 -2017-10-03 10:00:00,1.1736,1.17588,1.17356,1.1756,1892 -2017-10-03 11:00:00,1.17562,1.17623,1.17494,1.17497,1399 -2017-10-03 12:00:00,1.17498,1.17534,1.1738,1.17488,1691 -2017-10-03 13:00:00,1.17486,1.17612,1.17472,1.17552,2074 -2017-10-03 14:00:00,1.17549,1.17738,1.1753,1.17532,2729 -2017-10-03 15:00:00,1.17535,1.1764,1.17531,1.17586,1412 -2017-10-03 16:00:00,1.17588,1.17602,1.17498,1.17532,1316 -2017-10-03 17:00:00,1.17531,1.1756,1.17448,1.17464,939 -2017-10-03 18:00:00,1.17464,1.175,1.1739,1.17496,945 -2017-10-03 19:00:00,1.17498,1.17532,1.17454,1.17494,925 -2017-10-03 20:00:00,1.17492,1.17508,1.17432,1.1744,716 -2017-10-03 21:00:00,1.1742,1.17444,1.17347,1.1737,2108 -2017-10-03 22:00:00,1.17367,1.17456,1.17364,1.17432,928 -2017-10-03 23:00:00,1.17438,1.17494,1.17414,1.1748,429 -2017-10-04 00:00:00,1.17478,1.17797,1.17464,1.17748,2185 -2017-10-04 01:00:00,1.17743,1.17764,1.17663,1.17724,1464 -2017-10-04 02:00:00,1.17727,1.178,1.17664,1.17681,1039 -2017-10-04 03:00:00,1.17678,1.17718,1.17646,1.17676,573 -2017-10-04 04:00:00,1.17678,1.1771,1.17634,1.17672,560 -2017-10-04 05:00:00,1.17667,1.1774,1.17655,1.17712,1219 -2017-10-04 06:00:00,1.17712,1.17767,1.17626,1.17639,2057 -2017-10-04 07:00:00,1.17634,1.17641,1.1747,1.17574,2449 -2017-10-04 08:00:00,1.17574,1.17666,1.1756,1.17565,1732 -2017-10-04 09:00:00,1.1756,1.17592,1.17529,1.17588,1138 -2017-10-04 10:00:00,1.17584,1.1781,1.17579,1.17744,2057 -2017-10-04 11:00:00,1.17742,1.17874,1.17666,1.17801,2085 -2017-10-04 12:00:00,1.178,1.17882,1.17623,1.1772,3512 -2017-10-04 13:00:00,1.1772,1.17731,1.17562,1.1765,2258 -2017-10-04 14:00:00,1.17642,1.17654,1.17468,1.176,3823 -2017-10-04 15:00:00,1.17598,1.17642,1.1754,1.17616,2211 -2017-10-04 16:00:00,1.17616,1.17666,1.17568,1.17632,1325 -2017-10-04 17:00:00,1.17629,1.17647,1.17546,1.17642,1103 -2017-10-04 18:00:00,1.17646,1.17658,1.17604,1.17643,766 -2017-10-04 19:00:00,1.17644,1.17658,1.17616,1.17632,888 -2017-10-04 20:00:00,1.17632,1.17664,1.17588,1.17596,515 -2017-10-04 21:00:00,1.17632,1.17632,1.17554,1.17572,5281 -2017-10-04 22:00:00,1.17565,1.17632,1.17564,1.17607,547 -2017-10-04 23:00:00,1.17606,1.17628,1.17549,1.1757,331 -2017-10-05 00:00:00,1.1757,1.17592,1.17518,1.1755,1177 -2017-10-05 01:00:00,1.17549,1.17581,1.17516,1.17574,1122 -2017-10-05 02:00:00,1.17568,1.17594,1.17558,1.17578,431 -2017-10-05 03:00:00,1.17572,1.17584,1.17546,1.17548,431 -2017-10-05 04:00:00,1.17551,1.17597,1.17542,1.17592,377 -2017-10-05 05:00:00,1.17589,1.17644,1.17538,1.17542,1157 -2017-10-05 06:00:00,1.17544,1.17644,1.17478,1.17634,1887 -2017-10-05 07:00:00,1.17638,1.1779,1.17598,1.17717,3037 -2017-10-05 08:00:00,1.17716,1.1777,1.17686,1.17751,1627 -2017-10-05 09:00:00,1.17754,1.17756,1.17624,1.17635,1569 -2017-10-05 10:00:00,1.17634,1.17657,1.17424,1.17464,1483 -2017-10-05 11:00:00,1.17464,1.17493,1.1735,1.17366,2433 -2017-10-05 12:00:00,1.1737,1.17456,1.17252,1.17306,3088 -2017-10-05 13:00:00,1.1731,1.1734,1.17127,1.17226,4012 -2017-10-05 14:00:00,1.17228,1.17352,1.17133,1.17143,3219 -2017-10-05 15:00:00,1.17142,1.17159,1.1703,1.17056,2108 -2017-10-05 16:00:00,1.1706,1.17122,1.17042,1.17094,1426 -2017-10-05 17:00:00,1.17095,1.171,1.16999,1.1705,983 -2017-10-05 18:00:00,1.17055,1.17068,1.16992,1.17048,1084 -2017-10-05 19:00:00,1.17048,1.17076,1.17034,1.17058,799 -2017-10-05 20:00:00,1.17056,1.17119,1.17033,1.17114,450 -2017-10-05 21:00:00,1.17114,1.17146,1.17092,1.17116,1338 -2017-10-05 22:00:00,1.17114,1.1712,1.17094,1.17108,364 -2017-10-05 23:00:00,1.17108,1.17141,1.17072,1.1714,629 -2017-10-06 00:00:00,1.17146,1.17148,1.16994,1.17118,1548 -2017-10-06 01:00:00,1.17116,1.17158,1.17078,1.17096,918 -2017-10-06 02:00:00,1.17096,1.17142,1.17084,1.17084,582 -2017-10-06 03:00:00,1.1708,1.17084,1.16948,1.16966,982 -2017-10-06 04:00:00,1.16966,1.17008,1.1686,1.16997,1598 -2017-10-06 05:00:00,1.17001,1.17023,1.16933,1.16994,1016 -2017-10-06 06:00:00,1.16992,1.17071,1.16894,1.16956,2031 -2017-10-06 07:00:00,1.16954,1.16992,1.16862,1.16888,2035 -2017-10-06 08:00:00,1.16882,1.17006,1.16873,1.16964,1703 -2017-10-06 09:00:00,1.16962,1.17074,1.16944,1.17048,1397 -2017-10-06 10:00:00,1.17048,1.1715,1.17026,1.17076,1448 -2017-10-06 11:00:00,1.17076,1.17122,1.17048,1.17066,1296 -2017-10-06 12:00:00,1.17067,1.17149,1.16692,1.16908,10491 -2017-10-06 13:00:00,1.16904,1.17078,1.16892,1.16976,4726 -2017-10-06 14:00:00,1.1698,1.17386,1.16842,1.17314,7623 -2017-10-06 15:00:00,1.17314,1.17382,1.17188,1.1733,3841 -2017-10-06 16:00:00,1.1733,1.17358,1.1723,1.1724,1958 -2017-10-06 17:00:00,1.17242,1.1735,1.17242,1.17328,1075 -2017-10-06 18:00:00,1.17323,1.17349,1.17256,1.17336,1098 -2017-10-06 19:00:00,1.17335,1.17356,1.17301,1.17332,1106 -2017-10-06 20:00:00,1.17331,1.17376,1.17276,1.17326,1269 -2017-10-06 21:00:00,1.17324,1.17324,1.17324,1.17324,1 -2017-10-08 21:00:00,1.17298,1.17417,1.17297,1.17376,291 -2017-10-08 22:00:00,1.17373,1.17422,1.17335,1.1739,2232 -2017-10-08 23:00:00,1.17392,1.17434,1.17378,1.17427,765 -2017-10-09 00:00:00,1.17424,1.17446,1.17353,1.1737,699 -2017-10-09 01:00:00,1.17375,1.17437,1.1732,1.17358,773 -2017-10-09 02:00:00,1.17364,1.1748,1.17364,1.17412,674 -2017-10-09 03:00:00,1.17418,1.17427,1.1736,1.17364,280 -2017-10-09 04:00:00,1.1736,1.17394,1.17344,1.17358,377 -2017-10-09 05:00:00,1.17358,1.1737,1.17324,1.1737,464 -2017-10-09 06:00:00,1.17367,1.17414,1.17232,1.17274,1071 -2017-10-09 07:00:00,1.17269,1.17308,1.17197,1.17282,1281 -2017-10-09 08:00:00,1.1728,1.17412,1.1725,1.17358,1017 -2017-10-09 09:00:00,1.17355,1.17452,1.17337,1.17438,871 -2017-10-09 10:00:00,1.17442,1.17469,1.17398,1.17452,572 -2017-10-09 11:00:00,1.17454,1.1748,1.17399,1.1747,919 -2017-10-09 12:00:00,1.1747,1.1747,1.17372,1.17388,889 -2017-10-09 13:00:00,1.17393,1.17402,1.17312,1.17312,731 -2017-10-09 14:00:00,1.17309,1.17392,1.17253,1.17381,1149 -2017-10-09 15:00:00,1.17377,1.17466,1.17362,1.17428,928 -2017-10-09 16:00:00,1.17424,1.17561,1.17417,1.17499,1348 -2017-10-09 17:00:00,1.17496,1.17554,1.17468,1.17514,690 -2017-10-09 18:00:00,1.17512,1.17528,1.17474,1.17496,544 -2017-10-09 19:00:00,1.17492,1.17562,1.17486,1.17513,729 -2017-10-09 20:00:00,1.17508,1.17514,1.17391,1.17413,520 -2017-10-09 21:00:00,1.17403,1.17423,1.17395,1.1741,323 -2017-10-09 22:00:00,1.17416,1.17442,1.17394,1.17414,924 -2017-10-09 23:00:00,1.17416,1.17431,1.174,1.17411,408 -2017-10-10 00:00:00,1.17406,1.1749,1.17406,1.17484,1017 -2017-10-10 01:00:00,1.17483,1.17825,1.1748,1.17765,2160 -2017-10-10 02:00:00,1.17764,1.17814,1.17717,1.17718,881 -2017-10-10 03:00:00,1.17718,1.17737,1.17666,1.17668,500 -2017-10-10 04:00:00,1.17674,1.17737,1.17659,1.17708,723 -2017-10-10 05:00:00,1.17708,1.17749,1.1768,1.17713,889 -2017-10-10 06:00:00,1.17713,1.17896,1.17657,1.17776,2276 -2017-10-10 07:00:00,1.17774,1.17774,1.17624,1.1765,2541 -2017-10-10 08:00:00,1.17652,1.17859,1.17651,1.17785,1857 -2017-10-10 09:00:00,1.17789,1.18027,1.17749,1.1802,1904 -2017-10-10 10:00:00,1.18024,1.18072,1.17792,1.17818,1874 -2017-10-10 11:00:00,1.17814,1.17962,1.17733,1.17962,1699 -2017-10-10 12:00:00,1.1796,1.17978,1.17853,1.1787,2012 -2017-10-10 13:00:00,1.1787,1.18054,1.17824,1.1803,2206 -2017-10-10 14:00:00,1.18033,1.18182,1.18009,1.18174,2667 -2017-10-10 15:00:00,1.18169,1.18178,1.18028,1.18038,1576 -2017-10-10 16:00:00,1.18039,1.18048,1.17956,1.18024,1491 -2017-10-10 17:00:00,1.18024,1.18254,1.17962,1.18038,4810 -2017-10-10 18:00:00,1.18042,1.18118,1.18008,1.18039,1048 -2017-10-10 19:00:00,1.18044,1.18162,1.18026,1.18152,914 -2017-10-10 20:00:00,1.18148,1.18177,1.18079,1.18084,443 -2017-10-10 21:00:00,1.1808,1.18119,1.18066,1.1808,5353 -2017-10-10 22:00:00,1.18078,1.18118,1.18076,1.18108,673 -2017-10-10 23:00:00,1.18102,1.18174,1.18102,1.1814,565 -2017-10-11 00:00:00,1.18137,1.18278,1.18128,1.18193,1478 -2017-10-11 01:00:00,1.18194,1.18245,1.18112,1.18113,1581 -2017-10-11 02:00:00,1.18108,1.18114,1.17951,1.18022,2112 -2017-10-11 03:00:00,1.18024,1.18096,1.18004,1.18079,811 -2017-10-11 04:00:00,1.18084,1.18206,1.18077,1.18138,1180 -2017-10-11 05:00:00,1.1814,1.1818,1.18124,1.18166,815 -2017-10-11 06:00:00,1.18164,1.18343,1.18154,1.1822,2360 -2017-10-11 07:00:00,1.18218,1.18308,1.1814,1.18267,1971 -2017-10-11 08:00:00,1.18268,1.18447,1.18259,1.18272,2478 -2017-10-11 09:00:00,1.1827,1.18279,1.18016,1.18065,2439 -2017-10-11 10:00:00,1.18067,1.18231,1.18052,1.18228,1476 -2017-10-11 11:00:00,1.18226,1.18308,1.18183,1.18289,1620 -2017-10-11 12:00:00,1.18294,1.18467,1.18274,1.18444,2069 -2017-10-11 13:00:00,1.18443,1.18586,1.1837,1.1855,2690 -2017-10-11 14:00:00,1.18551,1.1856,1.18389,1.18446,1865 -2017-10-11 15:00:00,1.18446,1.18567,1.18423,1.18471,1950 -2017-10-11 16:00:00,1.18466,1.1851,1.18406,1.18456,921 -2017-10-11 17:00:00,1.18461,1.18492,1.1841,1.18434,1059 -2017-10-11 18:00:00,1.18439,1.18592,1.18396,1.1854,4778 -2017-10-11 19:00:00,1.1854,1.18692,1.18488,1.18668,1882 -2017-10-11 20:00:00,1.18672,1.18685,1.18576,1.18599,1072 -2017-10-11 21:00:00,1.18599,1.18646,1.18569,1.18605,2213 -2017-10-11 22:00:00,1.18602,1.18654,1.18596,1.18632,1362 -2017-10-11 23:00:00,1.18636,1.18659,1.18599,1.18642,1100 -2017-10-12 00:00:00,1.18636,1.18715,1.18583,1.18644,2164 -2017-10-12 01:00:00,1.18644,1.18762,1.18628,1.18701,1215 -2017-10-12 02:00:00,1.187,1.18755,1.18674,1.18744,1266 -2017-10-12 03:00:00,1.18744,1.18782,1.18722,1.18748,887 -2017-10-12 04:00:00,1.18752,1.18786,1.18735,1.1876,802 -2017-10-12 05:00:00,1.18756,1.188,1.18718,1.18783,893 -2017-10-12 06:00:00,1.18783,1.18787,1.18646,1.18669,1404 -2017-10-12 07:00:00,1.18667,1.18688,1.18562,1.18669,2017 -2017-10-12 08:00:00,1.18668,1.18669,1.18594,1.18624,1343 -2017-10-12 09:00:00,1.18628,1.18659,1.18509,1.18522,1489 -2017-10-12 10:00:00,1.18522,1.18564,1.18516,1.18539,1141 -2017-10-12 11:00:00,1.18539,1.18618,1.18514,1.18544,1301 -2017-10-12 12:00:00,1.18548,1.18586,1.18406,1.18472,2842 -2017-10-12 13:00:00,1.18472,1.1852,1.1829,1.1833,1682 -2017-10-12 14:00:00,1.18335,1.18494,1.18306,1.18467,2256 -2017-10-12 15:00:00,1.18465,1.1848,1.18344,1.18404,1686 -2017-10-12 16:00:00,1.184,1.18473,1.18338,1.18354,2361 -2017-10-12 17:00:00,1.18354,1.18506,1.18268,1.18468,2281 -2017-10-12 18:00:00,1.18468,1.18492,1.1834,1.18353,1165 -2017-10-12 19:00:00,1.18358,1.18384,1.18302,1.18353,884 -2017-10-12 20:00:00,1.18354,1.18354,1.18274,1.18306,1000 -2017-10-12 21:00:00,1.18282,1.18352,1.18266,1.18318,1184 -2017-10-12 22:00:00,1.1832,1.18382,1.18298,1.18352,469 -2017-10-12 23:00:00,1.18351,1.18351,1.18254,1.18311,886 -2017-10-13 00:00:00,1.18306,1.18448,1.1829,1.18442,1219 -2017-10-13 01:00:00,1.18444,1.18473,1.18375,1.18442,941 -2017-10-13 02:00:00,1.18439,1.18516,1.18424,1.18488,859 -2017-10-13 03:00:00,1.1849,1.18514,1.18456,1.18479,516 -2017-10-13 04:00:00,1.18485,1.1849,1.18435,1.18457,476 -2017-10-13 05:00:00,1.18462,1.18516,1.18444,1.18472,741 -2017-10-13 06:00:00,1.1847,1.18486,1.1836,1.18385,1643 -2017-10-13 07:00:00,1.1838,1.18389,1.18152,1.18288,3376 -2017-10-13 08:00:00,1.18289,1.18358,1.18254,1.1831,1245 -2017-10-13 09:00:00,1.18308,1.18342,1.18245,1.18298,1369 -2017-10-13 10:00:00,1.18297,1.18338,1.18197,1.18264,1521 -2017-10-13 11:00:00,1.18264,1.18264,1.18059,1.1807,1743 -2017-10-13 12:00:00,1.18066,1.18741,1.18056,1.18568,7670 -2017-10-13 13:00:00,1.18572,1.1875,1.18556,1.18664,3679 -2017-10-13 14:00:00,1.18663,1.18708,1.1832,1.18354,4256 -2017-10-13 15:00:00,1.18358,1.1843,1.18315,1.18364,2148 -2017-10-13 16:00:00,1.18364,1.18491,1.18268,1.1827,1757 -2017-10-13 17:00:00,1.1827,1.1831,1.18202,1.18251,1709 -2017-10-13 18:00:00,1.18246,1.18246,1.18106,1.1818,1798 -2017-10-13 19:00:00,1.18182,1.18225,1.1817,1.1819,941 -2017-10-13 20:00:00,1.18189,1.18262,1.18185,1.18234,1356 -2017-10-15 21:00:00,1.1814,1.18668,1.18106,1.18112,435 -2017-10-15 22:00:00,1.1812,1.18195,1.1807,1.1807,1467 -2017-10-15 23:00:00,1.18068,1.18146,1.18058,1.18146,514 -2017-10-16 00:00:00,1.18147,1.18194,1.1812,1.1813,898 -2017-10-16 01:00:00,1.18128,1.1816,1.18012,1.18034,947 -2017-10-16 02:00:00,1.18034,1.1809,1.17982,1.18076,784 -2017-10-16 03:00:00,1.18072,1.18081,1.18023,1.18062,573 -2017-10-16 04:00:00,1.18061,1.18107,1.18046,1.18092,408 -2017-10-16 05:00:00,1.18086,1.18098,1.17939,1.17964,783 -2017-10-16 06:00:00,1.17964,1.18004,1.1784,1.1784,1816 -2017-10-16 07:00:00,1.17842,1.17957,1.17806,1.17928,1975 -2017-10-16 08:00:00,1.17927,1.1795,1.17847,1.17899,1495 -2017-10-16 09:00:00,1.17894,1.17926,1.17844,1.17898,1019 -2017-10-16 10:00:00,1.17898,1.18064,1.17898,1.18018,1557 -2017-10-16 11:00:00,1.18018,1.1817,1.18009,1.18059,1584 -2017-10-16 12:00:00,1.18056,1.18092,1.17958,1.18071,2079 -2017-10-16 13:00:00,1.18066,1.18102,1.17997,1.18024,1701 -2017-10-16 14:00:00,1.18028,1.18048,1.17952,1.17968,1498 -2017-10-16 15:00:00,1.17964,1.18196,1.17964,1.1809,1611 -2017-10-16 16:00:00,1.18094,1.18118,1.18064,1.18106,800 -2017-10-16 17:00:00,1.18104,1.18108,1.18026,1.18059,1118 -2017-10-16 18:00:00,1.18057,1.18097,1.17892,1.1792,2780 -2017-10-16 19:00:00,1.1792,1.17928,1.1786,1.17924,1384 -2017-10-16 20:00:00,1.17923,1.17978,1.17918,1.17964,332 -2017-10-16 21:00:00,1.17964,1.18004,1.1796,1.17976,1946 -2017-10-16 22:00:00,1.17976,1.17978,1.17914,1.17922,888 -2017-10-16 23:00:00,1.17916,1.1795,1.17877,1.17946,358 -2017-10-17 00:00:00,1.17943,1.17954,1.17842,1.17863,760 -2017-10-17 01:00:00,1.17866,1.17871,1.1775,1.1776,1161 -2017-10-17 02:00:00,1.1776,1.17838,1.1776,1.17833,805 -2017-10-17 03:00:00,1.17838,1.17844,1.17778,1.17794,345 -2017-10-17 04:00:00,1.17795,1.17818,1.17771,1.17776,364 -2017-10-17 05:00:00,1.17774,1.17802,1.17668,1.17701,892 -2017-10-17 06:00:00,1.17699,1.17738,1.17561,1.17571,1863 -2017-10-17 07:00:00,1.17566,1.17735,1.17548,1.17724,1778 -2017-10-17 08:00:00,1.1772,1.17753,1.17641,1.17656,1619 -2017-10-17 09:00:00,1.17658,1.17683,1.17543,1.17586,1716 -2017-10-17 10:00:00,1.17582,1.17698,1.17547,1.17602,1566 -2017-10-17 11:00:00,1.17598,1.17684,1.17556,1.17631,1781 -2017-10-17 12:00:00,1.17633,1.17648,1.17513,1.17514,1932 -2017-10-17 13:00:00,1.17512,1.17534,1.17428,1.17466,2072 -2017-10-17 14:00:00,1.17462,1.17525,1.17362,1.17508,2284 -2017-10-17 15:00:00,1.17504,1.17576,1.17464,1.17536,1698 -2017-10-17 16:00:00,1.17537,1.1756,1.17446,1.17458,900 -2017-10-17 17:00:00,1.17456,1.17664,1.17442,1.17641,861 -2017-10-17 18:00:00,1.17638,1.17754,1.17618,1.17715,1108 -2017-10-17 19:00:00,1.1771,1.17723,1.17672,1.17682,847 -2017-10-17 20:00:00,1.17684,1.17687,1.17654,1.17668,270 -2017-10-17 21:00:00,1.17668,1.17698,1.17647,1.17664,1214 -2017-10-17 22:00:00,1.17663,1.17692,1.17641,1.17686,447 -2017-10-17 23:00:00,1.17687,1.17722,1.17684,1.17712,317 -2017-10-18 00:00:00,1.1771,1.17808,1.17702,1.1773,1396 -2017-10-18 01:00:00,1.1773,1.17736,1.17672,1.17694,605 -2017-10-18 02:00:00,1.17696,1.17753,1.1769,1.17728,459 -2017-10-18 03:00:00,1.17724,1.1773,1.17689,1.17701,348 -2017-10-18 04:00:00,1.17699,1.17708,1.17621,1.17639,424 -2017-10-18 05:00:00,1.17638,1.17655,1.17593,1.17652,832 -2017-10-18 06:00:00,1.17652,1.17708,1.17536,1.1754,1361 -2017-10-18 07:00:00,1.17544,1.17686,1.17481,1.17616,2054 -2017-10-18 08:00:00,1.17616,1.17659,1.1744,1.17455,1985 -2017-10-18 09:00:00,1.17458,1.17475,1.17302,1.17422,2318 -2017-10-18 10:00:00,1.17418,1.17588,1.17416,1.17522,1923 -2017-10-18 11:00:00,1.17524,1.17552,1.1745,1.17453,1670 -2017-10-18 12:00:00,1.17448,1.177,1.17438,1.1765,3546 -2017-10-18 13:00:00,1.17651,1.17777,1.17616,1.17648,2187 -2017-10-18 14:00:00,1.17644,1.17804,1.17598,1.17771,1982 -2017-10-18 15:00:00,1.17766,1.17808,1.17669,1.17732,1625 -2017-10-18 16:00:00,1.17732,1.1794,1.17732,1.17869,1946 -2017-10-18 17:00:00,1.17871,1.17896,1.17836,1.17855,725 -2017-10-18 18:00:00,1.17856,1.18054,1.17848,1.1803,1373 -2017-10-18 19:00:00,1.18034,1.18038,1.17932,1.1794,952 -2017-10-18 20:00:00,1.17933,1.1796,1.17864,1.17866,458 -2017-10-18 21:00:00,1.17892,1.1795,1.17878,1.17923,2801 -2017-10-18 22:00:00,1.17926,1.1797,1.17916,1.17952,679 -2017-10-18 23:00:00,1.17954,1.18003,1.17926,1.17943,1015 -2017-10-19 00:00:00,1.17942,1.18167,1.17928,1.18112,1914 -2017-10-19 01:00:00,1.1811,1.18146,1.18025,1.18044,1297 -2017-10-19 02:00:00,1.18044,1.18056,1.17955,1.17988,1064 -2017-10-19 03:00:00,1.17982,1.18023,1.17948,1.18,535 -2017-10-19 04:00:00,1.18002,1.18068,1.17994,1.18025,962 -2017-10-19 05:00:00,1.18022,1.18037,1.17946,1.17985,899 -2017-10-19 06:00:00,1.17984,1.18228,1.17973,1.18212,2318 -2017-10-19 07:00:00,1.18211,1.18214,1.18048,1.18136,2816 -2017-10-19 08:00:00,1.18137,1.18172,1.17683,1.18064,5957 -2017-10-19 09:00:00,1.18064,1.18162,1.18008,1.18132,2233 -2017-10-19 10:00:00,1.18131,1.18364,1.18094,1.1824,3637 -2017-10-19 11:00:00,1.18238,1.18398,1.18224,1.18348,2348 -2017-10-19 12:00:00,1.18352,1.18426,1.1826,1.18304,3500 -2017-10-19 13:00:00,1.18302,1.18478,1.18272,1.18452,2488 -2017-10-19 14:00:00,1.18449,1.18582,1.18403,1.18522,2718 -2017-10-19 15:00:00,1.18522,1.18549,1.18412,1.18426,1734 -2017-10-19 16:00:00,1.18426,1.18447,1.183,1.18348,2087 -2017-10-19 17:00:00,1.18351,1.18362,1.18277,1.18362,904 -2017-10-19 18:00:00,1.18362,1.18376,1.18271,1.18289,765 -2017-10-19 19:00:00,1.18284,1.18478,1.18262,1.1841,1575 -2017-10-19 20:00:00,1.18407,1.1858,1.1838,1.1852,1824 -2017-10-19 21:00:00,1.18526,1.1853,1.1842,1.18462,1779 -2017-10-19 22:00:00,1.18462,1.18512,1.1845,1.18477,709 -2017-10-19 23:00:00,1.18474,1.18532,1.18448,1.18489,662 -2017-10-20 00:00:00,1.1849,1.18526,1.18434,1.18496,1047 -2017-10-20 01:00:00,1.18499,1.18584,1.18226,1.1823,2495 -2017-10-20 02:00:00,1.18231,1.18231,1.18074,1.18094,4256 -2017-10-20 03:00:00,1.18094,1.18195,1.18078,1.18187,1120 -2017-10-20 04:00:00,1.1819,1.18211,1.18146,1.1815,579 -2017-10-20 05:00:00,1.18144,1.1817,1.1804,1.18083,1285 -2017-10-20 06:00:00,1.18082,1.18192,1.18046,1.18166,2129 -2017-10-20 07:00:00,1.18164,1.18262,1.17904,1.18052,3813 -2017-10-20 08:00:00,1.18054,1.18074,1.1799,1.18036,2541 -2017-10-20 09:00:00,1.18036,1.18126,1.1796,1.18117,1797 -2017-10-20 10:00:00,1.18112,1.18122,1.18001,1.18071,1666 -2017-10-20 11:00:00,1.1807,1.18203,1.18049,1.18156,2127 -2017-10-20 12:00:00,1.18152,1.18207,1.1801,1.18014,2435 -2017-10-20 13:00:00,1.18016,1.18054,1.17858,1.17869,2164 -2017-10-20 14:00:00,1.1787,1.17996,1.1781,1.17864,2694 -2017-10-20 15:00:00,1.17868,1.17899,1.17624,1.17696,2467 -2017-10-20 16:00:00,1.17692,1.17884,1.17688,1.17836,3504 -2017-10-20 17:00:00,1.17835,1.17869,1.17799,1.17856,973 -2017-10-20 18:00:00,1.17858,1.17887,1.17707,1.17781,3066 -2017-10-20 19:00:00,1.17782,1.17802,1.1772,1.1773,952 -2017-10-20 20:00:00,1.17732,1.17834,1.17662,1.17799,1978 -2017-10-20 21:00:00,1.17799,1.17799,1.17799,1.17799,1 -2017-10-22 21:00:00,1.17651,1.17742,1.1762,1.17726,947 -2017-10-22 22:00:00,1.17726,1.17748,1.17611,1.17618,1614 -2017-10-22 23:00:00,1.17624,1.17654,1.17515,1.17548,1027 -2017-10-23 00:00:00,1.17551,1.17624,1.17536,1.17604,1492 -2017-10-23 01:00:00,1.17605,1.17667,1.17552,1.17656,1146 -2017-10-23 02:00:00,1.17654,1.1771,1.17654,1.17692,540 -2017-10-23 03:00:00,1.17687,1.17707,1.17672,1.17703,262 -2017-10-23 04:00:00,1.177,1.17737,1.17684,1.17698,315 -2017-10-23 05:00:00,1.17704,1.17731,1.17662,1.17728,451 -2017-10-23 06:00:00,1.17728,1.17774,1.17591,1.17598,1599 -2017-10-23 07:00:00,1.17595,1.1763,1.17512,1.17559,2079 -2017-10-23 08:00:00,1.17562,1.1758,1.17404,1.17462,1698 -2017-10-23 09:00:00,1.17462,1.17532,1.17351,1.17356,1588 -2017-10-23 10:00:00,1.17356,1.17488,1.17352,1.17449,1796 -2017-10-23 11:00:00,1.17447,1.17458,1.17363,1.17391,2070 -2017-10-23 12:00:00,1.17386,1.17418,1.17334,1.17356,1741 -2017-10-23 13:00:00,1.17358,1.17502,1.17339,1.17479,1753 -2017-10-23 14:00:00,1.17484,1.1757,1.17428,1.17456,2297 -2017-10-23 15:00:00,1.1746,1.17626,1.17406,1.17606,2459 -2017-10-23 16:00:00,1.17608,1.17636,1.17444,1.17445,1796 -2017-10-23 17:00:00,1.1745,1.1748,1.17368,1.17372,1169 -2017-10-23 18:00:00,1.17371,1.17413,1.17254,1.17372,2035 -2017-10-23 19:00:00,1.17371,1.1754,1.17357,1.17492,1981 -2017-10-23 20:00:00,1.17488,1.1751,1.17452,1.17499,483 -2017-10-23 21:00:00,1.1749,1.1752,1.17454,1.17492,1797 -2017-10-23 22:00:00,1.17489,1.17508,1.1747,1.17495,353 -2017-10-23 23:00:00,1.175,1.17568,1.17487,1.17548,588 -2017-10-24 00:00:00,1.17552,1.17608,1.17542,1.176,666 -2017-10-24 01:00:00,1.17597,1.1762,1.17572,1.17608,609 -2017-10-24 02:00:00,1.17612,1.17655,1.17582,1.1761,606 -2017-10-24 03:00:00,1.17612,1.17702,1.17612,1.17662,798 -2017-10-24 04:00:00,1.17656,1.17666,1.17612,1.17618,441 -2017-10-24 05:00:00,1.17618,1.17628,1.17533,1.17554,511 -2017-10-24 06:00:00,1.17554,1.17642,1.17547,1.1757,1826 -2017-10-24 07:00:00,1.1757,1.17598,1.17428,1.17549,2722 -2017-10-24 08:00:00,1.17555,1.17659,1.17552,1.17642,1664 -2017-10-24 09:00:00,1.17646,1.17672,1.17515,1.1763,1457 -2017-10-24 10:00:00,1.17625,1.17625,1.17536,1.17592,1044 -2017-10-24 11:00:00,1.17594,1.177,1.17515,1.17572,1844 -2017-10-24 12:00:00,1.17568,1.17674,1.17549,1.17613,1861 -2017-10-24 13:00:00,1.17611,1.17652,1.17542,1.17596,2415 -2017-10-24 14:00:00,1.17595,1.17772,1.17578,1.17616,3409 -2017-10-24 15:00:00,1.17616,1.17714,1.17588,1.1766,2248 -2017-10-24 16:00:00,1.17657,1.17685,1.17618,1.17639,1375 -2017-10-24 17:00:00,1.17642,1.17676,1.17576,1.17588,1441 -2017-10-24 18:00:00,1.17585,1.17873,1.17564,1.17857,1657 -2017-10-24 19:00:00,1.17854,1.17933,1.1758,1.176,8614 -2017-10-24 20:00:00,1.17596,1.1766,1.17593,1.17606,553 -2017-10-24 21:00:00,1.17606,1.17657,1.17603,1.17636,864 -2017-10-24 22:00:00,1.17639,1.17701,1.17634,1.17646,609 -2017-10-24 23:00:00,1.17649,1.17663,1.17578,1.176,522 -2017-10-25 00:00:00,1.17594,1.17637,1.17531,1.17586,1582 -2017-10-25 01:00:00,1.17592,1.17644,1.17558,1.17598,892 -2017-10-25 02:00:00,1.17602,1.17632,1.17548,1.176,593 -2017-10-25 03:00:00,1.176,1.17604,1.17536,1.17558,393 -2017-10-25 04:00:00,1.17555,1.17584,1.17542,1.17578,374 -2017-10-25 05:00:00,1.17572,1.1766,1.17572,1.17658,1512 -2017-10-25 06:00:00,1.17658,1.1767,1.17558,1.17612,1950 -2017-10-25 07:00:00,1.17616,1.17692,1.17556,1.17613,2864 -2017-10-25 08:00:00,1.17611,1.17752,1.17603,1.17677,3634 -2017-10-25 09:00:00,1.17674,1.17752,1.17597,1.17678,2679 -2017-10-25 10:00:00,1.17673,1.17818,1.17642,1.17764,2203 -2017-10-25 11:00:00,1.17764,1.17812,1.17698,1.17792,2119 -2017-10-25 12:00:00,1.17788,1.17864,1.17702,1.17764,3632 -2017-10-25 13:00:00,1.17769,1.1801,1.17769,1.1797,3856 -2017-10-25 14:00:00,1.1797,1.18171,1.17856,1.18113,5777 -2017-10-25 15:00:00,1.18114,1.18152,1.18014,1.1803,3304 -2017-10-25 16:00:00,1.1803,1.18138,1.18022,1.18132,2781 -2017-10-25 17:00:00,1.18133,1.1818,1.18034,1.18086,2068 -2017-10-25 18:00:00,1.18082,1.18121,1.18022,1.18054,1803 -2017-10-25 19:00:00,1.18054,1.18103,1.18028,1.18036,1295 -2017-10-25 20:00:00,1.18036,1.18153,1.17998,1.18136,1035 -2017-10-25 21:00:00,1.18126,1.18176,1.18114,1.18158,1024 -2017-10-25 22:00:00,1.18156,1.18172,1.18121,1.18154,786 -2017-10-25 23:00:00,1.1815,1.18206,1.18147,1.18198,637 -2017-10-26 00:00:00,1.182,1.18234,1.18151,1.18176,931 -2017-10-26 01:00:00,1.1818,1.1831,1.18173,1.18284,1349 -2017-10-26 02:00:00,1.18288,1.18332,1.18226,1.18244,694 -2017-10-26 03:00:00,1.18242,1.18294,1.18232,1.18248,467 -2017-10-26 04:00:00,1.18252,1.18268,1.18235,1.1826,402 -2017-10-26 05:00:00,1.1826,1.1837,1.18226,1.18294,1361 -2017-10-26 06:00:00,1.18294,1.18332,1.18205,1.18223,1366 -2017-10-26 07:00:00,1.18218,1.18289,1.18143,1.18181,2805 -2017-10-26 08:00:00,1.1818,1.18208,1.18127,1.18136,1688 -2017-10-26 09:00:00,1.18138,1.18138,1.18034,1.18088,1135 -2017-10-26 10:00:00,1.18088,1.18168,1.1808,1.18126,858 -2017-10-26 11:00:00,1.18122,1.18174,1.17576,1.17687,8223 -2017-10-26 12:00:00,1.17685,1.177,1.17382,1.177,13247 -2017-10-26 13:00:00,1.177,1.1786,1.17067,1.17192,10117 -2017-10-26 14:00:00,1.17198,1.17261,1.16992,1.1703,4202 -2017-10-26 15:00:00,1.17032,1.17076,1.16884,1.16992,5083 -2017-10-26 16:00:00,1.16994,1.1701,1.16792,1.16824,2756 -2017-10-26 17:00:00,1.16824,1.16827,1.16594,1.16636,5472 -2017-10-26 18:00:00,1.16636,1.16684,1.16558,1.16587,2679 -2017-10-26 19:00:00,1.16582,1.16594,1.16406,1.16474,2051 -2017-10-26 20:00:00,1.16474,1.16578,1.16456,1.16519,1433 -2017-10-26 21:00:00,1.16524,1.16576,1.16514,1.1654,1036 -2017-10-26 22:00:00,1.16534,1.16556,1.16434,1.16455,1283 -2017-10-26 23:00:00,1.1645,1.1645,1.16316,1.1638,1573 -2017-10-27 00:00:00,1.16376,1.16426,1.16286,1.16306,1489 -2017-10-27 01:00:00,1.16306,1.16336,1.16244,1.16319,1216 -2017-10-27 02:00:00,1.1632,1.16396,1.16275,1.1636,786 -2017-10-27 03:00:00,1.16357,1.16394,1.16321,1.1639,1022 -2017-10-27 04:00:00,1.16388,1.16392,1.16344,1.16355,344 -2017-10-27 05:00:00,1.16352,1.16439,1.1633,1.16437,1053 -2017-10-27 06:00:00,1.16438,1.16438,1.1621,1.16236,2745 -2017-10-27 07:00:00,1.16232,1.1635,1.16156,1.16337,3727 -2017-10-27 08:00:00,1.16333,1.16381,1.16244,1.16273,3177 -2017-10-27 09:00:00,1.1627,1.16362,1.16231,1.16342,2225 -2017-10-27 10:00:00,1.1634,1.1639,1.16198,1.16264,2196 -2017-10-27 11:00:00,1.16262,1.16264,1.1605,1.16076,2501 -2017-10-27 12:00:00,1.16075,1.16121,1.15872,1.15991,6659 -2017-10-27 13:00:00,1.15991,1.16059,1.15788,1.15806,5649 -2017-10-27 14:00:00,1.1581,1.16241,1.15783,1.15806,11848 -2017-10-27 15:00:00,1.15811,1.1587,1.15741,1.15806,4316 -2017-10-27 16:00:00,1.1581,1.1593,1.1578,1.15903,1980 -2017-10-27 17:00:00,1.159,1.15947,1.15852,1.15867,1297 -2017-10-27 18:00:00,1.15867,1.16004,1.15844,1.15973,1234 -2017-10-27 19:00:00,1.15974,1.16038,1.15964,1.15986,1391 -2017-10-27 20:00:00,1.15982,1.16109,1.15966,1.1608,2615 -2017-10-29 21:00:00,1.16096,1.16165,1.16052,1.16068,370 -2017-10-29 22:00:00,1.16058,1.1607,1.15936,1.15955,1861 -2017-10-29 23:00:00,1.15956,1.16102,1.15955,1.16055,849 -2017-10-30 00:00:00,1.16055,1.16084,1.15978,1.1606,1632 -2017-10-30 01:00:00,1.16065,1.16146,1.16006,1.16108,1595 -2017-10-30 02:00:00,1.16114,1.1615,1.1606,1.16094,1184 -2017-10-30 03:00:00,1.16097,1.16154,1.16079,1.16145,880 -2017-10-30 04:00:00,1.16144,1.16172,1.1613,1.16172,624 -2017-10-30 05:00:00,1.1617,1.1618,1.16127,1.16165,784 -2017-10-30 06:00:00,1.16166,1.16179,1.16132,1.1617,598 -2017-10-30 07:00:00,1.16164,1.16227,1.16017,1.16193,2418 -2017-10-30 08:00:00,1.16199,1.16354,1.16154,1.1634,3322 -2017-10-30 09:00:00,1.16335,1.1641,1.16302,1.16396,1834 -2017-10-30 10:00:00,1.16396,1.16423,1.16314,1.16376,1796 -2017-10-30 11:00:00,1.1638,1.1642,1.16322,1.16322,1682 -2017-10-30 12:00:00,1.16324,1.1633,1.16097,1.16144,2861 -2017-10-30 13:00:00,1.16147,1.16202,1.16048,1.162,2661 -2017-10-30 14:00:00,1.16202,1.16228,1.16035,1.16172,2101 -2017-10-30 15:00:00,1.16168,1.16338,1.16126,1.16272,2975 -2017-10-30 16:00:00,1.16268,1.16462,1.16224,1.16392,3165 -2017-10-30 17:00:00,1.16391,1.1641,1.16298,1.16302,1002 -2017-10-30 18:00:00,1.16298,1.16396,1.1628,1.1639,1194 -2017-10-30 19:00:00,1.1639,1.16576,1.16368,1.16566,1203 -2017-10-30 20:00:00,1.16568,1.16578,1.16505,1.16517,885 -2017-10-30 21:00:00,1.16495,1.16527,1.1648,1.16496,686 -2017-10-30 22:00:00,1.16496,1.16496,1.16416,1.16432,655 -2017-10-30 23:00:00,1.16438,1.1653,1.16422,1.16515,697 -2017-10-31 00:00:00,1.16516,1.1652,1.16398,1.16474,1258 -2017-10-31 01:00:00,1.1647,1.1647,1.16332,1.16344,749 -2017-10-31 02:00:00,1.16349,1.1639,1.16328,1.16382,556 -2017-10-31 03:00:00,1.1638,1.1639,1.1635,1.16366,531 -2017-10-31 04:00:00,1.16364,1.16366,1.16253,1.16257,482 -2017-10-31 05:00:00,1.16252,1.16378,1.16252,1.16358,841 -2017-10-31 06:00:00,1.16356,1.16499,1.16356,1.16434,996 -2017-10-31 07:00:00,1.16432,1.16446,1.16316,1.16446,2078 -2017-10-31 08:00:00,1.16443,1.16491,1.1632,1.16413,2202 -2017-10-31 09:00:00,1.16418,1.16418,1.1631,1.1634,1413 -2017-10-31 10:00:00,1.16334,1.16364,1.16248,1.16306,2400 -2017-10-31 11:00:00,1.16308,1.16402,1.16268,1.16395,1648 -2017-10-31 12:00:00,1.16393,1.1645,1.16304,1.16362,2552 -2017-10-31 13:00:00,1.16362,1.16431,1.1634,1.1641,2864 -2017-10-31 14:00:00,1.16408,1.16438,1.16266,1.16382,2123 -2017-10-31 15:00:00,1.16386,1.16614,1.16298,1.16484,4183 -2017-10-31 16:00:00,1.1648,1.16586,1.16392,1.16586,2664 -2017-10-31 17:00:00,1.16581,1.16585,1.16445,1.16476,1077 -2017-10-31 18:00:00,1.16476,1.16568,1.16462,1.16509,1373 -2017-10-31 19:00:00,1.1651,1.16572,1.16481,1.16499,1166 -2017-10-31 20:00:00,1.165,1.16515,1.16434,1.16458,600 -2017-10-31 21:00:00,1.16457,1.16492,1.16402,1.1646,1261 -2017-10-31 22:00:00,1.1647,1.16528,1.16459,1.16498,485 -2017-10-31 23:00:00,1.165,1.1655,1.1647,1.1652,519 -2017-11-01 00:00:00,1.16514,1.16544,1.16394,1.164,1357 -2017-11-01 01:00:00,1.16402,1.1641,1.1632,1.16364,1440 -2017-11-01 02:00:00,1.16364,1.16378,1.16315,1.16325,725 -2017-11-01 03:00:00,1.16328,1.1634,1.1629,1.16316,564 -2017-11-01 04:00:00,1.1631,1.1633,1.16289,1.1631,413 -2017-11-01 05:00:00,1.16306,1.16321,1.16258,1.16293,591 -2017-11-01 06:00:00,1.16292,1.16458,1.16288,1.16404,1190 -2017-11-01 07:00:00,1.16399,1.16528,1.1634,1.16522,1843 -2017-11-01 08:00:00,1.1652,1.16575,1.16387,1.16402,1822 -2017-11-01 09:00:00,1.16398,1.16456,1.1632,1.16325,1766 -2017-11-01 10:00:00,1.16321,1.1642,1.16321,1.16415,1138 -2017-11-01 11:00:00,1.16412,1.16434,1.16326,1.16382,1156 -2017-11-01 12:00:00,1.16387,1.16422,1.16142,1.16178,3968 -2017-11-01 13:00:00,1.16183,1.162,1.16066,1.1612,2612 -2017-11-01 14:00:00,1.1612,1.16433,1.16108,1.16324,5203 -2017-11-01 15:00:00,1.16322,1.16368,1.1614,1.16174,2538 -2017-11-01 16:00:00,1.16174,1.16267,1.16136,1.16257,2385 -2017-11-01 17:00:00,1.16255,1.16332,1.1621,1.16284,1953 -2017-11-01 18:00:00,1.16268,1.16419,1.16107,1.16193,6981 -2017-11-01 19:00:00,1.16194,1.16335,1.16165,1.16202,2115 -2017-11-01 20:00:00,1.16206,1.16302,1.16148,1.16194,1546 -2017-11-01 21:00:00,1.16194,1.16253,1.16174,1.1623,1080 -2017-11-01 22:00:00,1.1623,1.16232,1.16132,1.16184,854 -2017-11-01 23:00:00,1.16186,1.16288,1.16176,1.16282,656 -2017-11-02 00:00:00,1.16287,1.16388,1.1628,1.16348,2355 -2017-11-02 01:00:00,1.16346,1.16718,1.16334,1.16608,3743 -2017-11-02 02:00:00,1.16613,1.16652,1.16535,1.16538,1026 -2017-11-02 03:00:00,1.16543,1.16572,1.16499,1.16556,645 -2017-11-02 04:00:00,1.16558,1.16624,1.16519,1.1658,845 -2017-11-02 05:00:00,1.16576,1.16591,1.16506,1.16564,585 -2017-11-02 06:00:00,1.16562,1.16594,1.16508,1.16576,1018 -2017-11-02 07:00:00,1.1658,1.16629,1.16408,1.16418,1939 -2017-11-02 08:00:00,1.1642,1.16439,1.16259,1.16326,2348 -2017-11-02 09:00:00,1.16329,1.16438,1.16322,1.16415,1705 -2017-11-02 10:00:00,1.16416,1.16504,1.16406,1.1648,1488 -2017-11-02 11:00:00,1.16483,1.16586,1.16472,1.16529,2171 -2017-11-02 12:00:00,1.16534,1.16679,1.16472,1.16523,6359 -2017-11-02 13:00:00,1.1652,1.16533,1.16352,1.16506,4128 -2017-11-02 14:00:00,1.165,1.16878,1.165,1.16626,7854 -2017-11-02 15:00:00,1.16626,1.16783,1.16546,1.16724,5083 -2017-11-02 16:00:00,1.16724,1.16737,1.1654,1.16628,3065 -2017-11-02 17:00:00,1.16629,1.16633,1.16542,1.16564,1804 -2017-11-02 18:00:00,1.16568,1.1663,1.16544,1.16594,1728 -2017-11-02 19:00:00,1.16595,1.16646,1.1648,1.16611,3020 -2017-11-02 20:00:00,1.16614,1.16622,1.1657,1.16584,760 -2017-11-02 21:00:00,1.16578,1.16604,1.16541,1.16564,1331 -2017-11-02 22:00:00,1.16567,1.16597,1.16556,1.16573,509 -2017-11-02 23:00:00,1.16575,1.16606,1.1654,1.16586,440 -2017-11-03 00:00:00,1.16586,1.16651,1.16562,1.16576,947 -2017-11-03 01:00:00,1.16573,1.16663,1.16572,1.16614,752 -2017-11-03 02:00:00,1.16619,1.16631,1.16562,1.16588,823 -2017-11-03 03:00:00,1.16588,1.16617,1.16564,1.16576,328 -2017-11-03 04:00:00,1.1658,1.16626,1.16568,1.1662,299 -2017-11-03 05:00:00,1.16618,1.16654,1.16593,1.16648,534 -2017-11-03 06:00:00,1.16648,1.16679,1.16598,1.16606,711 -2017-11-03 07:00:00,1.16607,1.16607,1.16442,1.16467,1613 -2017-11-03 08:00:00,1.16462,1.16494,1.16419,1.16475,1374 -2017-11-03 09:00:00,1.16472,1.16496,1.16398,1.16471,1222 -2017-11-03 10:00:00,1.16473,1.16542,1.16421,1.16441,1334 -2017-11-03 11:00:00,1.1644,1.16491,1.16386,1.16476,1689 -2017-11-03 12:00:00,1.16476,1.16914,1.16452,1.16548,10517 -2017-11-03 13:00:00,1.16548,1.16587,1.16408,1.16462,4478 -2017-11-03 14:00:00,1.16456,1.16456,1.16061,1.1609,6161 -2017-11-03 15:00:00,1.16096,1.16202,1.16029,1.16161,3781 -2017-11-03 16:00:00,1.16164,1.16193,1.16,1.16044,1999 -2017-11-03 17:00:00,1.16044,1.16108,1.16004,1.16031,1186 -2017-11-03 18:00:00,1.1603,1.1608,1.15994,1.16076,1379 -2017-11-03 19:00:00,1.16071,1.16144,1.16071,1.16076,726 -2017-11-03 20:00:00,1.16072,1.1614,1.1606,1.16101,2069 -2017-11-05 22:00:00,1.16172,1.1618,1.16048,1.16158,510 -2017-11-05 23:00:00,1.16158,1.16182,1.16088,1.16149,702 -2017-11-06 00:00:00,1.16153,1.16164,1.15998,1.16054,1140 -2017-11-06 01:00:00,1.16054,1.16141,1.15968,1.16103,2715 -2017-11-06 02:00:00,1.16102,1.16244,1.1607,1.16176,1816 -2017-11-06 03:00:00,1.16172,1.16184,1.16114,1.16144,790 -2017-11-06 04:00:00,1.16144,1.1616,1.16082,1.16096,1038 -2017-11-06 05:00:00,1.16098,1.16134,1.16061,1.16122,664 -2017-11-06 06:00:00,1.16118,1.1617,1.16052,1.1609,1296 -2017-11-06 07:00:00,1.16088,1.16165,1.15955,1.16106,2212 -2017-11-06 08:00:00,1.16106,1.16153,1.16057,1.16103,2148 -2017-11-06 09:00:00,1.16103,1.16136,1.1588,1.16028,2886 -2017-11-06 10:00:00,1.16032,1.16142,1.16009,1.16096,1384 -2017-11-06 11:00:00,1.16097,1.16104,1.15904,1.15924,1647 -2017-11-06 12:00:00,1.15929,1.15971,1.15836,1.15905,1391 -2017-11-06 13:00:00,1.159,1.15988,1.15854,1.15855,1474 -2017-11-06 14:00:00,1.15857,1.15922,1.15824,1.15853,1475 -2017-11-06 15:00:00,1.15858,1.15919,1.15804,1.15852,1955 -2017-11-06 16:00:00,1.15856,1.16036,1.15841,1.15988,2549 -2017-11-06 17:00:00,1.15983,1.16137,1.15982,1.16119,2779 -2017-11-06 18:00:00,1.16123,1.16162,1.16082,1.16104,1099 -2017-11-06 19:00:00,1.1611,1.16152,1.16049,1.16059,1085 -2017-11-06 20:00:00,1.1606,1.16101,1.16034,1.16092,939 -2017-11-06 21:00:00,1.16092,1.16128,1.16084,1.16096,391 -2017-11-06 22:00:00,1.16115,1.16157,1.16095,1.16102,619 -2017-11-06 23:00:00,1.16104,1.16136,1.16084,1.16114,644 -2017-11-07 00:00:00,1.16108,1.16142,1.16084,1.16137,775 -2017-11-07 01:00:00,1.16134,1.16154,1.16024,1.16044,1517 -2017-11-07 02:00:00,1.16046,1.16139,1.16018,1.16134,1015 -2017-11-07 03:00:00,1.16134,1.16152,1.1608,1.1612,1060 -2017-11-07 04:00:00,1.16119,1.16122,1.16043,1.16075,849 -2017-11-07 05:00:00,1.1608,1.16106,1.16047,1.16056,656 -2017-11-07 06:00:00,1.16055,1.16092,1.1596,1.16024,946 -2017-11-07 07:00:00,1.16018,1.16018,1.15856,1.15883,2228 -2017-11-07 08:00:00,1.15884,1.1594,1.15658,1.15658,3773 -2017-11-07 09:00:00,1.15661,1.15766,1.15661,1.15672,2253 -2017-11-07 10:00:00,1.1567,1.1572,1.15539,1.15664,2781 -2017-11-07 11:00:00,1.15666,1.15784,1.15564,1.15697,2986 -2017-11-07 12:00:00,1.15696,1.15704,1.15588,1.15652,2405 -2017-11-07 13:00:00,1.15651,1.15684,1.1558,1.15626,2128 -2017-11-07 14:00:00,1.1563,1.15817,1.15599,1.15776,2841 -2017-11-07 15:00:00,1.15776,1.15904,1.15674,1.15749,4107 -2017-11-07 16:00:00,1.1575,1.15791,1.15638,1.15768,2990 -2017-11-07 17:00:00,1.15764,1.15882,1.1576,1.15823,1718 -2017-11-07 18:00:00,1.15822,1.15842,1.1575,1.15759,1038 -2017-11-07 19:00:00,1.15758,1.15886,1.15746,1.15874,1285 -2017-11-07 20:00:00,1.1587,1.15927,1.15844,1.159,1136 -2017-11-07 21:00:00,1.15894,1.1591,1.15861,1.15867,628 -2017-11-07 22:00:00,1.15888,1.15936,1.15862,1.15934,1201 -2017-11-07 23:00:00,1.15932,1.16065,1.15922,1.16008,1709 -2017-11-08 00:00:00,1.1601,1.16039,1.15924,1.15935,1632 -2017-11-08 01:00:00,1.15937,1.15982,1.15915,1.15961,987 -2017-11-08 02:00:00,1.15958,1.1599,1.1594,1.15956,645 -2017-11-08 03:00:00,1.15959,1.15988,1.15936,1.15966,474 -2017-11-08 04:00:00,1.15968,1.16004,1.1596,1.15986,289 -2017-11-08 05:00:00,1.15991,1.16005,1.15955,1.15962,463 -2017-11-08 06:00:00,1.15962,1.15972,1.15852,1.1592,893 -2017-11-08 07:00:00,1.15918,1.16048,1.15899,1.15954,1818 -2017-11-08 08:00:00,1.15954,1.16114,1.15916,1.15993,2706 -2017-11-08 09:00:00,1.15994,1.16038,1.15918,1.15922,1846 -2017-11-08 10:00:00,1.15918,1.16046,1.15918,1.16036,1325 -2017-11-08 11:00:00,1.16032,1.16069,1.15966,1.15976,1396 -2017-11-08 12:00:00,1.1597,1.15982,1.15836,1.15862,2446 -2017-11-08 13:00:00,1.15856,1.15946,1.15855,1.15912,2015 -2017-11-08 14:00:00,1.1591,1.16039,1.15886,1.15986,1826 -2017-11-08 15:00:00,1.15986,1.16039,1.15845,1.15852,2355 -2017-11-08 16:00:00,1.15855,1.15946,1.1579,1.15902,1834 -2017-11-08 17:00:00,1.15904,1.15956,1.15878,1.15934,1346 -2017-11-08 18:00:00,1.15934,1.15963,1.15894,1.15944,962 -2017-11-08 19:00:00,1.15939,1.15966,1.15894,1.15954,696 -2017-11-08 20:00:00,1.15956,1.15989,1.15945,1.15983,1058 -2017-11-08 21:00:00,1.15986,1.1599,1.15927,1.15944,722 -2017-11-08 22:00:00,1.15959,1.15977,1.15904,1.15937,1351 -2017-11-08 23:00:00,1.15931,1.15969,1.15922,1.15952,523 -2017-11-09 00:00:00,1.15958,1.15962,1.15874,1.1588,1001 -2017-11-09 01:00:00,1.1588,1.15956,1.15856,1.15938,1117 -2017-11-09 02:00:00,1.15938,1.16003,1.15923,1.1596,1226 -2017-11-09 03:00:00,1.1596,1.15994,1.15911,1.15922,1378 -2017-11-09 04:00:00,1.15916,1.1598,1.1591,1.1596,1404 -2017-11-09 05:00:00,1.15962,1.16052,1.15958,1.16032,2413 -2017-11-09 06:00:00,1.16032,1.16121,1.16016,1.16094,1319 -2017-11-09 07:00:00,1.16094,1.16158,1.16038,1.16056,2065 -2017-11-09 08:00:00,1.16053,1.16067,1.15896,1.15942,2311 -2017-11-09 09:00:00,1.15938,1.16053,1.15936,1.16022,1107 -2017-11-09 10:00:00,1.1602,1.16122,1.15991,1.1612,1089 -2017-11-09 11:00:00,1.16118,1.16445,1.16086,1.16402,3874 -2017-11-09 12:00:00,1.164,1.164,1.16247,1.16318,2485 -2017-11-09 13:00:00,1.16313,1.16328,1.16022,1.16044,3226 -2017-11-09 14:00:00,1.16042,1.16322,1.16005,1.16314,3016 -2017-11-09 15:00:00,1.16314,1.16362,1.16216,1.16242,3584 -2017-11-09 16:00:00,1.16246,1.16545,1.16246,1.16478,4828 -2017-11-09 17:00:00,1.16475,1.1655,1.16398,1.16404,3627 -2017-11-09 18:00:00,1.16406,1.165,1.16378,1.16488,2005 -2017-11-09 19:00:00,1.16484,1.16496,1.16408,1.16488,1379 -2017-11-09 20:00:00,1.16488,1.165,1.16414,1.16425,1232 -2017-11-09 21:00:00,1.16429,1.16441,1.1639,1.16416,420 -2017-11-09 22:00:00,1.16384,1.16461,1.16384,1.16444,2269 -2017-11-09 23:00:00,1.16443,1.16484,1.16416,1.16466,445 -2017-11-10 00:00:00,1.16463,1.16537,1.16442,1.16526,1117 -2017-11-10 01:00:00,1.16524,1.16545,1.16448,1.1646,981 -2017-11-10 02:00:00,1.16458,1.16484,1.16426,1.16456,718 -2017-11-10 03:00:00,1.16458,1.16489,1.16448,1.16476,529 -2017-11-10 04:00:00,1.16482,1.16496,1.16418,1.16446,516 -2017-11-10 05:00:00,1.16444,1.16467,1.16412,1.16458,393 -2017-11-10 06:00:00,1.16458,1.16508,1.16437,1.16489,1042 -2017-11-10 07:00:00,1.16486,1.16486,1.16326,1.16332,1785 -2017-11-10 08:00:00,1.16328,1.16422,1.16228,1.16342,2344 -2017-11-10 09:00:00,1.16344,1.16622,1.16287,1.16604,2178 -2017-11-10 10:00:00,1.16599,1.16599,1.16494,1.16504,1606 -2017-11-10 11:00:00,1.16508,1.1651,1.16384,1.16398,1497 -2017-11-10 12:00:00,1.16394,1.1651,1.16385,1.1651,1311 -2017-11-10 13:00:00,1.16514,1.1655,1.16394,1.16483,1696 -2017-11-10 14:00:00,1.16488,1.16668,1.16484,1.16646,2240 -2017-11-10 15:00:00,1.16645,1.1678,1.16604,1.16612,2563 -2017-11-10 16:00:00,1.16612,1.16627,1.16509,1.1656,2390 -2017-11-10 17:00:00,1.16564,1.16598,1.1652,1.1659,1202 -2017-11-10 18:00:00,1.16593,1.16652,1.1658,1.16609,905 -2017-11-10 19:00:00,1.16606,1.16688,1.16586,1.16666,754 -2017-11-10 20:00:00,1.1667,1.16688,1.16634,1.1665,525 -2017-11-10 21:00:00,1.16652,1.16692,1.1663,1.1665,956 -2017-11-12 22:00:00,1.16585,1.16652,1.16558,1.16584,1312 -2017-11-12 23:00:00,1.16584,1.16657,1.16572,1.16611,1274 -2017-11-13 00:00:00,1.16606,1.1662,1.16448,1.16487,1127 -2017-11-13 01:00:00,1.16484,1.16517,1.16448,1.16503,681 -2017-11-13 02:00:00,1.165,1.16546,1.1649,1.16496,596 -2017-11-13 03:00:00,1.16496,1.16569,1.16492,1.16556,401 -2017-11-13 04:00:00,1.16554,1.16554,1.16512,1.16515,245 -2017-11-13 05:00:00,1.16512,1.16604,1.1651,1.16584,493 -2017-11-13 06:00:00,1.16584,1.16586,1.16454,1.16485,1115 -2017-11-13 07:00:00,1.16488,1.1653,1.16396,1.164,2013 -2017-11-13 08:00:00,1.16404,1.16487,1.16376,1.16472,1856 -2017-11-13 09:00:00,1.16467,1.16531,1.1641,1.16411,1372 -2017-11-13 10:00:00,1.16412,1.16484,1.16382,1.16468,962 -2017-11-13 11:00:00,1.16466,1.1653,1.1645,1.16509,822 -2017-11-13 12:00:00,1.16508,1.166,1.16502,1.16542,1141 -2017-11-13 13:00:00,1.16538,1.16754,1.16537,1.16702,1743 -2017-11-13 14:00:00,1.16706,1.16742,1.1659,1.16607,1712 -2017-11-13 15:00:00,1.16609,1.1673,1.16607,1.16648,2288 -2017-11-13 16:00:00,1.16648,1.1666,1.16549,1.16558,1584 -2017-11-13 17:00:00,1.16554,1.16628,1.16551,1.16628,663 -2017-11-13 18:00:00,1.16625,1.16683,1.16618,1.1665,648 -2017-11-13 19:00:00,1.16652,1.16694,1.16645,1.16674,688 -2017-11-13 20:00:00,1.1667,1.16711,1.16648,1.16686,779 -2017-11-13 21:00:00,1.16681,1.16683,1.16648,1.1667,372 -2017-11-13 22:00:00,1.16685,1.16708,1.16637,1.16643,896 -2017-11-13 23:00:00,1.16642,1.16656,1.16614,1.16646,212 -2017-11-14 00:00:00,1.16644,1.16764,1.16628,1.16712,905 -2017-11-14 01:00:00,1.16706,1.16739,1.16689,1.16703,780 -2017-11-14 02:00:00,1.16702,1.16727,1.16664,1.16715,566 -2017-11-14 03:00:00,1.16719,1.16736,1.16698,1.16717,371 -2017-11-14 04:00:00,1.16715,1.16746,1.16702,1.16726,255 -2017-11-14 05:00:00,1.16724,1.16766,1.16708,1.16739,298 -2017-11-14 06:00:00,1.16738,1.16749,1.16646,1.16654,604 -2017-11-14 07:00:00,1.16654,1.16958,1.16652,1.16898,2946 -2017-11-14 08:00:00,1.16898,1.17102,1.16849,1.17102,2609 -2017-11-14 09:00:00,1.171,1.172,1.17032,1.17179,2063 -2017-11-14 10:00:00,1.17177,1.17252,1.17129,1.17172,2002 -2017-11-14 11:00:00,1.17168,1.1728,1.17161,1.17239,1444 -2017-11-14 12:00:00,1.17237,1.1747,1.17222,1.17466,2593 -2017-11-14 13:00:00,1.17468,1.1764,1.17389,1.17518,3901 -2017-11-14 14:00:00,1.1752,1.17598,1.17449,1.17518,2718 -2017-11-14 15:00:00,1.17516,1.17588,1.17446,1.17555,3874 -2017-11-14 16:00:00,1.17554,1.17746,1.17514,1.1763,3177 -2017-11-14 17:00:00,1.17632,1.17863,1.17623,1.17818,2798 -2017-11-14 18:00:00,1.17815,1.18052,1.1781,1.18004,4116 -2017-11-14 19:00:00,1.18002,1.18004,1.17922,1.17942,1549 -2017-11-14 20:00:00,1.17943,1.17952,1.17891,1.1793,1114 -2017-11-14 21:00:00,1.1793,1.17984,1.17914,1.1798,656 -2017-11-14 22:00:00,1.1794,1.18026,1.17898,1.17982,1590 -2017-11-14 23:00:00,1.1798,1.1799,1.1791,1.1791,639 -2017-11-15 00:00:00,1.17905,1.17942,1.17857,1.17925,1444 -2017-11-15 01:00:00,1.17919,1.1797,1.17884,1.17894,1196 -2017-11-15 02:00:00,1.17898,1.17975,1.17884,1.17933,714 -2017-11-15 03:00:00,1.17938,1.17994,1.17914,1.1797,695 -2017-11-15 04:00:00,1.17965,1.17968,1.17922,1.17926,557 -2017-11-15 05:00:00,1.17926,1.17936,1.17864,1.17868,591 -2017-11-15 06:00:00,1.17867,1.17956,1.17846,1.17928,1265 -2017-11-15 07:00:00,1.17927,1.18171,1.17922,1.1811,3815 -2017-11-15 08:00:00,1.18106,1.1844,1.18079,1.18386,4127 -2017-11-15 09:00:00,1.18388,1.18531,1.18338,1.18396,3139 -2017-11-15 10:00:00,1.18394,1.18468,1.18285,1.18464,2829 -2017-11-15 11:00:00,1.18458,1.185,1.1834,1.18468,2316 -2017-11-15 12:00:00,1.18472,1.18472,1.18346,1.18368,1793 -2017-11-15 13:00:00,1.18372,1.18612,1.18274,1.18448,7558 -2017-11-15 14:00:00,1.18448,1.1845,1.18142,1.182,6811 -2017-11-15 15:00:00,1.18204,1.18207,1.17994,1.18012,4997 -2017-11-15 16:00:00,1.18011,1.1803,1.17898,1.17934,2841 -2017-11-15 17:00:00,1.17938,1.18002,1.1791,1.17974,1375 -2017-11-15 18:00:00,1.17974,1.1804,1.17962,1.18021,1385 -2017-11-15 19:00:00,1.18016,1.18033,1.17896,1.17931,1573 -2017-11-15 20:00:00,1.1793,1.17959,1.17898,1.17922,2004 -2017-11-15 21:00:00,1.17924,1.1794,1.17886,1.17912,583 -2017-11-15 22:00:00,1.17916,1.17926,1.17684,1.17694,3819 -2017-11-15 23:00:00,1.17698,1.17832,1.17695,1.17825,1306 -2017-11-16 00:00:00,1.17826,1.17864,1.1777,1.1781,1347 -2017-11-16 01:00:00,1.17814,1.17895,1.1781,1.17876,809 -2017-11-16 02:00:00,1.17877,1.17877,1.1779,1.17808,1244 -2017-11-16 03:00:00,1.1781,1.17824,1.17768,1.17778,703 -2017-11-16 04:00:00,1.17776,1.17804,1.17764,1.17772,570 -2017-11-16 05:00:00,1.1777,1.1781,1.17758,1.17794,478 -2017-11-16 06:00:00,1.17795,1.18009,1.17788,1.17998,1823 -2017-11-16 07:00:00,1.17997,1.18,1.17712,1.17712,2804 -2017-11-16 08:00:00,1.17712,1.17968,1.17712,1.17896,3740 -2017-11-16 09:00:00,1.17896,1.17902,1.17733,1.17758,2539 -2017-11-16 10:00:00,1.17756,1.17778,1.17678,1.17704,1922 -2017-11-16 11:00:00,1.17708,1.1771,1.17568,1.17645,2081 -2017-11-16 12:00:00,1.17646,1.1769,1.1759,1.17608,1618 -2017-11-16 13:00:00,1.17611,1.17798,1.17609,1.17753,2899 -2017-11-16 14:00:00,1.17757,1.17852,1.17669,1.1779,3318 -2017-11-16 15:00:00,1.17792,1.1785,1.17606,1.17738,3364 -2017-11-16 16:00:00,1.17736,1.17774,1.17669,1.17721,2207 -2017-11-16 17:00:00,1.17718,1.1779,1.17706,1.17734,1393 -2017-11-16 18:00:00,1.1773,1.17774,1.17678,1.17686,1323 -2017-11-16 19:00:00,1.17682,1.17686,1.17594,1.17654,1120 -2017-11-16 20:00:00,1.17657,1.17707,1.17613,1.17707,677 -2017-11-16 21:00:00,1.17706,1.17728,1.17671,1.17694,662 -2017-11-16 22:00:00,1.17714,1.17727,1.1768,1.17709,1245 -2017-11-16 23:00:00,1.17712,1.17788,1.17654,1.17782,818 -2017-11-17 00:00:00,1.17787,1.17942,1.17754,1.17896,1784 -2017-11-17 01:00:00,1.1789,1.18166,1.17872,1.18131,3014 -2017-11-17 02:00:00,1.18128,1.18216,1.18099,1.18202,2315 -2017-11-17 03:00:00,1.18198,1.18206,1.18042,1.18088,1239 -2017-11-17 04:00:00,1.18088,1.18122,1.18041,1.18042,906 -2017-11-17 05:00:00,1.18044,1.18112,1.18028,1.18039,667 -2017-11-17 06:00:00,1.18037,1.1816,1.18033,1.18122,1641 -2017-11-17 07:00:00,1.1812,1.18126,1.17867,1.17873,2190 -2017-11-17 08:00:00,1.17876,1.17998,1.1784,1.17866,3047 -2017-11-17 09:00:00,1.17868,1.18028,1.17857,1.1794,1808 -2017-11-17 10:00:00,1.17938,1.18028,1.17921,1.18016,1556 -2017-11-17 11:00:00,1.18014,1.18126,1.1793,1.1794,1963 -2017-11-17 12:00:00,1.17936,1.18006,1.17898,1.17918,1699 -2017-11-17 13:00:00,1.17923,1.17963,1.17738,1.17872,2610 -2017-11-17 14:00:00,1.17868,1.18028,1.17868,1.17946,3243 -2017-11-17 15:00:00,1.17946,1.17981,1.17802,1.17809,2841 -2017-11-17 16:00:00,1.17812,1.17982,1.17762,1.17975,2990 -2017-11-17 17:00:00,1.17978,1.18016,1.17878,1.18016,1481 -2017-11-17 18:00:00,1.1802,1.18059,1.17984,1.18,1236 -2017-11-17 19:00:00,1.18005,1.18006,1.17924,1.1797,913 -2017-11-17 20:00:00,1.1797,1.1806,1.17948,1.1795,1254 -2017-11-17 21:00:00,1.17948,1.1795,1.17854,1.1791,1972 -2017-11-19 22:00:00,1.1791,1.1791,1.1766,1.1767,702 -2017-11-19 23:00:00,1.1767,1.17692,1.17221,1.17345,4083 -2017-11-20 00:00:00,1.1734,1.17506,1.17316,1.17439,3230 -2017-11-20 01:00:00,1.17436,1.17504,1.17374,1.1745,1681 -2017-11-20 02:00:00,1.17448,1.17461,1.17248,1.17364,1689 -2017-11-20 03:00:00,1.17367,1.17382,1.17331,1.17368,686 -2017-11-20 04:00:00,1.17367,1.17376,1.17272,1.17286,662 -2017-11-20 05:00:00,1.17286,1.1737,1.17282,1.17338,961 -2017-11-20 06:00:00,1.17332,1.17414,1.17319,1.17363,1245 -2017-11-20 07:00:00,1.17358,1.17556,1.17352,1.1754,2869 -2017-11-20 08:00:00,1.17543,1.18083,1.17516,1.17991,7956 -2017-11-20 09:00:00,1.1799,1.18048,1.17922,1.17944,2256 -2017-11-20 10:00:00,1.17944,1.17968,1.17852,1.17884,1647 -2017-11-20 11:00:00,1.17881,1.17906,1.17724,1.1776,1684 -2017-11-20 12:00:00,1.17766,1.1786,1.17746,1.17832,2041 -2017-11-20 13:00:00,1.1783,1.17846,1.17664,1.17708,2708 -2017-11-20 14:00:00,1.17711,1.17757,1.17556,1.17577,2500 -2017-11-20 15:00:00,1.1758,1.17592,1.17422,1.1748,2488 -2017-11-20 16:00:00,1.17482,1.17552,1.17318,1.17402,2961 -2017-11-20 17:00:00,1.17405,1.17498,1.17345,1.1747,1866 -2017-11-20 18:00:00,1.17472,1.17508,1.17362,1.17365,1323 -2017-11-20 19:00:00,1.17368,1.17376,1.17298,1.1732,1725 -2017-11-20 20:00:00,1.1732,1.17366,1.17278,1.17292,956 -2017-11-20 21:00:00,1.17292,1.17349,1.17286,1.17326,838 -2017-11-20 22:00:00,1.17344,1.17362,1.17322,1.1734,667 -2017-11-20 23:00:00,1.17338,1.17382,1.17332,1.17372,481 -2017-11-21 00:00:00,1.1737,1.17446,1.17366,1.17432,769 -2017-11-21 01:00:00,1.1743,1.17448,1.17305,1.17336,1105 -2017-11-21 02:00:00,1.17338,1.17359,1.17303,1.17348,555 -2017-11-21 03:00:00,1.1735,1.17388,1.17336,1.17383,328 -2017-11-21 04:00:00,1.17386,1.17394,1.17367,1.17386,281 -2017-11-21 05:00:00,1.17388,1.17434,1.17372,1.17414,273 -2017-11-21 06:00:00,1.17415,1.17496,1.17383,1.1743,1001 -2017-11-21 07:00:00,1.17425,1.175,1.17303,1.17364,2108 -2017-11-21 08:00:00,1.1736,1.17578,1.17324,1.17388,2934 -2017-11-21 09:00:00,1.17382,1.17422,1.17139,1.17288,3076 -2017-11-21 10:00:00,1.1729,1.17467,1.1726,1.1737,2289 -2017-11-21 11:00:00,1.17374,1.17375,1.17212,1.17222,1850 -2017-11-21 12:00:00,1.17228,1.17281,1.1715,1.17154,2050 -2017-11-21 13:00:00,1.17157,1.17286,1.1713,1.17222,1874 -2017-11-21 14:00:00,1.17225,1.17398,1.1718,1.17372,2933 -2017-11-21 15:00:00,1.17378,1.17448,1.17245,1.17252,3110 -2017-11-21 16:00:00,1.17256,1.17484,1.17239,1.17408,1918 -2017-11-21 17:00:00,1.17409,1.17442,1.17345,1.17428,1813 -2017-11-21 18:00:00,1.17423,1.17519,1.17356,1.17463,1780 -2017-11-21 19:00:00,1.17461,1.17496,1.17392,1.17428,1745 -2017-11-21 20:00:00,1.17428,1.17455,1.1735,1.1739,1096 -2017-11-21 21:00:00,1.17387,1.17434,1.1735,1.17388,639 -2017-11-21 22:00:00,1.17388,1.17422,1.17328,1.17342,1587 -2017-11-21 23:00:00,1.17344,1.17476,1.17332,1.17418,878 -2017-11-22 00:00:00,1.17412,1.17478,1.17374,1.17408,1100 -2017-11-22 01:00:00,1.17404,1.17417,1.17356,1.17389,1011 -2017-11-22 02:00:00,1.17392,1.17405,1.17353,1.17368,588 -2017-11-22 03:00:00,1.17362,1.17404,1.17349,1.17386,603 -2017-11-22 04:00:00,1.17384,1.17444,1.17381,1.17417,342 -2017-11-22 05:00:00,1.17418,1.17454,1.17394,1.17445,426 -2017-11-22 06:00:00,1.17442,1.17562,1.17419,1.1751,1110 -2017-11-22 07:00:00,1.17512,1.17616,1.17476,1.17576,1830 -2017-11-22 08:00:00,1.17574,1.17712,1.17552,1.17694,2632 -2017-11-22 09:00:00,1.17698,1.17731,1.17564,1.17568,1442 -2017-11-22 10:00:00,1.17568,1.17568,1.17484,1.17502,1275 -2017-11-22 11:00:00,1.17504,1.1755,1.17456,1.1753,1143 -2017-11-22 12:00:00,1.17526,1.17528,1.17357,1.17426,2111 -2017-11-22 13:00:00,1.17426,1.17544,1.17406,1.1751,2709 -2017-11-22 14:00:00,1.17511,1.17782,1.175,1.17762,3033 -2017-11-22 15:00:00,1.17764,1.17968,1.17718,1.17859,3431 -2017-11-22 16:00:00,1.17862,1.17979,1.17834,1.17886,1883 -2017-11-22 17:00:00,1.17882,1.17984,1.1786,1.1795,1421 -2017-11-22 18:00:00,1.17955,1.17994,1.17928,1.17991,1078 -2017-11-22 19:00:00,1.1799,1.18268,1.1795,1.18252,4914 -2017-11-22 20:00:00,1.1825,1.18256,1.1814,1.18201,1372 -2017-11-22 21:00:00,1.18206,1.18252,1.18182,1.18232,610 -2017-11-22 22:00:00,1.18234,1.18234,1.18168,1.1819,592 -2017-11-22 23:00:00,1.1819,1.18218,1.18138,1.18147,632 -2017-11-23 00:00:00,1.18152,1.18206,1.18136,1.18144,673 -2017-11-23 01:00:00,1.18144,1.18246,1.18138,1.18231,916 -2017-11-23 02:00:00,1.18225,1.1825,1.18172,1.1821,642 -2017-11-23 03:00:00,1.18214,1.18385,1.18189,1.18325,1106 -2017-11-23 04:00:00,1.1832,1.1838,1.1832,1.1835,498 -2017-11-23 05:00:00,1.1835,1.18375,1.18255,1.18294,621 -2017-11-23 06:00:00,1.18295,1.1836,1.18267,1.18283,821 -2017-11-23 07:00:00,1.18283,1.18392,1.1824,1.18274,1632 -2017-11-23 08:00:00,1.18271,1.18464,1.18271,1.18448,2603 -2017-11-23 09:00:00,1.18441,1.1847,1.18364,1.1843,1464 -2017-11-23 10:00:00,1.1843,1.18468,1.18384,1.18468,1189 -2017-11-23 11:00:00,1.18468,1.18514,1.18422,1.18456,1150 -2017-11-23 12:00:00,1.18457,1.18558,1.18409,1.18434,1557 -2017-11-23 13:00:00,1.18438,1.18499,1.18419,1.18496,994 -2017-11-23 14:00:00,1.18496,1.18526,1.1846,1.18462,943 -2017-11-23 15:00:00,1.18462,1.1854,1.18431,1.18432,1037 -2017-11-23 16:00:00,1.18434,1.1851,1.184,1.1851,808 -2017-11-23 17:00:00,1.1851,1.18544,1.18466,1.18496,534 -2017-11-23 18:00:00,1.18498,1.18536,1.18462,1.18514,830 -2017-11-23 19:00:00,1.1851,1.18526,1.1846,1.18519,2455 -2017-11-23 20:00:00,1.18521,1.18538,1.1849,1.18521,2453 -2017-11-23 21:00:00,1.18522,1.18533,1.18463,1.18516,1858 -2017-11-23 22:00:00,1.18502,1.18534,1.1846,1.18505,1410 -2017-11-23 23:00:00,1.18511,1.18536,1.18479,1.18505,380 -2017-11-24 00:00:00,1.185,1.1855,1.18396,1.1843,906 -2017-11-24 01:00:00,1.18428,1.18501,1.18369,1.18486,764 -2017-11-24 02:00:00,1.18487,1.1856,1.18479,1.18554,448 -2017-11-24 03:00:00,1.18559,1.1856,1.18436,1.18487,523 -2017-11-24 04:00:00,1.18485,1.18592,1.18464,1.18526,565 -2017-11-24 05:00:00,1.18523,1.1856,1.18498,1.18519,336 -2017-11-24 06:00:00,1.1852,1.1854,1.18436,1.18474,694 -2017-11-24 07:00:00,1.18472,1.18506,1.18372,1.18476,1237 -2017-11-24 08:00:00,1.18474,1.18648,1.18432,1.18588,2071 -2017-11-24 09:00:00,1.18581,1.18749,1.1858,1.18684,2028 -2017-11-24 10:00:00,1.18682,1.18698,1.18617,1.18663,1158 -2017-11-24 11:00:00,1.18668,1.18684,1.18557,1.18564,1201 -2017-11-24 12:00:00,1.1856,1.1874,1.18552,1.1874,1305 -2017-11-24 13:00:00,1.18736,1.18988,1.18722,1.18963,2470 -2017-11-24 14:00:00,1.18967,1.19198,1.18951,1.19194,3555 -2017-11-24 15:00:00,1.192,1.19384,1.19192,1.1934,2196 -2017-11-24 16:00:00,1.1934,1.19442,1.19314,1.1937,2323 -2017-11-24 17:00:00,1.19368,1.1938,1.19238,1.19276,1382 -2017-11-24 18:00:00,1.19275,1.19332,1.1923,1.19254,651 -2017-11-24 19:00:00,1.19254,1.19298,1.19238,1.19266,287 -2017-11-24 20:00:00,1.19269,1.1932,1.19253,1.19309,916 -2017-11-24 21:00:00,1.19307,1.19394,1.1926,1.19325,2923 -2017-11-26 22:00:00,1.19242,1.1936,1.19235,1.19354,1396 -2017-11-26 23:00:00,1.19356,1.19361,1.19242,1.19275,641 -2017-11-27 00:00:00,1.19281,1.19307,1.19128,1.19155,1082 -2017-11-27 01:00:00,1.19156,1.19222,1.19116,1.19206,1261 -2017-11-27 02:00:00,1.1921,1.1924,1.19143,1.19178,736 -2017-11-27 03:00:00,1.19174,1.1929,1.19172,1.19248,589 -2017-11-27 04:00:00,1.19244,1.19276,1.19222,1.19238,516 -2017-11-27 05:00:00,1.19236,1.19284,1.19222,1.19284,311 -2017-11-27 06:00:00,1.19284,1.19334,1.19192,1.19225,877 -2017-11-27 07:00:00,1.19221,1.19323,1.19172,1.19278,1338 -2017-11-27 08:00:00,1.19273,1.19571,1.19234,1.19386,3844 -2017-11-27 09:00:00,1.19382,1.19406,1.19208,1.19306,2003 -2017-11-27 10:00:00,1.19306,1.19396,1.19262,1.19387,1369 -2017-11-27 11:00:00,1.19389,1.19406,1.19318,1.19368,1016 -2017-11-27 12:00:00,1.19368,1.19483,1.1928,1.19432,1891 -2017-11-27 13:00:00,1.19428,1.19612,1.19425,1.19591,2453 -2017-11-27 14:00:00,1.19592,1.19592,1.19324,1.19396,2867 -2017-11-27 15:00:00,1.19396,1.19396,1.19151,1.19192,3748 -2017-11-27 16:00:00,1.19198,1.19262,1.1905,1.19106,3183 -2017-11-27 17:00:00,1.19106,1.19204,1.18977,1.19022,2222 -2017-11-27 18:00:00,1.19024,1.19062,1.1899,1.19015,1062 -2017-11-27 19:00:00,1.19011,1.19028,1.1896,1.18994,1057 -2017-11-27 20:00:00,1.18992,1.19017,1.18963,1.18994,867 -2017-11-27 21:00:00,1.18994,1.19011,1.18958,1.18983,471 -2017-11-27 22:00:00,1.18978,1.1904,1.18946,1.18994,1260 -2017-11-27 23:00:00,1.18995,1.19054,1.18994,1.19042,336 -2017-11-28 00:00:00,1.1904,1.1909,1.19004,1.19071,1087 -2017-11-28 01:00:00,1.19066,1.19072,1.18972,1.18995,1218 -2017-11-28 02:00:00,1.19001,1.19038,1.18978,1.19006,796 -2017-11-28 03:00:00,1.19006,1.19049,1.18983,1.19041,358 -2017-11-28 04:00:00,1.19039,1.19068,1.19027,1.19044,658 -2017-11-28 05:00:00,1.19047,1.19088,1.19005,1.19022,430 -2017-11-28 06:00:00,1.19021,1.19108,1.19016,1.19083,804 -2017-11-28 07:00:00,1.19085,1.19085,1.18851,1.18884,2470 -2017-11-28 08:00:00,1.1889,1.192,1.18884,1.19052,3103 -2017-11-28 09:00:00,1.19046,1.19068,1.18892,1.18916,1885 -2017-11-28 10:00:00,1.18911,1.18938,1.18749,1.18854,2551 -2017-11-28 11:00:00,1.18849,1.18914,1.18824,1.18866,1406 -2017-11-28 12:00:00,1.18864,1.18878,1.18768,1.18796,1187 -2017-11-28 13:00:00,1.18798,1.19004,1.18798,1.18938,1657 -2017-11-28 14:00:00,1.18938,1.18994,1.1877,1.18776,2140 -2017-11-28 15:00:00,1.1878,1.18884,1.18644,1.18698,4861 -2017-11-28 16:00:00,1.18692,1.18856,1.18654,1.18777,4169 -2017-11-28 17:00:00,1.18776,1.18837,1.18642,1.187,3617 -2017-11-28 18:00:00,1.187,1.18706,1.18528,1.18596,6853 -2017-11-28 19:00:00,1.18592,1.18632,1.18272,1.18379,4077 -2017-11-28 20:00:00,1.18374,1.1848,1.18327,1.18418,2568 -2017-11-28 21:00:00,1.18418,1.18477,1.1838,1.18412,617 -2017-11-28 22:00:00,1.18406,1.18494,1.18374,1.18468,1670 -2017-11-28 23:00:00,1.18474,1.18522,1.18452,1.18491,744 -2017-11-29 00:00:00,1.18496,1.18531,1.1846,1.18486,1451 -2017-11-29 01:00:00,1.18488,1.1849,1.18402,1.18418,1131 -2017-11-29 02:00:00,1.18424,1.18501,1.18416,1.18498,678 -2017-11-29 03:00:00,1.18504,1.18552,1.18474,1.18536,973 -2017-11-29 04:00:00,1.18541,1.18564,1.18492,1.18503,619 -2017-11-29 05:00:00,1.18507,1.18532,1.18481,1.18513,501 -2017-11-29 06:00:00,1.18512,1.18614,1.18507,1.18594,1115 -2017-11-29 07:00:00,1.1859,1.18718,1.18564,1.18695,1598 -2017-11-29 08:00:00,1.18696,1.18752,1.18599,1.18726,2482 -2017-11-29 09:00:00,1.18726,1.18827,1.18648,1.18668,2262 -2017-11-29 10:00:00,1.18669,1.18676,1.18438,1.18472,1362 -2017-11-29 11:00:00,1.18474,1.18491,1.18309,1.18424,1427 -2017-11-29 12:00:00,1.18419,1.18478,1.1832,1.18366,1843 -2017-11-29 13:00:00,1.18364,1.18386,1.18166,1.18375,4155 -2017-11-29 14:00:00,1.18376,1.18426,1.18303,1.1836,2339 -2017-11-29 15:00:00,1.1836,1.18546,1.18286,1.18496,5663 -2017-11-29 16:00:00,1.18499,1.1864,1.18476,1.18584,3279 -2017-11-29 17:00:00,1.18585,1.18661,1.18509,1.18514,1954 -2017-11-29 18:00:00,1.18512,1.18601,1.18497,1.1857,1807 -2017-11-29 19:00:00,1.18572,1.18649,1.18553,1.18624,1810 -2017-11-29 20:00:00,1.18622,1.1864,1.18502,1.18513,1408 -2017-11-29 21:00:00,1.18508,1.18562,1.18464,1.18477,826 -2017-11-29 22:00:00,1.18483,1.18533,1.18458,1.18493,1428 -2017-11-29 23:00:00,1.1849,1.18546,1.18484,1.18522,874 -2017-11-30 00:00:00,1.1852,1.18562,1.18476,1.18542,1374 -2017-11-30 01:00:00,1.1854,1.18686,1.18536,1.18612,1870 -2017-11-30 02:00:00,1.18617,1.18712,1.1859,1.18664,1044 -2017-11-30 03:00:00,1.18661,1.18685,1.18627,1.18658,469 -2017-11-30 04:00:00,1.18661,1.18662,1.1862,1.1862,450 -2017-11-30 05:00:00,1.18624,1.18672,1.1861,1.18645,563 -2017-11-30 06:00:00,1.1865,1.18727,1.18585,1.1867,939 -2017-11-30 07:00:00,1.18668,1.1876,1.18626,1.18644,2069 -2017-11-30 08:00:00,1.18646,1.18672,1.1841,1.18458,2584 -2017-11-30 09:00:00,1.18459,1.18466,1.18251,1.18324,2463 -2017-11-30 10:00:00,1.18322,1.18335,1.18086,1.18314,2988 -2017-11-30 11:00:00,1.18314,1.18429,1.18286,1.18366,1575 -2017-11-30 12:00:00,1.18366,1.18498,1.18356,1.1845,1862 -2017-11-30 13:00:00,1.18452,1.18636,1.18406,1.1859,2274 -2017-11-30 14:00:00,1.18594,1.19066,1.18589,1.19048,3199 -2017-11-30 15:00:00,1.19044,1.19307,1.19036,1.19226,5278 -2017-11-30 16:00:00,1.19226,1.19312,1.19003,1.19003,4612 -2017-11-30 17:00:00,1.19006,1.19012,1.18854,1.1892,2375 -2017-11-30 18:00:00,1.18918,1.19142,1.18894,1.19123,2492 -2017-11-30 19:00:00,1.19125,1.19128,1.18912,1.18981,1692 -2017-11-30 20:00:00,1.18986,1.19054,1.18956,1.19022,1417 -2017-11-30 21:00:00,1.1902,1.19151,1.19014,1.19041,883 -2017-11-30 22:00:00,1.19041,1.19067,1.1887,1.18902,1695 -2017-11-30 23:00:00,1.18902,1.19032,1.18898,1.18981,681 -2017-12-01 00:00:00,1.18982,1.1916,1.18965,1.1909,2215 -2017-12-01 01:00:00,1.19084,1.19115,1.19018,1.19094,1311 -2017-12-01 02:00:00,1.1909,1.19138,1.19064,1.19072,1467 -2017-12-01 03:00:00,1.19072,1.19132,1.19004,1.19118,1042 -2017-12-01 04:00:00,1.19118,1.19156,1.19086,1.1911,1142 -2017-12-01 05:00:00,1.19108,1.19297,1.191,1.19278,968 -2017-12-01 06:00:00,1.19276,1.19333,1.19184,1.19201,1676 -2017-12-01 07:00:00,1.19196,1.19224,1.19068,1.19158,2244 -2017-12-01 08:00:00,1.19152,1.19404,1.19119,1.19292,4266 -2017-12-01 09:00:00,1.19294,1.19298,1.19008,1.19028,2964 -2017-12-01 10:00:00,1.19024,1.19114,1.18838,1.18892,3010 -2017-12-01 11:00:00,1.18892,1.19046,1.18861,1.19005,1956 -2017-12-01 12:00:00,1.19002,1.19026,1.18878,1.18919,2340 -2017-12-01 13:00:00,1.18916,1.18934,1.18634,1.18692,3985 -2017-12-01 14:00:00,1.18697,1.18745,1.18606,1.1861,3212 -2017-12-01 15:00:00,1.18618,1.18762,1.18508,1.18648,6145 -2017-12-01 16:00:00,1.18648,1.19349,1.18644,1.19077,25625 -2017-12-01 17:00:00,1.19082,1.19174,1.18962,1.19066,10356 -2017-12-01 18:00:00,1.19066,1.19107,1.1886,1.18949,4636 -2017-12-01 19:00:00,1.18948,1.19009,1.18852,1.18941,2733 -2017-12-01 20:00:00,1.18946,1.18968,1.18898,1.18909,1329 -2017-12-01 21:00:00,1.18914,1.19002,1.18908,1.18974,840 -2017-12-03 22:00:00,1.1865,1.18738,1.18604,1.18692,1101 -2017-12-03 23:00:00,1.18695,1.18756,1.18564,1.1857,1396 -2017-12-04 00:00:00,1.18571,1.18728,1.1856,1.18711,1840 -2017-12-04 01:00:00,1.1871,1.18761,1.18669,1.1875,917 -2017-12-04 02:00:00,1.18744,1.18744,1.18682,1.18728,711 -2017-12-04 03:00:00,1.18733,1.18758,1.18698,1.1871,489 -2017-12-04 04:00:00,1.18711,1.18718,1.18674,1.18708,520 -2017-12-04 05:00:00,1.18702,1.1872,1.18676,1.18676,704 -2017-12-04 06:00:00,1.18676,1.18694,1.18621,1.18654,781 -2017-12-04 07:00:00,1.18652,1.18658,1.18362,1.18494,3314 -2017-12-04 08:00:00,1.18495,1.1879,1.18494,1.18725,2984 -2017-12-04 09:00:00,1.18727,1.18737,1.18508,1.18545,2072 -2017-12-04 10:00:00,1.1854,1.18602,1.18436,1.18494,1657 -2017-12-04 11:00:00,1.18488,1.18616,1.18471,1.18585,1889 -2017-12-04 12:00:00,1.18586,1.18586,1.18454,1.18566,2341 -2017-12-04 13:00:00,1.18565,1.18678,1.1843,1.18456,2989 -2017-12-04 14:00:00,1.18451,1.18466,1.18336,1.18425,3485 -2017-12-04 15:00:00,1.18424,1.1853,1.18293,1.18496,6234 -2017-12-04 16:00:00,1.18499,1.186,1.18456,1.18481,3114 -2017-12-04 17:00:00,1.18477,1.18522,1.1842,1.18436,1547 -2017-12-04 18:00:00,1.18437,1.18516,1.18433,1.18495,898 -2017-12-04 19:00:00,1.18495,1.18596,1.18488,1.18558,1343 -2017-12-04 20:00:00,1.18558,1.18584,1.18476,1.18568,1052 -2017-12-04 21:00:00,1.18567,1.18688,1.18566,1.18653,855 -2017-12-04 22:00:00,1.18642,1.18688,1.18618,1.18679,1400 -2017-12-04 23:00:00,1.18678,1.18706,1.18648,1.18679,462 -2017-12-05 00:00:00,1.18676,1.18728,1.1864,1.18708,1178 -2017-12-05 01:00:00,1.18712,1.18748,1.1869,1.18733,704 -2017-12-05 02:00:00,1.18733,1.18768,1.18701,1.18736,542 -2017-12-05 03:00:00,1.18734,1.18756,1.18716,1.18756,790 -2017-12-05 04:00:00,1.18756,1.18758,1.18692,1.18696,593 -2017-12-05 05:00:00,1.18702,1.18728,1.18668,1.18671,347 -2017-12-05 06:00:00,1.18671,1.187,1.1863,1.18668,716 -2017-12-05 07:00:00,1.18666,1.18768,1.18568,1.18582,1784 -2017-12-05 08:00:00,1.1858,1.1862,1.1845,1.1848,2786 -2017-12-05 09:00:00,1.1848,1.18596,1.18421,1.18528,1833 -2017-12-05 10:00:00,1.18527,1.18669,1.18491,1.18628,1407 -2017-12-05 11:00:00,1.18634,1.1874,1.18611,1.18658,1413 -2017-12-05 12:00:00,1.18653,1.18671,1.18462,1.18476,1472 -2017-12-05 13:00:00,1.18474,1.1848,1.18279,1.1835,2465 -2017-12-05 14:00:00,1.1835,1.18372,1.18132,1.18281,4956 -2017-12-05 15:00:00,1.18288,1.18429,1.18222,1.18324,5970 -2017-12-05 16:00:00,1.18324,1.18332,1.18078,1.18205,3801 -2017-12-05 17:00:00,1.18204,1.18248,1.18048,1.18058,2484 -2017-12-05 18:00:00,1.18054,1.18079,1.18006,1.18072,1857 -2017-12-05 19:00:00,1.18068,1.18182,1.18065,1.18144,1523 -2017-12-05 20:00:00,1.18142,1.18296,1.18139,1.18242,1400 -2017-12-05 21:00:00,1.18248,1.18287,1.18234,1.18262,435 -2017-12-05 22:00:00,1.18258,1.18302,1.18244,1.18288,791 -2017-12-05 23:00:00,1.18285,1.18312,1.18256,1.18305,841 -2017-12-06 00:00:00,1.1831,1.1831,1.18166,1.18211,1164 -2017-12-06 01:00:00,1.18208,1.18296,1.1819,1.18265,828 -2017-12-06 02:00:00,1.18268,1.18305,1.18258,1.18275,974 -2017-12-06 03:00:00,1.1828,1.18486,1.18272,1.18427,1531 -2017-12-06 04:00:00,1.18432,1.18444,1.18382,1.18388,932 -2017-12-06 05:00:00,1.18388,1.18454,1.18362,1.1844,602 -2017-12-06 06:00:00,1.1844,1.18442,1.18318,1.18336,717 -2017-12-06 07:00:00,1.18341,1.18395,1.18192,1.18234,2438 -2017-12-06 08:00:00,1.18234,1.18312,1.18132,1.18223,2262 -2017-12-06 09:00:00,1.18226,1.18262,1.18124,1.18234,1972 -2017-12-06 10:00:00,1.18234,1.18334,1.18222,1.18282,1657 -2017-12-06 11:00:00,1.18283,1.18283,1.18085,1.18129,2383 -2017-12-06 12:00:00,1.18128,1.18157,1.18048,1.18132,1548 -2017-12-06 13:00:00,1.18136,1.18237,1.18,1.18076,2951 -2017-12-06 14:00:00,1.1808,1.18082,1.17872,1.17902,3996 -2017-12-06 15:00:00,1.17902,1.17991,1.17854,1.17884,3253 -2017-12-06 16:00:00,1.17888,1.17954,1.17804,1.17885,2235 -2017-12-06 17:00:00,1.17884,1.17948,1.17838,1.17933,1606 -2017-12-06 18:00:00,1.17934,1.17976,1.17889,1.1792,1412 -2017-12-06 19:00:00,1.1792,1.17992,1.17897,1.17912,1423 -2017-12-06 20:00:00,1.17913,1.18006,1.179,1.17956,1305 -2017-12-06 21:00:00,1.17956,1.17968,1.17918,1.1796,485 -2017-12-06 22:00:00,1.17946,1.1806,1.17946,1.18035,1185 -2017-12-06 23:00:00,1.18042,1.18088,1.18014,1.18041,637 -2017-12-07 00:00:00,1.18046,1.18068,1.17954,1.17957,759 -2017-12-07 01:00:00,1.17958,1.18014,1.17926,1.17985,791 -2017-12-07 02:00:00,1.17981,1.18026,1.17956,1.17997,685 -2017-12-07 03:00:00,1.17994,1.18052,1.1799,1.18038,483 -2017-12-07 04:00:00,1.18038,1.18069,1.1798,1.17983,410 -2017-12-07 05:00:00,1.17978,1.18,1.17895,1.17919,586 -2017-12-07 06:00:00,1.17922,1.1793,1.17866,1.17929,728 -2017-12-07 07:00:00,1.17932,1.1797,1.17874,1.17956,1324 -2017-12-07 08:00:00,1.17956,1.18049,1.17886,1.17912,1719 -2017-12-07 09:00:00,1.17912,1.17982,1.1788,1.17892,1074 -2017-12-07 10:00:00,1.17892,1.17922,1.17783,1.17794,1318 -2017-12-07 11:00:00,1.17798,1.17891,1.17761,1.1788,1271 -2017-12-07 12:00:00,1.1788,1.17928,1.17765,1.17777,1600 -2017-12-07 13:00:00,1.17777,1.1801,1.17766,1.17998,2008 -2017-12-07 14:00:00,1.17996,1.17996,1.17882,1.17969,2784 -2017-12-07 15:00:00,1.17966,1.18002,1.1787,1.17896,3100 -2017-12-07 16:00:00,1.17897,1.18,1.17867,1.17895,1978 -2017-12-07 17:00:00,1.17897,1.17986,1.17862,1.17971,1336 -2017-12-07 18:00:00,1.17974,1.18148,1.1793,1.17963,3221 -2017-12-07 19:00:00,1.17966,1.17966,1.17728,1.1773,2362 -2017-12-07 20:00:00,1.1773,1.17809,1.17729,1.1775,1668 -2017-12-07 21:00:00,1.17748,1.17759,1.17719,1.17726,325 -2017-12-07 22:00:00,1.17741,1.17764,1.17721,1.17756,331 -2017-12-07 23:00:00,1.17759,1.1777,1.1771,1.17728,467 -2017-12-08 00:00:00,1.17723,1.17746,1.17664,1.17686,666 -2017-12-08 01:00:00,1.17686,1.17692,1.17614,1.17636,895 -2017-12-08 02:00:00,1.17636,1.17696,1.17628,1.1767,731 -2017-12-08 03:00:00,1.17667,1.17692,1.17652,1.17676,515 -2017-12-08 04:00:00,1.17676,1.17686,1.17612,1.17619,409 -2017-12-08 05:00:00,1.17621,1.17662,1.17606,1.17649,539 -2017-12-08 06:00:00,1.17648,1.17678,1.17516,1.1752,1633 -2017-12-08 07:00:00,1.1752,1.17541,1.17425,1.17513,2307 -2017-12-08 08:00:00,1.17508,1.17544,1.17347,1.17354,2550 -2017-12-08 09:00:00,1.17352,1.17477,1.17324,1.1737,1752 -2017-12-08 10:00:00,1.1737,1.1744,1.17345,1.17438,1105 -2017-12-08 11:00:00,1.17436,1.17436,1.17338,1.1738,1064 -2017-12-08 12:00:00,1.17382,1.17456,1.17312,1.17353,1619 -2017-12-08 13:00:00,1.17358,1.17692,1.173,1.17629,8164 -2017-12-08 14:00:00,1.17634,1.17702,1.1752,1.17558,4642 -2017-12-08 15:00:00,1.17558,1.17716,1.17478,1.17512,5148 -2017-12-08 16:00:00,1.17512,1.17662,1.17466,1.17605,2838 -2017-12-08 17:00:00,1.176,1.17668,1.17546,1.1756,1768 -2017-12-08 18:00:00,1.17566,1.17656,1.17556,1.17636,815 -2017-12-08 19:00:00,1.17638,1.17682,1.17632,1.17673,884 -2017-12-08 20:00:00,1.17669,1.17706,1.17642,1.17647,649 -2017-12-08 21:00:00,1.17649,1.17746,1.17648,1.17721,1133 -2017-12-10 22:00:00,1.17642,1.17714,1.17637,1.17702,616 -2017-12-10 23:00:00,1.17704,1.17721,1.17666,1.17677,672 -2017-12-11 00:00:00,1.17672,1.17744,1.17671,1.17714,1509 -2017-12-11 01:00:00,1.17718,1.1778,1.17718,1.1777,882 -2017-12-11 02:00:00,1.17768,1.17784,1.17753,1.17772,302 -2017-12-11 03:00:00,1.17776,1.1784,1.17771,1.17808,814 -2017-12-11 04:00:00,1.17806,1.17808,1.17762,1.17786,368 -2017-12-11 05:00:00,1.17789,1.17844,1.17778,1.17802,521 -2017-12-11 06:00:00,1.17802,1.1786,1.17784,1.17788,596 -2017-12-11 07:00:00,1.17784,1.17914,1.17778,1.17833,1417 -2017-12-11 08:00:00,1.1783,1.17964,1.17754,1.17941,1874 -2017-12-11 09:00:00,1.17936,1.1801,1.17885,1.17974,1261 -2017-12-11 10:00:00,1.17974,1.18009,1.17929,1.17984,1042 -2017-12-11 11:00:00,1.17985,1.18032,1.1789,1.17913,1131 -2017-12-11 12:00:00,1.17914,1.17974,1.1789,1.17938,1223 -2017-12-11 13:00:00,1.1794,1.1796,1.17767,1.1778,1569 -2017-12-11 14:00:00,1.17776,1.1796,1.17774,1.17952,1707 -2017-12-11 15:00:00,1.17957,1.18118,1.17921,1.17952,3167 -2017-12-11 16:00:00,1.1795,1.18066,1.17942,1.18014,2128 -2017-12-11 17:00:00,1.18014,1.18014,1.17869,1.17916,1370 -2017-12-11 18:00:00,1.17921,1.17942,1.17838,1.17916,747 -2017-12-11 19:00:00,1.17912,1.17943,1.17833,1.17864,674 -2017-12-11 20:00:00,1.17865,1.17876,1.17715,1.1773,864 -2017-12-11 21:00:00,1.1773,1.17744,1.17639,1.17693,889 -2017-12-11 22:00:00,1.17725,1.17748,1.17687,1.17732,777 -2017-12-11 23:00:00,1.17724,1.17782,1.1772,1.17762,907 -2017-12-12 00:00:00,1.1776,1.1778,1.17713,1.17756,567 -2017-12-12 01:00:00,1.1776,1.17798,1.17688,1.17694,626 -2017-12-12 02:00:00,1.1769,1.17698,1.17646,1.17688,359 -2017-12-12 03:00:00,1.17683,1.1772,1.17678,1.17688,343 -2017-12-12 04:00:00,1.17688,1.1772,1.1768,1.17717,263 -2017-12-12 05:00:00,1.17718,1.17755,1.17716,1.17731,321 -2017-12-12 06:00:00,1.17731,1.17793,1.17724,1.17762,463 -2017-12-12 07:00:00,1.17763,1.17844,1.17714,1.17714,1158 -2017-12-12 08:00:00,1.1771,1.17926,1.177,1.17909,2336 -2017-12-12 09:00:00,1.17909,1.1791,1.1778,1.17828,1601 -2017-12-12 10:00:00,1.1783,1.17862,1.17708,1.17762,1566 -2017-12-12 11:00:00,1.17758,1.17809,1.17716,1.17751,982 -2017-12-12 12:00:00,1.17756,1.17795,1.17692,1.17746,1355 -2017-12-12 13:00:00,1.17743,1.17743,1.175,1.17505,2029 -2017-12-12 14:00:00,1.17503,1.1752,1.17353,1.17418,2197 -2017-12-12 15:00:00,1.1742,1.17434,1.17222,1.17296,1823 -2017-12-12 16:00:00,1.17301,1.17307,1.17177,1.17236,2091 -2017-12-12 17:00:00,1.17236,1.17388,1.17204,1.17234,2726 -2017-12-12 18:00:00,1.17234,1.17358,1.17208,1.17298,1739 -2017-12-12 19:00:00,1.17302,1.1741,1.17297,1.17388,1148 -2017-12-12 20:00:00,1.17389,1.1746,1.17377,1.17448,972 -2017-12-12 21:00:00,1.17451,1.1749,1.174,1.1743,567 -2017-12-12 22:00:00,1.17415,1.17427,1.17352,1.17368,839 -2017-12-12 23:00:00,1.17367,1.17433,1.17358,1.17426,236 -2017-12-13 00:00:00,1.17432,1.17482,1.1742,1.17472,450 -2017-12-13 01:00:00,1.17468,1.17477,1.17428,1.17431,382 -2017-12-13 02:00:00,1.17428,1.17491,1.17425,1.17484,267 -2017-12-13 03:00:00,1.17484,1.17622,1.17472,1.17576,910 -2017-12-13 04:00:00,1.17576,1.17581,1.17534,1.1754,223 -2017-12-13 05:00:00,1.17536,1.17588,1.17535,1.17544,206 -2017-12-13 06:00:00,1.17545,1.17628,1.17541,1.17556,629 -2017-12-13 07:00:00,1.17557,1.17563,1.17379,1.17386,702 -2017-12-13 08:00:00,1.17383,1.17482,1.17375,1.17412,804 -2017-12-13 09:00:00,1.17408,1.17526,1.1739,1.1749,1192 -2017-12-13 10:00:00,1.1749,1.17544,1.17462,1.1751,1218 -2017-12-13 11:00:00,1.17515,1.17516,1.17385,1.17392,1078 -2017-12-13 12:00:00,1.17392,1.17428,1.17302,1.174,1329 -2017-12-13 13:00:00,1.17399,1.17712,1.17295,1.17576,5308 -2017-12-13 14:00:00,1.17579,1.17624,1.17475,1.17512,2337 -2017-12-13 15:00:00,1.17512,1.17648,1.17488,1.17578,2401 -2017-12-13 16:00:00,1.17582,1.17686,1.1755,1.17604,2352 -2017-12-13 17:00:00,1.17604,1.17708,1.17574,1.17628,1815 -2017-12-13 18:00:00,1.17628,1.17794,1.17628,1.17739,2008 -2017-12-13 19:00:00,1.17743,1.18234,1.1767,1.18202,16282 -2017-12-13 20:00:00,1.18202,1.18262,1.18128,1.18251,4645 -2017-12-13 21:00:00,1.18248,1.1832,1.18214,1.18261,948 -2017-12-13 22:00:00,1.18244,1.18368,1.18228,1.18258,1757 -2017-12-13 23:00:00,1.1826,1.18408,1.18217,1.18364,933 -2017-12-14 00:00:00,1.1836,1.18402,1.18284,1.18395,1516 -2017-12-14 01:00:00,1.184,1.1844,1.18378,1.18424,1048 -2017-12-14 02:00:00,1.18421,1.18422,1.18318,1.18323,825 -2017-12-14 03:00:00,1.18326,1.18378,1.18312,1.18356,550 -2017-12-14 04:00:00,1.18354,1.18384,1.18308,1.18324,521 -2017-12-14 05:00:00,1.18318,1.18347,1.18258,1.18268,436 -2017-12-14 06:00:00,1.18268,1.18268,1.1819,1.18234,765 -2017-12-14 07:00:00,1.1823,1.1826,1.18112,1.18183,1787 -2017-12-14 08:00:00,1.18184,1.18376,1.18168,1.18266,2976 -2017-12-14 09:00:00,1.18268,1.18294,1.18123,1.18192,2181 -2017-12-14 10:00:00,1.18191,1.18345,1.18123,1.1834,1931 -2017-12-14 11:00:00,1.1834,1.18372,1.18204,1.18252,1801 -2017-12-14 12:00:00,1.18258,1.1845,1.18236,1.1833,3828 -2017-12-14 13:00:00,1.18329,1.18628,1.18163,1.18206,9741 -2017-12-14 14:00:00,1.18207,1.18271,1.17945,1.18019,7151 -2017-12-14 15:00:00,1.18018,1.1806,1.1771,1.17776,3929 -2017-12-14 16:00:00,1.1778,1.17838,1.1771,1.17771,3387 -2017-12-14 17:00:00,1.17776,1.17896,1.17718,1.17877,2191 -2017-12-14 18:00:00,1.17873,1.18002,1.17841,1.17977,2591 -2017-12-14 19:00:00,1.17974,1.18015,1.17906,1.17918,1441 -2017-12-14 20:00:00,1.17919,1.17962,1.17852,1.1788,1180 -2017-12-14 21:00:00,1.1788,1.17884,1.17748,1.17771,1167 -2017-12-14 22:00:00,1.17782,1.1781,1.17644,1.17658,2201 -2017-12-14 23:00:00,1.17664,1.17762,1.17649,1.17749,994 -2017-12-15 00:00:00,1.17746,1.17906,1.17731,1.17858,1125 -2017-12-15 01:00:00,1.17852,1.17889,1.17788,1.17848,830 -2017-12-15 02:00:00,1.17852,1.17913,1.17836,1.17859,909 -2017-12-15 03:00:00,1.1786,1.17877,1.17808,1.17818,829 -2017-12-15 04:00:00,1.17818,1.17845,1.17798,1.17842,427 -2017-12-15 05:00:00,1.17842,1.17842,1.17782,1.17835,586 -2017-12-15 06:00:00,1.17835,1.1786,1.17816,1.17844,708 -2017-12-15 07:00:00,1.17838,1.1797,1.17806,1.17918,1516 -2017-12-15 08:00:00,1.17917,1.17945,1.17816,1.17834,1799 -2017-12-15 09:00:00,1.17834,1.1799,1.17792,1.17971,1877 -2017-12-15 10:00:00,1.17966,1.18072,1.17947,1.18056,1690 -2017-12-15 11:00:00,1.18055,1.18124,1.17969,1.17987,1501 -2017-12-15 12:00:00,1.1799,1.18016,1.1791,1.18015,1514 -2017-12-15 13:00:00,1.1802,1.18094,1.17936,1.17995,3036 -2017-12-15 14:00:00,1.17996,1.18004,1.17716,1.17774,3775 -2017-12-15 15:00:00,1.17773,1.17832,1.17618,1.17637,4189 -2017-12-15 16:00:00,1.17642,1.17796,1.17606,1.17778,3209 -2017-12-15 17:00:00,1.17784,1.17819,1.17632,1.17649,1859 -2017-12-15 18:00:00,1.17652,1.17655,1.17504,1.17551,1483 -2017-12-15 19:00:00,1.17546,1.1761,1.17536,1.17568,1132 -2017-12-15 20:00:00,1.17564,1.17596,1.17538,1.1754,1336 -2017-12-15 21:00:00,1.17543,1.17563,1.17488,1.17503,1972 -2017-12-17 22:00:00,1.17459,1.17494,1.17382,1.17466,1365 -2017-12-17 23:00:00,1.17476,1.17516,1.17404,1.17434,1772 -2017-12-18 00:00:00,1.17432,1.1756,1.17422,1.17498,2077 -2017-12-18 01:00:00,1.17492,1.17572,1.17489,1.17566,634 -2017-12-18 02:00:00,1.17566,1.1763,1.17557,1.17566,569 -2017-12-18 03:00:00,1.17569,1.17656,1.17564,1.17644,537 -2017-12-18 04:00:00,1.17642,1.17646,1.17594,1.17608,535 -2017-12-18 05:00:00,1.17611,1.17628,1.17597,1.17606,262 -2017-12-18 06:00:00,1.17606,1.17713,1.17606,1.17681,712 -2017-12-18 07:00:00,1.17676,1.17812,1.17619,1.17807,2324 -2017-12-18 08:00:00,1.17808,1.17913,1.17754,1.17888,2688 -2017-12-18 09:00:00,1.17892,1.17952,1.17858,1.17886,2021 -2017-12-18 10:00:00,1.17884,1.17956,1.17841,1.17952,1258 -2017-12-18 11:00:00,1.17956,1.17984,1.17876,1.1793,1503 -2017-12-18 12:00:00,1.17925,1.17956,1.17884,1.17952,1137 -2017-12-18 13:00:00,1.17948,1.1799,1.17918,1.17937,1349 -2017-12-18 14:00:00,1.17936,1.18098,1.17879,1.18078,2420 -2017-12-18 15:00:00,1.18079,1.18344,1.18058,1.1812,2745 -2017-12-18 16:00:00,1.18121,1.18167,1.17976,1.18044,1983 -2017-12-18 17:00:00,1.18042,1.18054,1.17896,1.17904,1376 -2017-12-18 18:00:00,1.17906,1.17948,1.17884,1.17934,1169 -2017-12-18 19:00:00,1.17937,1.17979,1.17753,1.17841,1254 -2017-12-18 20:00:00,1.17846,1.17856,1.1779,1.17812,962 -2017-12-18 21:00:00,1.17816,1.1784,1.17792,1.1781,519 -2017-12-18 22:00:00,1.17819,1.17876,1.17808,1.1783,1032 -2017-12-18 23:00:00,1.17825,1.17851,1.17818,1.17839,472 -2017-12-19 00:00:00,1.17834,1.17845,1.17772,1.17836,720 -2017-12-19 01:00:00,1.17836,1.1784,1.17766,1.17824,535 -2017-12-19 02:00:00,1.1782,1.1789,1.17802,1.17868,524 -2017-12-19 03:00:00,1.1787,1.179,1.17856,1.17888,513 -2017-12-19 04:00:00,1.1789,1.17928,1.1787,1.17924,340 -2017-12-19 05:00:00,1.1792,1.1796,1.179,1.17928,397 -2017-12-19 06:00:00,1.17928,1.17987,1.17902,1.17944,593 -2017-12-19 07:00:00,1.17943,1.18067,1.1791,1.18061,2916 -2017-12-19 08:00:00,1.18062,1.18184,1.18022,1.18057,2066 -2017-12-19 09:00:00,1.18058,1.18121,1.1791,1.18065,2187 -2017-12-19 10:00:00,1.1806,1.1813,1.17998,1.18078,1669 -2017-12-19 11:00:00,1.18078,1.18134,1.18058,1.181,1383 -2017-12-19 12:00:00,1.181,1.1829,1.18084,1.18286,1810 -2017-12-19 13:00:00,1.18282,1.18318,1.18152,1.18268,2805 -2017-12-19 14:00:00,1.1827,1.18304,1.18048,1.18092,2544 -2017-12-19 15:00:00,1.18096,1.18292,1.18084,1.18102,3277 -2017-12-19 16:00:00,1.181,1.18224,1.18052,1.18216,2833 -2017-12-19 17:00:00,1.18212,1.18294,1.18156,1.1829,2763 -2017-12-19 18:00:00,1.18294,1.1849,1.18282,1.18442,2798 -2017-12-19 19:00:00,1.18442,1.18477,1.18425,1.18449,1196 -2017-12-19 20:00:00,1.1845,1.18465,1.18403,1.18408,1203 -2017-12-19 21:00:00,1.18408,1.18429,1.18382,1.18398,550 -2017-12-19 22:00:00,1.18403,1.18456,1.18382,1.18424,925 -2017-12-19 23:00:00,1.18424,1.18426,1.18366,1.18374,378 -2017-12-20 00:00:00,1.18372,1.18438,1.18353,1.18437,589 -2017-12-20 01:00:00,1.18442,1.18465,1.18407,1.18419,523 -2017-12-20 02:00:00,1.18422,1.18449,1.18412,1.18429,336 -2017-12-20 03:00:00,1.18432,1.18472,1.18424,1.18468,259 -2017-12-20 04:00:00,1.18466,1.18466,1.1841,1.18416,273 -2017-12-20 05:00:00,1.18412,1.18462,1.1841,1.18457,574 -2017-12-20 06:00:00,1.18458,1.18488,1.18294,1.18298,950 -2017-12-20 07:00:00,1.18297,1.18424,1.18291,1.18416,1402 -2017-12-20 08:00:00,1.18412,1.18542,1.18352,1.18472,2763 -2017-12-20 09:00:00,1.18471,1.1853,1.18364,1.18378,1833 -2017-12-20 10:00:00,1.18382,1.1858,1.18358,1.18446,2036 -2017-12-20 11:00:00,1.18448,1.18488,1.1836,1.18363,1620 -2017-12-20 12:00:00,1.18364,1.18484,1.18322,1.18418,1806 -2017-12-20 13:00:00,1.18418,1.18492,1.18408,1.18438,2105 -2017-12-20 14:00:00,1.18438,1.18637,1.18436,1.186,2973 -2017-12-20 15:00:00,1.186,1.19016,1.18545,1.1883,5007 -2017-12-20 16:00:00,1.18832,1.1885,1.18751,1.18807,2588 -2017-12-20 17:00:00,1.18802,1.18814,1.1874,1.1877,1787 -2017-12-20 18:00:00,1.18774,1.18892,1.1877,1.1881,1381 -2017-12-20 19:00:00,1.18814,1.18822,1.18748,1.18782,1185 -2017-12-20 20:00:00,1.18782,1.18826,1.18759,1.18786,1191 -2017-12-20 21:00:00,1.18785,1.18785,1.18688,1.18712,534 -2017-12-20 22:00:00,1.18683,1.18752,1.18683,1.1873,1045 -2017-12-20 23:00:00,1.1873,1.18822,1.18694,1.18774,782 -2017-12-21 00:00:00,1.18774,1.18821,1.18739,1.18746,955 -2017-12-21 01:00:00,1.18748,1.18758,1.18708,1.18708,589 -2017-12-21 02:00:00,1.18704,1.18744,1.187,1.18742,301 -2017-12-21 03:00:00,1.18746,1.1876,1.18648,1.1866,651 -2017-12-21 04:00:00,1.18658,1.18686,1.18642,1.18672,355 -2017-12-21 05:00:00,1.1867,1.18684,1.1863,1.18682,495 -2017-12-21 06:00:00,1.18682,1.18701,1.18634,1.18694,517 -2017-12-21 07:00:00,1.18692,1.18752,1.18651,1.18722,1685 -2017-12-21 08:00:00,1.18728,1.18806,1.18642,1.18786,2303 -2017-12-21 09:00:00,1.18786,1.18868,1.18732,1.18808,1861 -2017-12-21 10:00:00,1.18807,1.18898,1.18704,1.18708,1838 -2017-12-21 11:00:00,1.1871,1.18774,1.1866,1.18662,1228 -2017-12-21 12:00:00,1.1866,1.18695,1.1851,1.18629,2024 -2017-12-21 13:00:00,1.18624,1.1871,1.18548,1.18588,2246 -2017-12-21 14:00:00,1.18582,1.18702,1.18492,1.18647,2368 -2017-12-21 15:00:00,1.1865,1.18698,1.18544,1.18602,2468 -2017-12-21 16:00:00,1.18604,1.18792,1.18586,1.18714,2689 -2017-12-21 17:00:00,1.18716,1.18734,1.1865,1.18677,838 -2017-12-21 18:00:00,1.1868,1.18692,1.1863,1.1867,987 -2017-12-21 19:00:00,1.1867,1.18725,1.18614,1.18718,833 -2017-12-21 20:00:00,1.18718,1.18792,1.187,1.18765,938 -2017-12-21 21:00:00,1.18764,1.18781,1.18727,1.18739,501 -2017-12-21 22:00:00,1.18756,1.1876,1.18645,1.1866,854 -2017-12-21 23:00:00,1.1866,1.1869,1.18524,1.18524,955 -2017-12-22 00:00:00,1.18522,1.1854,1.1817,1.18441,3858 -2017-12-22 01:00:00,1.18444,1.1848,1.18353,1.18446,1646 -2017-12-22 02:00:00,1.18442,1.18514,1.18426,1.1851,918 -2017-12-22 03:00:00,1.18509,1.1852,1.18471,1.18489,545 -2017-12-22 04:00:00,1.18494,1.1851,1.18476,1.18482,408 -2017-12-22 05:00:00,1.1848,1.1851,1.18474,1.18498,402 -2017-12-22 06:00:00,1.18498,1.18588,1.18466,1.18566,981 -2017-12-22 07:00:00,1.18564,1.18613,1.18522,1.18524,1215 -2017-12-22 08:00:00,1.18522,1.18588,1.18445,1.18548,2360 -2017-12-22 09:00:00,1.18549,1.18622,1.18457,1.18492,2109 -2017-12-22 10:00:00,1.18488,1.18547,1.18454,1.18476,1476 -2017-12-22 11:00:00,1.18471,1.18574,1.18455,1.18519,1855 -2017-12-22 12:00:00,1.18514,1.18558,1.18474,1.18494,1465 -2017-12-22 13:00:00,1.185,1.18551,1.18484,1.18548,1761 -2017-12-22 14:00:00,1.18546,1.18568,1.18434,1.18514,2678 -2017-12-22 15:00:00,1.18514,1.18515,1.18286,1.18347,2628 -2017-12-22 16:00:00,1.18346,1.1844,1.18302,1.18384,1814 -2017-12-22 17:00:00,1.1839,1.18533,1.18387,1.1853,1630 -2017-12-22 18:00:00,1.18534,1.18576,1.18505,1.18508,1027 -2017-12-22 19:00:00,1.18504,1.1856,1.1844,1.18508,1121 -2017-12-22 20:00:00,1.18508,1.18591,1.18504,1.18584,885 -2017-12-22 21:00:00,1.18584,1.18644,1.18556,1.18617,1234 -2017-12-25 22:00:00,1.18688,1.18754,1.18608,1.18712,774 -2017-12-25 23:00:00,1.18712,1.18743,1.18655,1.18711,737 -2017-12-26 00:00:00,1.18705,1.18728,1.18662,1.18686,971 -2017-12-26 01:00:00,1.18687,1.18698,1.18646,1.18656,624 -2017-12-26 02:00:00,1.18658,1.18736,1.18628,1.18715,491 -2017-12-26 03:00:00,1.1872,1.18722,1.18687,1.18709,293 -2017-12-26 04:00:00,1.18711,1.18719,1.18674,1.18696,251 -2017-12-26 05:00:00,1.18696,1.1871,1.18675,1.18706,202 -2017-12-26 06:00:00,1.18709,1.18714,1.18672,1.18675,240 -2017-12-26 07:00:00,1.1867,1.18757,1.18669,1.18724,285 -2017-12-26 08:00:00,1.1872,1.18756,1.18687,1.18692,358 -2017-12-26 09:00:00,1.18687,1.1872,1.1858,1.1861,599 -2017-12-26 10:00:00,1.18604,1.18608,1.18554,1.18597,403 -2017-12-26 11:00:00,1.186,1.18603,1.18502,1.18512,350 -2017-12-26 12:00:00,1.18512,1.18536,1.18468,1.18468,979 -2017-12-26 13:00:00,1.1847,1.18558,1.18466,1.18551,547 -2017-12-26 14:00:00,1.18552,1.18779,1.18552,1.18775,1653 -2017-12-26 15:00:00,1.18775,1.18792,1.18636,1.18651,1352 -2017-12-26 16:00:00,1.1865,1.18706,1.18632,1.18666,853 -2017-12-26 17:00:00,1.18671,1.18718,1.18614,1.18704,595 -2017-12-26 18:00:00,1.18708,1.1872,1.18664,1.18701,459 -2017-12-26 19:00:00,1.18698,1.18698,1.18616,1.18635,435 -2017-12-26 20:00:00,1.1864,1.1866,1.18618,1.1863,466 -2017-12-26 21:00:00,1.18625,1.18644,1.1858,1.18584,342 -2017-12-26 22:00:00,1.18569,1.18648,1.18562,1.18604,705 -2017-12-26 23:00:00,1.18613,1.18613,1.18554,1.18574,423 -2017-12-27 00:00:00,1.18576,1.1865,1.18548,1.18628,853 -2017-12-27 01:00:00,1.18624,1.18638,1.18578,1.18605,417 -2017-12-27 02:00:00,1.186,1.1864,1.18592,1.18637,295 -2017-12-27 03:00:00,1.18639,1.18674,1.18622,1.18634,272 -2017-12-27 04:00:00,1.18637,1.1877,1.1862,1.18746,476 -2017-12-27 05:00:00,1.1875,1.18806,1.18735,1.18779,409 -2017-12-27 06:00:00,1.18782,1.18849,1.18778,1.18786,523 -2017-12-27 07:00:00,1.18792,1.18829,1.18648,1.18678,1377 -2017-12-27 08:00:00,1.18674,1.18772,1.18656,1.187,2685 -2017-12-27 09:00:00,1.18702,1.18912,1.18692,1.1888,2214 -2017-12-27 10:00:00,1.18878,1.18932,1.18846,1.18927,1513 -2017-12-27 11:00:00,1.18925,1.18954,1.18804,1.18926,1731 -2017-12-27 12:00:00,1.1893,1.19,1.18902,1.18929,1757 -2017-12-27 13:00:00,1.18934,1.19046,1.18927,1.19012,1512 -2017-12-27 14:00:00,1.19008,1.19071,1.18965,1.19068,1654 -2017-12-27 15:00:00,1.19066,1.19105,1.18932,1.18949,2015 -2017-12-27 16:00:00,1.18954,1.19016,1.18856,1.19016,2273 -2017-12-27 17:00:00,1.19011,1.19034,1.18967,1.1899,1132 -2017-12-27 18:00:00,1.18994,1.19036,1.1895,1.18984,1239 -2017-12-27 19:00:00,1.18988,1.19006,1.18948,1.18974,1438 -2017-12-27 20:00:00,1.18979,1.18984,1.18924,1.18946,883 -2017-12-27 21:00:00,1.18943,1.18957,1.18844,1.18881,739 -2017-12-27 22:00:00,1.18979,1.19037,1.18954,1.18996,1189 -2017-12-27 23:00:00,1.18994,1.19015,1.18968,1.19004,656 -2017-12-28 00:00:00,1.19001,1.1904,1.18968,1.19033,810 -2017-12-28 01:00:00,1.1903,1.19062,1.1901,1.19059,398 -2017-12-28 02:00:00,1.19056,1.19106,1.19025,1.19091,669 -2017-12-28 03:00:00,1.19094,1.19111,1.1908,1.19102,230 -2017-12-28 04:00:00,1.191,1.19186,1.191,1.19176,506 -2017-12-28 05:00:00,1.19181,1.19332,1.19163,1.19317,966 -2017-12-28 06:00:00,1.19317,1.1935,1.19262,1.19323,580 -2017-12-28 07:00:00,1.1932,1.19412,1.19284,1.194,1154 -2017-12-28 08:00:00,1.19404,1.19467,1.19332,1.19372,1609 -2017-12-28 09:00:00,1.19376,1.19381,1.19294,1.1932,1202 -2017-12-28 10:00:00,1.19322,1.19332,1.19237,1.19314,1219 -2017-12-28 11:00:00,1.19319,1.19369,1.1929,1.19367,810 -2017-12-28 12:00:00,1.19371,1.19427,1.1932,1.19402,1299 -2017-12-28 13:00:00,1.19403,1.19476,1.19326,1.1947,1578 -2017-12-28 14:00:00,1.19473,1.19502,1.19428,1.19478,1562 -2017-12-28 15:00:00,1.19478,1.19508,1.19366,1.19372,1315 -2017-12-28 16:00:00,1.19376,1.19544,1.19373,1.19512,1709 -2017-12-28 17:00:00,1.19516,1.19552,1.19488,1.19533,1539 -2017-12-28 18:00:00,1.1953,1.19591,1.19521,1.19584,873 -2017-12-28 19:00:00,1.19578,1.19587,1.19498,1.19526,907 -2017-12-28 20:00:00,1.19526,1.19536,1.19408,1.19408,730 -2017-12-28 21:00:00,1.19408,1.19454,1.19392,1.19448,360 -2017-12-28 22:00:00,1.19432,1.1947,1.1936,1.19384,651 -2017-12-28 23:00:00,1.19386,1.19416,1.19383,1.19396,330 -2017-12-29 00:00:00,1.19392,1.19472,1.19392,1.19444,409 -2017-12-29 01:00:00,1.1944,1.19492,1.19368,1.19426,804 -2017-12-29 02:00:00,1.19426,1.19482,1.19376,1.19476,736 -2017-12-29 03:00:00,1.19474,1.19474,1.19419,1.19428,380 -2017-12-29 04:00:00,1.19433,1.19462,1.19414,1.19445,411 -2017-12-29 05:00:00,1.19442,1.19496,1.1944,1.19488,383 -2017-12-29 06:00:00,1.19488,1.19553,1.19488,1.19552,564 -2017-12-29 07:00:00,1.1955,1.19587,1.19462,1.19519,1427 -2017-12-29 08:00:00,1.19518,1.19692,1.19516,1.19674,2057 -2017-12-29 09:00:00,1.19676,1.19876,1.19674,1.19814,1823 -2017-12-29 10:00:00,1.19818,1.19854,1.19736,1.19804,1582 -2017-12-29 11:00:00,1.1981,1.19898,1.19794,1.19872,1157 -2017-12-29 12:00:00,1.19877,1.19952,1.19846,1.19951,1492 -2017-12-29 13:00:00,1.19952,1.19985,1.19826,1.19869,1686 -2017-12-29 14:00:00,1.19865,1.19955,1.19854,1.1993,1190 -2017-12-29 15:00:00,1.1993,1.20115,1.19876,1.201,2448 -2017-12-29 16:00:00,1.20101,1.20227,1.2002,1.2022,2636 -2017-12-29 17:00:00,1.20225,1.20256,1.20192,1.20212,1534 -2017-12-29 18:00:00,1.20214,1.20243,1.20118,1.20139,1073 -2017-12-29 19:00:00,1.2014,1.20142,1.20072,1.20093,699 -2017-12-29 20:00:00,1.20098,1.20108,1.19976,1.19982,816 -2017-12-29 21:00:00,1.19984,1.20071,1.19922,1.20039,998 -2018-01-01 22:00:00,1.20071,1.20174,1.20044,1.20152,338 -2018-01-01 23:00:00,1.20148,1.20162,1.20019,1.20108,2917 -2018-01-02 00:00:00,1.20105,1.20178,1.2009,1.20162,804 -2018-01-02 01:00:00,1.20168,1.20236,1.20143,1.20156,1208 -2018-01-02 02:00:00,1.2016,1.20166,1.20079,1.20096,766 -2018-01-02 03:00:00,1.201,1.20212,1.20095,1.2012,683 -2018-01-02 04:00:00,1.20126,1.20196,1.20116,1.20175,497 -2018-01-02 05:00:00,1.2018,1.20245,1.2016,1.20245,427 -2018-01-02 06:00:00,1.20245,1.20307,1.20226,1.20288,659 -2018-01-02 07:00:00,1.20284,1.20382,1.20242,1.2036,2185 -2018-01-02 08:00:00,1.20365,1.20475,1.20322,1.2045,1853 -2018-01-02 09:00:00,1.20452,1.20706,1.20419,1.20706,1797 -2018-01-02 10:00:00,1.20703,1.20812,1.20617,1.20686,2419 -2018-01-02 11:00:00,1.20689,1.20708,1.20592,1.20594,1511 -2018-01-02 12:00:00,1.20592,1.20686,1.2057,1.2063,1805 -2018-01-02 13:00:00,1.20634,1.20666,1.20564,1.20576,1925 -2018-01-02 14:00:00,1.20571,1.2059,1.20353,1.2039,2672 -2018-01-02 15:00:00,1.20394,1.2046,1.20266,1.20444,3186 -2018-01-02 16:00:00,1.20443,1.2059,1.20434,1.20492,3120 -2018-01-02 17:00:00,1.20495,1.20538,1.2041,1.20446,1716 -2018-01-02 18:00:00,1.2044,1.20496,1.20418,1.20442,837 -2018-01-02 19:00:00,1.20442,1.20538,1.20432,1.20532,664 -2018-01-02 20:00:00,1.20532,1.20606,1.20518,1.20593,676 -2018-01-02 21:00:00,1.20598,1.20656,1.20548,1.2058,965 -2018-01-02 22:00:00,1.2059,1.2059,1.20549,1.20574,239 -2018-01-02 23:00:00,1.20576,1.20666,1.20569,1.20618,540 -2018-01-03 00:00:00,1.20624,1.2064,1.20491,1.20594,1008 -2018-01-03 01:00:00,1.20589,1.20636,1.20447,1.20532,981 -2018-01-03 02:00:00,1.20527,1.20533,1.2042,1.20425,692 -2018-01-03 03:00:00,1.20428,1.20479,1.20418,1.20469,287 -2018-01-03 04:00:00,1.20474,1.20538,1.20464,1.20509,351 -2018-01-03 05:00:00,1.20509,1.20591,1.20494,1.20585,503 -2018-01-03 06:00:00,1.20585,1.20606,1.20442,1.20452,948 -2018-01-03 07:00:00,1.20453,1.20492,1.20346,1.20392,2009 -2018-01-03 08:00:00,1.20391,1.20428,1.20312,1.20427,1711 -2018-01-03 09:00:00,1.20432,1.20434,1.20344,1.20382,1193 -2018-01-03 10:00:00,1.20378,1.20404,1.20153,1.20178,2135 -2018-01-03 11:00:00,1.20182,1.2019,1.20108,1.2015,2079 -2018-01-03 12:00:00,1.2015,1.20237,1.2011,1.20235,1469 -2018-01-03 13:00:00,1.20236,1.20346,1.202,1.20328,1507 -2018-01-03 14:00:00,1.20326,1.20327,1.20143,1.20174,1788 -2018-01-03 15:00:00,1.20174,1.20246,1.20034,1.20236,3330 -2018-01-03 16:00:00,1.20231,1.20326,1.202,1.20296,1383 -2018-01-03 17:00:00,1.203,1.20318,1.20244,1.2027,832 -2018-01-03 18:00:00,1.2027,1.20294,1.2022,1.20275,680 -2018-01-03 19:00:00,1.20274,1.20301,1.2001,1.20161,3330 -2018-01-03 20:00:00,1.20162,1.20288,1.20103,1.20124,1500 -2018-01-03 21:00:00,1.2012,1.20158,1.20102,1.20144,859 -2018-01-03 22:00:00,1.20144,1.20162,1.20106,1.20114,898 -2018-01-03 23:00:00,1.20114,1.2014,1.20064,1.20111,880 -2018-01-04 00:00:00,1.20112,1.20115,1.20042,1.20101,985 -2018-01-04 01:00:00,1.20098,1.20114,1.20048,1.20075,803 -2018-01-04 02:00:00,1.20075,1.20192,1.20075,1.20177,893 -2018-01-04 03:00:00,1.20174,1.20178,1.20124,1.20145,451 -2018-01-04 04:00:00,1.20149,1.20224,1.20146,1.2018,425 -2018-01-04 05:00:00,1.20178,1.20231,1.20144,1.20192,394 -2018-01-04 06:00:00,1.20192,1.20382,1.2017,1.20282,1388 -2018-01-04 07:00:00,1.20281,1.2038,1.20254,1.20285,1810 -2018-01-04 08:00:00,1.2028,1.20354,1.20216,1.20258,1564 -2018-01-04 09:00:00,1.20256,1.20462,1.20251,1.2043,1663 -2018-01-04 10:00:00,1.2043,1.20556,1.20415,1.20513,1899 -2018-01-04 11:00:00,1.20514,1.2066,1.20467,1.20624,2061 -2018-01-04 12:00:00,1.20619,1.20751,1.2059,1.20706,1518 -2018-01-04 13:00:00,1.20703,1.2075,1.20552,1.2062,3877 -2018-01-04 14:00:00,1.20625,1.20863,1.20603,1.20825,3121 -2018-01-04 15:00:00,1.20826,1.2089,1.20716,1.20744,2718 -2018-01-04 16:00:00,1.20749,1.2077,1.20612,1.20632,2754 -2018-01-04 17:00:00,1.20635,1.20784,1.20618,1.20747,1487 -2018-01-04 18:00:00,1.20748,1.20801,1.20611,1.20648,1480 -2018-01-04 19:00:00,1.2065,1.2072,1.2064,1.20716,803 -2018-01-04 20:00:00,1.2072,1.20738,1.20651,1.20688,768 -2018-01-04 21:00:00,1.20684,1.20712,1.20653,1.20683,547 -2018-01-04 22:00:00,1.20664,1.20734,1.20635,1.2072,750 -2018-01-04 23:00:00,1.2072,1.20728,1.20667,1.20667,589 -2018-01-05 00:00:00,1.20661,1.20797,1.20651,1.20772,1192 -2018-01-05 01:00:00,1.20774,1.20794,1.20698,1.2072,709 -2018-01-05 02:00:00,1.20716,1.20744,1.20682,1.20712,661 -2018-01-05 03:00:00,1.2071,1.20756,1.2071,1.20747,504 -2018-01-05 04:00:00,1.20748,1.20748,1.20704,1.20739,278 -2018-01-05 05:00:00,1.20741,1.20754,1.20696,1.20714,542 -2018-01-05 06:00:00,1.20714,1.20744,1.20564,1.20568,1075 -2018-01-05 07:00:00,1.20574,1.20674,1.20556,1.20578,1722 -2018-01-05 08:00:00,1.20577,1.20626,1.20511,1.20528,1723 -2018-01-05 09:00:00,1.20524,1.20575,1.20416,1.2046,1471 -2018-01-05 10:00:00,1.2046,1.2054,1.20422,1.20502,1483 -2018-01-05 11:00:00,1.20502,1.20554,1.2048,1.20529,836 -2018-01-05 12:00:00,1.20524,1.20541,1.20446,1.20475,976 -2018-01-05 13:00:00,1.2048,1.20834,1.20446,1.20522,7458 -2018-01-05 14:00:00,1.20518,1.20559,1.20252,1.20294,4649 -2018-01-05 15:00:00,1.20294,1.20444,1.20208,1.20364,3545 -2018-01-05 16:00:00,1.20364,1.20436,1.20302,1.20386,2123 -2018-01-05 17:00:00,1.2039,1.2049,1.20361,1.20472,1252 -2018-01-05 18:00:00,1.2047,1.20491,1.20434,1.20456,687 -2018-01-05 19:00:00,1.20462,1.20508,1.2046,1.20475,607 -2018-01-05 20:00:00,1.2047,1.20492,1.20389,1.20417,493 -2018-01-05 21:00:00,1.20421,1.20422,1.20283,1.20297,1153 -2018-01-07 22:00:00,1.20271,1.20366,1.20266,1.20318,506 -2018-01-07 23:00:00,1.20324,1.2039,1.20324,1.20371,909 -2018-01-08 00:00:00,1.20369,1.20449,1.20334,1.20428,465 -2018-01-08 01:00:00,1.20431,1.20522,1.20416,1.20446,1006 -2018-01-08 02:00:00,1.20448,1.20464,1.20309,1.2036,883 -2018-01-08 03:00:00,1.20356,1.20356,1.20271,1.20326,513 -2018-01-08 04:00:00,1.20329,1.20329,1.2023,1.20252,749 -2018-01-08 05:00:00,1.20255,1.20288,1.20122,1.20198,983 -2018-01-08 06:00:00,1.20198,1.2023,1.20126,1.20142,689 -2018-01-08 07:00:00,1.20144,1.20144,1.19928,1.19931,1583 -2018-01-08 08:00:00,1.19928,1.20008,1.19838,1.19906,1726 -2018-01-08 09:00:00,1.19906,1.19938,1.19868,1.19899,1163 -2018-01-08 10:00:00,1.19902,1.20096,1.19896,1.20038,1440 -2018-01-08 11:00:00,1.20041,1.20067,1.19845,1.19858,1134 -2018-01-08 12:00:00,1.19861,1.19905,1.1971,1.19715,1717 -2018-01-08 13:00:00,1.1971,1.19791,1.19684,1.19699,1944 -2018-01-08 14:00:00,1.19703,1.19792,1.19663,1.19673,2027 -2018-01-08 15:00:00,1.19669,1.19774,1.19594,1.19753,2125 -2018-01-08 16:00:00,1.19756,1.19823,1.19702,1.19726,2049 -2018-01-08 17:00:00,1.19724,1.19787,1.19686,1.1977,1181 -2018-01-08 18:00:00,1.19773,1.19774,1.19568,1.19624,1176 -2018-01-08 19:00:00,1.19622,1.19659,1.19558,1.19628,717 -2018-01-08 20:00:00,1.19624,1.19673,1.1961,1.19672,521 -2018-01-08 21:00:00,1.19671,1.19687,1.19638,1.19687,412 -2018-01-08 22:00:00,1.19689,1.19706,1.1966,1.1968,413 -2018-01-08 23:00:00,1.1968,1.1971,1.19663,1.19703,397 -2018-01-09 00:00:00,1.19698,1.19737,1.1965,1.19718,521 -2018-01-09 01:00:00,1.19718,1.19719,1.19581,1.19673,1376 -2018-01-09 02:00:00,1.19674,1.19756,1.19671,1.19728,1535 -2018-01-09 03:00:00,1.19731,1.19752,1.19676,1.19719,536 -2018-01-09 04:00:00,1.19716,1.19724,1.19662,1.19683,371 -2018-01-09 05:00:00,1.1968,1.19716,1.19642,1.19652,482 -2018-01-09 06:00:00,1.19652,1.19652,1.19516,1.19559,905 -2018-01-09 07:00:00,1.19562,1.1971,1.1951,1.19511,2503 -2018-01-09 08:00:00,1.19507,1.19526,1.19326,1.19394,2301 -2018-01-09 09:00:00,1.1939,1.19463,1.1932,1.19386,2148 -2018-01-09 10:00:00,1.19386,1.19396,1.19252,1.19279,1781 -2018-01-09 11:00:00,1.19276,1.193,1.1921,1.19281,1147 -2018-01-09 12:00:00,1.19284,1.19357,1.19252,1.19334,1237 -2018-01-09 13:00:00,1.1933,1.19338,1.19159,1.19208,2082 -2018-01-09 14:00:00,1.19208,1.1933,1.19174,1.19182,2382 -2018-01-09 15:00:00,1.19181,1.19338,1.19178,1.19297,2605 -2018-01-09 16:00:00,1.19299,1.19314,1.1918,1.1921,2108 -2018-01-09 17:00:00,1.19213,1.19259,1.19182,1.19214,1216 -2018-01-09 18:00:00,1.19218,1.19314,1.19166,1.19304,821 -2018-01-09 19:00:00,1.19304,1.19358,1.19248,1.19318,849 -2018-01-09 20:00:00,1.1932,1.19386,1.19299,1.19379,618 -2018-01-09 21:00:00,1.19376,1.19394,1.19358,1.19369,348 -2018-01-09 22:00:00,1.19369,1.19388,1.19351,1.1936,404 -2018-01-09 23:00:00,1.19357,1.19364,1.19278,1.19284,465 -2018-01-10 00:00:00,1.19288,1.19386,1.19284,1.19377,847 -2018-01-10 01:00:00,1.19372,1.19452,1.1933,1.1945,1725 -2018-01-10 02:00:00,1.19446,1.19491,1.19406,1.19486,924 -2018-01-10 03:00:00,1.19482,1.19496,1.19414,1.19418,348 -2018-01-10 04:00:00,1.1942,1.19428,1.19357,1.1936,408 -2018-01-10 05:00:00,1.19365,1.19417,1.19272,1.19281,753 -2018-01-10 06:00:00,1.19281,1.19344,1.19235,1.1929,1396 -2018-01-10 07:00:00,1.19289,1.19452,1.19278,1.1935,3130 -2018-01-10 08:00:00,1.19354,1.1955,1.19341,1.19464,2258 -2018-01-10 09:00:00,1.19468,1.19496,1.19382,1.19389,1946 -2018-01-10 10:00:00,1.1939,1.20006,1.19317,1.19948,6932 -2018-01-10 11:00:00,1.19952,1.20166,1.19872,1.20056,5439 -2018-01-10 12:00:00,1.20056,1.20182,1.19957,1.19979,3564 -2018-01-10 13:00:00,1.19982,1.2003,1.19901,1.19948,3156 -2018-01-10 14:00:00,1.19953,1.2007,1.19733,1.19862,4003 -2018-01-10 15:00:00,1.19862,1.19965,1.19771,1.1983,3308 -2018-01-10 16:00:00,1.1983,1.1984,1.19556,1.19578,3512 -2018-01-10 17:00:00,1.19579,1.19652,1.1951,1.19606,2003 -2018-01-10 18:00:00,1.19607,1.19679,1.19558,1.1959,1487 -2018-01-10 19:00:00,1.19588,1.19596,1.194,1.19578,3016 -2018-01-10 20:00:00,1.19576,1.19653,1.19546,1.1957,2007 -2018-01-10 21:00:00,1.19574,1.19586,1.19472,1.19474,690 -2018-01-10 22:00:00,1.19479,1.19532,1.19461,1.19494,580 -2018-01-10 23:00:00,1.19494,1.19592,1.19492,1.19562,402 -2018-01-11 00:00:00,1.19561,1.19604,1.19474,1.19604,1545 -2018-01-11 01:00:00,1.19604,1.19629,1.19542,1.19597,1556 -2018-01-11 02:00:00,1.19595,1.19692,1.19566,1.19668,814 -2018-01-11 03:00:00,1.19665,1.19706,1.19453,1.19536,2059 -2018-01-11 04:00:00,1.19534,1.19548,1.19414,1.1947,1169 -2018-01-11 05:00:00,1.1947,1.19541,1.19412,1.19521,1048 -2018-01-11 06:00:00,1.19521,1.19521,1.19365,1.19424,1048 -2018-01-11 07:00:00,1.19424,1.19499,1.19297,1.194,2273 -2018-01-11 08:00:00,1.19398,1.19418,1.19295,1.19378,2339 -2018-01-11 09:00:00,1.19377,1.19495,1.19331,1.19477,2210 -2018-01-11 10:00:00,1.19478,1.19518,1.1939,1.19466,1864 -2018-01-11 11:00:00,1.1947,1.19508,1.19406,1.19435,1468 -2018-01-11 12:00:00,1.19437,1.2013,1.19364,1.20044,9176 -2018-01-11 13:00:00,1.20048,1.20353,1.20026,1.20314,9406 -2018-01-11 14:00:00,1.20312,1.20489,1.2031,1.2048,4285 -2018-01-11 15:00:00,1.2048,1.20592,1.20394,1.20492,4332 -2018-01-11 16:00:00,1.20496,1.20496,1.2032,1.20343,2620 -2018-01-11 17:00:00,1.20342,1.2041,1.20313,1.20378,1605 -2018-01-11 18:00:00,1.20384,1.20476,1.20304,1.2037,1974 -2018-01-11 19:00:00,1.20368,1.20456,1.2034,1.20387,1036 -2018-01-11 20:00:00,1.20382,1.20398,1.20276,1.20311,796 -2018-01-11 21:00:00,1.2031,1.2035,1.20282,1.2032,811 -2018-01-11 22:00:00,1.20332,1.20408,1.20315,1.20386,854 -2018-01-11 23:00:00,1.20384,1.2044,1.20308,1.20431,918 -2018-01-12 00:00:00,1.20436,1.20669,1.20417,1.20586,2966 -2018-01-12 01:00:00,1.20584,1.20616,1.20432,1.20455,1378 -2018-01-12 02:00:00,1.20452,1.20508,1.2042,1.20471,844 -2018-01-12 03:00:00,1.20473,1.20532,1.20458,1.20516,680 -2018-01-12 04:00:00,1.20512,1.2055,1.20458,1.20536,669 -2018-01-12 05:00:00,1.2054,1.20573,1.20403,1.20444,685 -2018-01-12 06:00:00,1.20442,1.20526,1.20424,1.20482,934 -2018-01-12 07:00:00,1.20477,1.2076,1.20454,1.20626,3649 -2018-01-12 08:00:00,1.20628,1.21208,1.2052,1.21114,6783 -2018-01-12 09:00:00,1.21115,1.21368,1.21109,1.21253,5139 -2018-01-12 10:00:00,1.21258,1.21293,1.21148,1.21187,2153 -2018-01-12 11:00:00,1.21188,1.21358,1.21188,1.21246,2167 -2018-01-12 12:00:00,1.21251,1.21382,1.21228,1.21331,2179 -2018-01-12 13:00:00,1.21332,1.21493,1.2112,1.21202,9629 -2018-01-12 14:00:00,1.21203,1.21492,1.21112,1.21382,5906 -2018-01-12 15:00:00,1.21382,1.21553,1.2133,1.21482,4987 -2018-01-12 16:00:00,1.21482,1.21557,1.2122,1.21302,5546 -2018-01-12 17:00:00,1.21305,1.21371,1.21242,1.21344,2483 -2018-01-12 18:00:00,1.21346,1.21668,1.2133,1.21627,3430 -2018-01-12 19:00:00,1.21624,1.21846,1.21608,1.21809,3402 -2018-01-12 20:00:00,1.21812,1.21884,1.21768,1.21872,1389 -2018-01-12 21:00:00,1.21878,1.22193,1.2187,1.21968,3851 -2018-01-14 22:00:00,1.21935,1.22089,1.21931,1.22036,1308 -2018-01-14 23:00:00,1.22034,1.22124,1.21909,1.21919,1835 -2018-01-15 00:00:00,1.21918,1.21988,1.21878,1.21909,2576 -2018-01-15 01:00:00,1.21906,1.22088,1.21892,1.21986,3016 -2018-01-15 02:00:00,1.21986,1.22082,1.21924,1.21947,2009 -2018-01-15 03:00:00,1.21942,1.22046,1.2193,1.22001,1561 -2018-01-15 04:00:00,1.21997,1.22113,1.21962,1.22102,1346 -2018-01-15 05:00:00,1.221,1.224,1.2208,1.22228,4610 -2018-01-15 06:00:00,1.22228,1.22301,1.22076,1.22087,3372 -2018-01-15 07:00:00,1.22086,1.22202,1.22012,1.22117,3001 -2018-01-15 08:00:00,1.22114,1.22348,1.22096,1.22309,2685 -2018-01-15 09:00:00,1.22308,1.22698,1.22288,1.22604,3836 -2018-01-15 10:00:00,1.226,1.22968,1.22576,1.22744,4236 -2018-01-15 11:00:00,1.22743,1.22824,1.22522,1.22554,2561 -2018-01-15 12:00:00,1.22554,1.22725,1.22513,1.22696,1797 -2018-01-15 13:00:00,1.22701,1.22865,1.22654,1.2283,2509 -2018-01-15 14:00:00,1.2283,1.22912,1.22598,1.2262,2560 -2018-01-15 15:00:00,1.22618,1.22714,1.22546,1.22598,2237 -2018-01-15 16:00:00,1.22598,1.22938,1.22592,1.2266,4140 -2018-01-15 17:00:00,1.22664,1.22878,1.22664,1.22719,1097 -2018-01-15 18:00:00,1.22725,1.22769,1.2268,1.22728,960 -2018-01-15 19:00:00,1.22726,1.22746,1.22633,1.22688,1299 -2018-01-15 20:00:00,1.22694,1.22784,1.22633,1.22694,2467 -2018-01-15 21:00:00,1.22693,1.22699,1.22632,1.22636,1104 -2018-01-15 22:00:00,1.22655,1.22678,1.22622,1.2265,423 -2018-01-15 23:00:00,1.22656,1.22753,1.22615,1.22668,1185 -2018-01-16 00:00:00,1.2267,1.22698,1.22604,1.2262,1375 -2018-01-16 01:00:00,1.22622,1.22659,1.22477,1.22655,1908 -2018-01-16 02:00:00,1.22651,1.22798,1.22588,1.22678,2016 -2018-01-16 03:00:00,1.22672,1.22696,1.22555,1.22573,1179 -2018-01-16 04:00:00,1.22574,1.22705,1.22574,1.2267,1051 -2018-01-16 05:00:00,1.22668,1.227,1.22616,1.2263,768 -2018-01-16 06:00:00,1.2263,1.22832,1.22581,1.22674,2357 -2018-01-16 07:00:00,1.22674,1.22682,1.22156,1.22466,10486 -2018-01-16 08:00:00,1.22465,1.22678,1.22227,1.2236,4599 -2018-01-16 09:00:00,1.22356,1.2241,1.22222,1.22332,3188 -2018-01-16 10:00:00,1.22334,1.22389,1.22018,1.22132,5283 -2018-01-16 11:00:00,1.22137,1.2224,1.22048,1.22158,1978 -2018-01-16 12:00:00,1.22156,1.22406,1.22146,1.22324,2043 -2018-01-16 13:00:00,1.22322,1.22357,1.22123,1.2218,2566 -2018-01-16 14:00:00,1.22182,1.22184,1.21952,1.22092,4724 -2018-01-16 15:00:00,1.2209,1.22344,1.2207,1.22296,3636 -2018-01-16 16:00:00,1.22296,1.22486,1.2225,1.22446,2873 -2018-01-16 17:00:00,1.22443,1.22456,1.22335,1.22437,2068 -2018-01-16 18:00:00,1.22441,1.22695,1.22432,1.22674,1976 -2018-01-16 19:00:00,1.22674,1.2281,1.22634,1.22716,2354 -2018-01-16 20:00:00,1.22716,1.22744,1.22649,1.22664,1327 -2018-01-16 21:00:00,1.2266,1.22665,1.22544,1.22607,720 -2018-01-16 22:00:00,1.22591,1.22642,1.2254,1.22562,1113 -2018-01-16 23:00:00,1.22564,1.22774,1.22564,1.22708,1207 -2018-01-17 00:00:00,1.22705,1.2323,1.22638,1.23034,6019 -2018-01-17 01:00:00,1.2304,1.2306,1.22852,1.22911,4049 -2018-01-17 02:00:00,1.22907,1.22972,1.22674,1.22684,2513 -2018-01-17 03:00:00,1.22688,1.22755,1.2259,1.22672,2314 -2018-01-17 04:00:00,1.22672,1.22702,1.22486,1.22494,2208 -2018-01-17 05:00:00,1.22496,1.22542,1.2237,1.22439,2581 -2018-01-17 06:00:00,1.22439,1.22514,1.22148,1.22201,3325 -2018-01-17 07:00:00,1.22203,1.22353,1.22084,1.22172,5452 -2018-01-17 08:00:00,1.22174,1.22442,1.22112,1.22268,5240 -2018-01-17 09:00:00,1.22264,1.22439,1.22166,1.22366,3126 -2018-01-17 10:00:00,1.22372,1.22503,1.22324,1.22344,2907 -2018-01-17 11:00:00,1.22343,1.2237,1.22055,1.2207,2521 -2018-01-17 12:00:00,1.22069,1.22144,1.2201,1.22095,2195 -2018-01-17 13:00:00,1.22096,1.22232,1.21964,1.22194,3596 -2018-01-17 14:00:00,1.2219,1.22298,1.22128,1.22216,3855 -2018-01-17 15:00:00,1.22216,1.22456,1.22161,1.22428,4933 -2018-01-17 16:00:00,1.22427,1.22447,1.22256,1.22288,3177 -2018-01-17 17:00:00,1.22285,1.22536,1.22272,1.2252,2059 -2018-01-17 18:00:00,1.22518,1.2288,1.22501,1.22768,3954 -2018-01-17 19:00:00,1.22766,1.22766,1.22357,1.22376,3769 -2018-01-17 20:00:00,1.22371,1.22385,1.22089,1.22131,4593 -2018-01-17 21:00:00,1.22133,1.2218,1.21776,1.21854,3194 -2018-01-17 22:00:00,1.21872,1.21922,1.21656,1.21656,2343 -2018-01-17 23:00:00,1.21653,1.21883,1.21653,1.21803,1293 -2018-01-18 00:00:00,1.21809,1.22046,1.2179,1.21901,4246 -2018-01-18 01:00:00,1.21906,1.21974,1.218,1.2193,2496 -2018-01-18 02:00:00,1.21925,1.22016,1.21908,1.21943,2011 -2018-01-18 03:00:00,1.21942,1.21949,1.21735,1.21798,1840 -2018-01-18 04:00:00,1.21794,1.21968,1.21788,1.21948,1616 -2018-01-18 05:00:00,1.21954,1.2209,1.21942,1.2207,2315 -2018-01-18 06:00:00,1.2207,1.22097,1.21962,1.2207,2156 -2018-01-18 07:00:00,1.22076,1.22124,1.21864,1.22064,3502 -2018-01-18 08:00:00,1.22064,1.22178,1.2202,1.2204,2946 -2018-01-18 09:00:00,1.2204,1.2218,1.21961,1.22144,2226 -2018-01-18 10:00:00,1.22146,1.22295,1.22126,1.22279,2055 -2018-01-18 11:00:00,1.2228,1.22472,1.22274,1.224,2420 -2018-01-18 12:00:00,1.22397,1.22528,1.22339,1.22394,2502 -2018-01-18 13:00:00,1.22394,1.22503,1.2227,1.22489,2964 -2018-01-18 14:00:00,1.2249,1.2265,1.22419,1.22606,3310 -2018-01-18 15:00:00,1.22607,1.22607,1.22308,1.22392,4079 -2018-01-18 16:00:00,1.2239,1.22546,1.22269,1.22382,5483 -2018-01-18 17:00:00,1.22386,1.22556,1.22208,1.22283,3083 -2018-01-18 18:00:00,1.22283,1.22359,1.22199,1.2226,2458 -2018-01-18 19:00:00,1.22266,1.22448,1.22248,1.22434,1672 -2018-01-18 20:00:00,1.22434,1.22475,1.22264,1.22386,2202 -2018-01-18 21:00:00,1.22386,1.22436,1.22368,1.2239,1060 -2018-01-18 22:00:00,1.2237,1.22444,1.22334,1.22409,885 -2018-01-18 23:00:00,1.22412,1.22466,1.22322,1.2234,1274 -2018-01-19 00:00:00,1.2234,1.22542,1.22324,1.22368,3295 -2018-01-19 01:00:00,1.22366,1.22457,1.2232,1.22436,2560 -2018-01-19 02:00:00,1.22442,1.22564,1.22404,1.22448,2669 -2018-01-19 03:00:00,1.22454,1.22704,1.22436,1.22667,2546 -2018-01-19 04:00:00,1.22666,1.2267,1.22596,1.22625,1310 -2018-01-19 05:00:00,1.2263,1.22638,1.22536,1.2261,929 -2018-01-19 06:00:00,1.2261,1.22684,1.22576,1.22593,1916 -2018-01-19 07:00:00,1.22588,1.22796,1.22514,1.22718,3556 -2018-01-19 08:00:00,1.22713,1.22852,1.22624,1.22832,3888 -2018-01-19 09:00:00,1.22831,1.22954,1.22649,1.22816,3843 -2018-01-19 10:00:00,1.22815,1.22842,1.22666,1.22742,2912 -2018-01-19 11:00:00,1.22744,1.22774,1.22561,1.22731,2346 -2018-01-19 12:00:00,1.22726,1.22726,1.22532,1.22572,2070 -2018-01-19 13:00:00,1.22578,1.22696,1.22392,1.22435,6699 -2018-01-19 14:00:00,1.22431,1.22529,1.22304,1.22503,4743 -2018-01-19 15:00:00,1.22503,1.22576,1.22183,1.22208,5010 -2018-01-19 16:00:00,1.22211,1.22392,1.22206,1.22372,2674 -2018-01-19 17:00:00,1.22372,1.22436,1.22311,1.22328,1890 -2018-01-19 18:00:00,1.22328,1.22328,1.22191,1.22324,1563 -2018-01-19 19:00:00,1.22326,1.22386,1.22316,1.22328,1412 -2018-01-19 20:00:00,1.22328,1.22347,1.22204,1.22212,1174 -2018-01-19 21:00:00,1.2221,1.22338,1.22152,1.22211,2661 -2018-01-21 22:00:00,1.22716,1.22743,1.22552,1.22591,1121 -2018-01-21 23:00:00,1.22594,1.22602,1.22342,1.22562,2248 -2018-01-22 00:00:00,1.22562,1.22574,1.22413,1.22442,2370 -2018-01-22 01:00:00,1.2244,1.22448,1.22253,1.2229,3227 -2018-01-22 02:00:00,1.22287,1.22377,1.22265,1.22366,1885 -2018-01-22 03:00:00,1.22362,1.22376,1.22248,1.2229,1073 -2018-01-22 04:00:00,1.22288,1.223,1.22165,1.2224,1641 -2018-01-22 05:00:00,1.22237,1.2233,1.22174,1.22319,1445 -2018-01-22 06:00:00,1.22316,1.22342,1.22141,1.22161,2125 -2018-01-22 07:00:00,1.22162,1.22427,1.22156,1.22374,3147 -2018-01-22 08:00:00,1.2238,1.225,1.22355,1.22418,2631 -2018-01-22 09:00:00,1.22422,1.2256,1.2242,1.22495,1695 -2018-01-22 10:00:00,1.22498,1.22671,1.22478,1.22621,1932 -2018-01-22 11:00:00,1.22624,1.2263,1.22513,1.22552,1431 -2018-01-22 12:00:00,1.2255,1.22567,1.2239,1.22414,1314 -2018-01-22 13:00:00,1.22414,1.22519,1.22336,1.22494,1691 -2018-01-22 14:00:00,1.22498,1.22587,1.22384,1.22402,2521 -2018-01-22 15:00:00,1.22404,1.22608,1.22386,1.22537,2677 -2018-01-22 16:00:00,1.22535,1.22549,1.2228,1.2228,2934 -2018-01-22 17:00:00,1.22281,1.22448,1.2224,1.22438,2860 -2018-01-22 18:00:00,1.22438,1.2251,1.22392,1.22494,1295 -2018-01-22 19:00:00,1.22498,1.22614,1.22478,1.22584,1325 -2018-01-22 20:00:00,1.22586,1.22606,1.22546,1.22588,1002 -2018-01-22 21:00:00,1.22588,1.2263,1.2257,1.22614,564 -2018-01-22 22:00:00,1.22614,1.22648,1.22571,1.226,967 -2018-01-22 23:00:00,1.22598,1.22603,1.22555,1.22564,1299 -2018-01-23 00:00:00,1.22562,1.22732,1.22556,1.22674,1313 -2018-01-23 01:00:00,1.22672,1.22756,1.22626,1.22664,1515 -2018-01-23 02:00:00,1.22662,1.22674,1.22512,1.22615,1250 -2018-01-23 03:00:00,1.22611,1.22759,1.22548,1.22578,4124 -2018-01-23 04:00:00,1.22573,1.22651,1.22551,1.22596,1189 -2018-01-23 05:00:00,1.22598,1.22608,1.22515,1.22581,1066 -2018-01-23 06:00:00,1.22581,1.2271,1.22443,1.22482,3058 -2018-01-23 07:00:00,1.2248,1.22565,1.22384,1.22512,3427 -2018-01-23 08:00:00,1.22514,1.2253,1.2223,1.22386,3903 -2018-01-23 09:00:00,1.22382,1.22456,1.22312,1.22376,2345 -2018-01-23 10:00:00,1.22374,1.22546,1.22374,1.22465,2376 -2018-01-23 11:00:00,1.22468,1.22576,1.22364,1.22364,2334 -2018-01-23 12:00:00,1.22366,1.22538,1.22338,1.22494,2294 -2018-01-23 13:00:00,1.22496,1.22651,1.22458,1.22586,2634 -2018-01-23 14:00:00,1.2259,1.22833,1.22516,1.22784,3708 -2018-01-23 15:00:00,1.22786,1.23062,1.22768,1.2293,5201 -2018-01-23 16:00:00,1.22929,1.22947,1.22706,1.22763,3521 -2018-01-23 17:00:00,1.22758,1.22902,1.22753,1.2279,2019 -2018-01-23 18:00:00,1.22791,1.22896,1.2276,1.22808,1890 -2018-01-23 19:00:00,1.22806,1.22956,1.228,1.22956,1611 -2018-01-23 20:00:00,1.22955,1.2297,1.22883,1.22938,825 -2018-01-23 21:00:00,1.22934,1.22998,1.22928,1.2299,746 -2018-01-23 22:00:00,1.23004,1.23004,1.22959,1.22974,305 -2018-01-23 23:00:00,1.22968,1.23158,1.2294,1.23092,1693 -2018-01-24 00:00:00,1.23092,1.2313,1.22914,1.23003,2169 -2018-01-24 01:00:00,1.22997,1.23121,1.22932,1.2307,2212 -2018-01-24 02:00:00,1.2307,1.23184,1.23016,1.231,3715 -2018-01-24 03:00:00,1.23098,1.23164,1.23015,1.23143,1687 -2018-01-24 04:00:00,1.23146,1.23356,1.23146,1.23214,2807 -2018-01-24 05:00:00,1.23212,1.23255,1.2314,1.23249,1368 -2018-01-24 06:00:00,1.23246,1.23291,1.23067,1.23092,3173 -2018-01-24 07:00:00,1.23092,1.23198,1.23026,1.23124,3455 -2018-01-24 08:00:00,1.23125,1.23449,1.23114,1.23404,5805 -2018-01-24 09:00:00,1.23404,1.23563,1.23367,1.23369,5641 -2018-01-24 10:00:00,1.23368,1.23482,1.23341,1.23374,3304 -2018-01-24 11:00:00,1.23374,1.2349,1.23296,1.234,3164 -2018-01-24 12:00:00,1.23401,1.23458,1.23305,1.23384,2801 -2018-01-24 13:00:00,1.23384,1.23679,1.23384,1.23658,7281 -2018-01-24 14:00:00,1.23654,1.23966,1.2363,1.23925,5598 -2018-01-24 15:00:00,1.23927,1.24022,1.23802,1.23808,5367 -2018-01-24 16:00:00,1.23814,1.23972,1.23766,1.23897,4256 -2018-01-24 17:00:00,1.23893,1.23963,1.23824,1.23915,2432 -2018-01-24 18:00:00,1.23917,1.24149,1.23902,1.24126,3465 -2018-01-24 19:00:00,1.24122,1.24154,1.23978,1.24048,2544 -2018-01-24 20:00:00,1.24047,1.24062,1.23946,1.2399,1624 -2018-01-24 21:00:00,1.2399,1.24101,1.23978,1.2408,1573 -2018-01-24 22:00:00,1.24104,1.24109,1.24006,1.2405,1216 -2018-01-24 23:00:00,1.24048,1.24049,1.23902,1.2393,1043 -2018-01-25 00:00:00,1.23926,1.24002,1.23845,1.23985,2900 -2018-01-25 01:00:00,1.23986,1.2411,1.23894,1.24104,2965 -2018-01-25 02:00:00,1.24102,1.24282,1.24056,1.24231,4617 -2018-01-25 03:00:00,1.2423,1.24401,1.24202,1.24314,5198 -2018-01-25 04:00:00,1.24312,1.24392,1.24258,1.24364,2532 -2018-01-25 05:00:00,1.24362,1.24487,1.2426,1.2448,2441 -2018-01-25 06:00:00,1.2448,1.24596,1.24228,1.24357,5894 -2018-01-25 07:00:00,1.24352,1.24422,1.2409,1.24194,12088 -2018-01-25 08:00:00,1.24191,1.24195,1.2389,1.23968,7607 -2018-01-25 09:00:00,1.2397,1.24332,1.2397,1.24318,4369 -2018-01-25 10:00:00,1.24316,1.24324,1.2408,1.24134,3774 -2018-01-25 11:00:00,1.24133,1.24212,1.23987,1.24034,2468 -2018-01-25 12:00:00,1.2403,1.24159,1.23972,1.24044,3963 -2018-01-25 13:00:00,1.24045,1.24984,1.24022,1.24972,24445 -2018-01-25 14:00:00,1.24973,1.25374,1.24623,1.24899,21503 -2018-01-25 15:00:00,1.24898,1.25301,1.2484,1.25039,10393 -2018-01-25 16:00:00,1.25041,1.25069,1.24838,1.24871,4975 -2018-01-25 17:00:00,1.24866,1.24922,1.24774,1.24922,3503 -2018-01-25 18:00:00,1.24923,1.25065,1.24734,1.24844,5107 -2018-01-25 19:00:00,1.24846,1.24875,1.23642,1.23904,31054 -2018-01-25 20:00:00,1.23905,1.24312,1.23884,1.24065,9978 -2018-01-25 21:00:00,1.2407,1.2423,1.23874,1.2398,3213 -2018-01-25 22:00:00,1.2394,1.24014,1.23699,1.2373,1307 -2018-01-25 23:00:00,1.23718,1.23959,1.23716,1.23912,2730 -2018-01-26 00:00:00,1.23914,1.24108,1.2386,1.2406,3564 -2018-01-26 01:00:00,1.24058,1.24332,1.24033,1.24306,4653 -2018-01-26 02:00:00,1.24304,1.24304,1.24123,1.24272,4517 -2018-01-26 03:00:00,1.24272,1.24318,1.24224,1.24294,2188 -2018-01-26 04:00:00,1.24294,1.24315,1.24204,1.24213,999 -2018-01-26 05:00:00,1.24212,1.24326,1.24131,1.24313,1688 -2018-01-26 06:00:00,1.24312,1.24526,1.24284,1.24508,4061 -2018-01-26 07:00:00,1.24508,1.2494,1.24477,1.24745,7990 -2018-01-26 08:00:00,1.2475,1.24908,1.2452,1.24668,6098 -2018-01-26 09:00:00,1.2467,1.24678,1.2452,1.24556,4570 -2018-01-26 10:00:00,1.24558,1.24671,1.24423,1.2459,4104 -2018-01-26 11:00:00,1.24594,1.24652,1.24298,1.24386,4397 -2018-01-26 12:00:00,1.24382,1.24502,1.24344,1.24408,4107 -2018-01-26 13:00:00,1.24408,1.24576,1.24207,1.24286,7873 -2018-01-26 14:00:00,1.24287,1.24478,1.24127,1.24412,9288 -2018-01-26 15:00:00,1.24416,1.24458,1.24155,1.2433,6780 -2018-01-26 16:00:00,1.2433,1.24374,1.24077,1.24216,6574 -2018-01-26 17:00:00,1.24216,1.2442,1.2416,1.24388,4712 -2018-01-26 18:00:00,1.24387,1.24505,1.24334,1.24446,2989 -2018-01-26 19:00:00,1.24447,1.2448,1.24176,1.24208,7796 -2018-01-26 20:00:00,1.24207,1.24235,1.24059,1.24196,2627 -2018-01-26 21:00:00,1.24196,1.24321,1.24174,1.24296,2200 -2018-01-28 22:00:00,1.2428,1.2428,1.24134,1.24164,755 -2018-01-28 23:00:00,1.24164,1.24311,1.24161,1.2431,1552 -2018-01-29 00:00:00,1.24304,1.24324,1.24207,1.2421,2431 -2018-01-29 01:00:00,1.24212,1.2422,1.23956,1.23968,4632 -2018-01-29 02:00:00,1.23967,1.24014,1.23852,1.23997,3975 -2018-01-29 03:00:00,1.23996,1.24195,1.23982,1.24152,3504 -2018-01-29 04:00:00,1.24156,1.24221,1.24117,1.2413,1067 -2018-01-29 05:00:00,1.24135,1.24191,1.24054,1.24142,2235 -2018-01-29 06:00:00,1.24142,1.2427,1.24046,1.24158,3341 -2018-01-29 07:00:00,1.24158,1.24292,1.23944,1.24018,5236 -2018-01-29 08:00:00,1.2402,1.24096,1.23884,1.24071,4379 -2018-01-29 09:00:00,1.24073,1.24166,1.23942,1.24119,3991 -2018-01-29 10:00:00,1.24124,1.2428,1.24037,1.24037,3256 -2018-01-29 11:00:00,1.24032,1.24044,1.23912,1.23934,2338 -2018-01-29 12:00:00,1.2393,1.24043,1.23772,1.23846,2968 -2018-01-29 13:00:00,1.23842,1.23893,1.2359,1.23647,4045 -2018-01-29 14:00:00,1.23648,1.23714,1.23452,1.23517,4145 -2018-01-29 15:00:00,1.23518,1.23742,1.23498,1.23563,4324 -2018-01-29 16:00:00,1.23563,1.2368,1.2337,1.23522,7734 -2018-01-29 17:00:00,1.23523,1.2373,1.23448,1.23718,3241 -2018-01-29 18:00:00,1.23719,1.23802,1.2369,1.23781,2005 -2018-01-29 19:00:00,1.2378,1.23902,1.23734,1.23888,2067 -2018-01-29 20:00:00,1.23888,1.23899,1.2381,1.23825,1450 -2018-01-29 21:00:00,1.2382,1.23838,1.2378,1.23827,620 -2018-01-29 22:00:00,1.2381,1.23861,1.23778,1.23823,1043 -2018-01-29 23:00:00,1.23826,1.23866,1.23784,1.23808,1004 -2018-01-30 00:00:00,1.23809,1.23863,1.23684,1.23763,2660 -2018-01-30 01:00:00,1.23766,1.23884,1.23729,1.2385,2669 -2018-01-30 02:00:00,1.2385,1.2385,1.23601,1.23694,3793 -2018-01-30 03:00:00,1.23698,1.23837,1.23664,1.23785,2606 -2018-01-30 04:00:00,1.23784,1.23866,1.2371,1.23717,3131 -2018-01-30 05:00:00,1.23718,1.23763,1.23601,1.2364,2048 -2018-01-30 06:00:00,1.23635,1.23656,1.2347,1.23484,2557 -2018-01-30 07:00:00,1.23481,1.23705,1.2348,1.23555,3429 -2018-01-30 08:00:00,1.23554,1.23848,1.23349,1.23824,5082 -2018-01-30 09:00:00,1.23822,1.24076,1.23772,1.23986,6087 -2018-01-30 10:00:00,1.23988,1.24242,1.23947,1.24126,4784 -2018-01-30 11:00:00,1.24126,1.24414,1.24087,1.24396,3446 -2018-01-30 12:00:00,1.2439,1.24395,1.24178,1.24264,3480 -2018-01-30 13:00:00,1.2427,1.24482,1.24034,1.24454,4536 -2018-01-30 14:00:00,1.24454,1.24543,1.24312,1.24418,5943 -2018-01-30 15:00:00,1.2442,1.2443,1.2403,1.24103,6573 -2018-01-30 16:00:00,1.24102,1.24205,1.23838,1.23907,5325 -2018-01-30 17:00:00,1.23908,1.24079,1.2386,1.24052,2888 -2018-01-30 18:00:00,1.24056,1.24066,1.2384,1.23956,2694 -2018-01-30 19:00:00,1.2396,1.24058,1.23894,1.24056,2370 -2018-01-30 20:00:00,1.24056,1.24062,1.23939,1.23942,1114 -2018-01-30 21:00:00,1.2394,1.24036,1.2394,1.24024,594 -2018-01-30 22:00:00,1.24028,1.24058,1.2401,1.24052,739 -2018-01-30 23:00:00,1.24046,1.24135,1.23962,1.24085,1263 -2018-01-31 00:00:00,1.24082,1.24248,1.24066,1.24177,3571 -2018-01-31 01:00:00,1.24176,1.24208,1.24019,1.24147,4426 -2018-01-31 02:00:00,1.24146,1.24152,1.23988,1.2414,4356 -2018-01-31 03:00:00,1.24142,1.24338,1.2414,1.24236,4803 -2018-01-31 04:00:00,1.24238,1.24279,1.24152,1.24196,3012 -2018-01-31 05:00:00,1.24198,1.2438,1.24178,1.24372,2586 -2018-01-31 06:00:00,1.24372,1.24504,1.24334,1.24494,3378 -2018-01-31 07:00:00,1.24488,1.24628,1.24347,1.24444,5822 -2018-01-31 08:00:00,1.24444,1.2451,1.24251,1.24376,4251 -2018-01-31 09:00:00,1.24373,1.24561,1.24332,1.24512,4786 -2018-01-31 10:00:00,1.24512,1.24601,1.24394,1.24442,4322 -2018-01-31 11:00:00,1.24442,1.24561,1.24412,1.24546,2263 -2018-01-31 12:00:00,1.24544,1.24602,1.24458,1.24595,2336 -2018-01-31 13:00:00,1.24598,1.24728,1.24482,1.2465,5219 -2018-01-31 14:00:00,1.2465,1.2466,1.2445,1.24586,3988 -2018-01-31 15:00:00,1.24586,1.24748,1.24528,1.24564,5840 -2018-01-31 16:00:00,1.2457,1.24634,1.2424,1.24272,5895 -2018-01-31 17:00:00,1.24276,1.2437,1.24068,1.2415,3282 -2018-01-31 18:00:00,1.24154,1.24232,1.24089,1.24183,3171 -2018-01-31 19:00:00,1.24187,1.24384,1.2387,1.24112,17390 -2018-01-31 20:00:00,1.24112,1.2424,1.2402,1.2415,5015 -2018-01-31 21:00:00,1.2415,1.24176,1.24096,1.24138,882 -2018-01-31 22:00:00,1.24098,1.24148,1.24046,1.24122,1411 -2018-01-31 23:00:00,1.24128,1.24226,1.24122,1.24166,876 -2018-02-01 00:00:00,1.24169,1.24289,1.24165,1.2421,1831 -2018-02-01 01:00:00,1.2421,1.24266,1.24056,1.24192,2936 -2018-02-01 02:00:00,1.2419,1.2428,1.2415,1.24175,1625 -2018-02-01 03:00:00,1.24176,1.2426,1.24145,1.24246,1265 -2018-02-01 04:00:00,1.24246,1.24286,1.2417,1.24218,1063 -2018-02-01 05:00:00,1.24216,1.24282,1.24186,1.24211,1094 -2018-02-01 06:00:00,1.24208,1.24224,1.23934,1.23938,3482 -2018-02-01 07:00:00,1.23942,1.24046,1.23849,1.24029,5339 -2018-02-01 08:00:00,1.24028,1.24394,1.24021,1.24284,5876 -2018-02-01 09:00:00,1.24279,1.245,1.24278,1.24463,4987 -2018-02-01 10:00:00,1.2446,1.24512,1.24286,1.243,3100 -2018-02-01 11:00:00,1.24302,1.24382,1.24246,1.24379,2997 -2018-02-01 12:00:00,1.24374,1.24602,1.24324,1.24539,4027 -2018-02-01 13:00:00,1.24541,1.24622,1.24444,1.24496,5012 -2018-02-01 14:00:00,1.24495,1.24536,1.2437,1.24425,4274 -2018-02-01 15:00:00,1.24423,1.24745,1.24316,1.24696,7045 -2018-02-01 16:00:00,1.24696,1.2489,1.24624,1.24812,6037 -2018-02-01 17:00:00,1.24812,1.24984,1.24749,1.24784,4718 -2018-02-01 18:00:00,1.24787,1.24954,1.24776,1.24938,2794 -2018-02-01 19:00:00,1.24933,1.25067,1.24836,1.2503,4106 -2018-02-01 20:00:00,1.25031,1.25233,1.25012,1.2515,5909 -2018-02-01 21:00:00,1.25144,1.25182,1.25046,1.25079,1983 -2018-02-01 22:00:00,1.25135,1.25135,1.25028,1.25056,1161 -2018-02-01 23:00:00,1.25057,1.25158,1.25052,1.25106,1294 -2018-02-02 00:00:00,1.25108,1.25126,1.24978,1.25072,1626 -2018-02-02 01:00:00,1.25066,1.25149,1.2492,1.24994,5434 -2018-02-02 02:00:00,1.24995,1.25044,1.2489,1.2494,2742 -2018-02-02 03:00:00,1.24934,1.25006,1.24924,1.25001,1737 -2018-02-02 04:00:00,1.25002,1.25008,1.24919,1.2493,1061 -2018-02-02 05:00:00,1.24932,1.24985,1.24908,1.24955,1042 -2018-02-02 06:00:00,1.24955,1.24982,1.24865,1.24952,2638 -2018-02-02 07:00:00,1.24947,1.25144,1.24942,1.25098,3598 -2018-02-02 08:00:00,1.25096,1.25184,1.2485,1.24936,4891 -2018-02-02 09:00:00,1.24932,1.24955,1.24802,1.24867,3824 -2018-02-02 10:00:00,1.24864,1.24913,1.24759,1.24898,2590 -2018-02-02 11:00:00,1.24894,1.24992,1.24855,1.24902,2462 -2018-02-02 12:00:00,1.249,1.24934,1.24853,1.24904,2174 -2018-02-02 13:00:00,1.24909,1.24982,1.24382,1.24454,11821 -2018-02-02 14:00:00,1.2445,1.24601,1.2427,1.24285,7653 -2018-02-02 15:00:00,1.24288,1.2438,1.24092,1.24354,7367 -2018-02-02 16:00:00,1.24354,1.24547,1.24354,1.24454,6536 -2018-02-02 17:00:00,1.24458,1.24782,1.24456,1.24692,6212 -2018-02-02 18:00:00,1.24692,1.2491,1.24674,1.24693,5717 -2018-02-02 19:00:00,1.24692,1.24719,1.24487,1.24508,5625 -2018-02-02 20:00:00,1.24508,1.2465,1.2449,1.24618,5330 -2018-02-02 21:00:00,1.24612,1.24628,1.24514,1.24566,2431 -2018-02-04 22:00:00,1.24359,1.24455,1.2429,1.24318,1870 -2018-02-04 23:00:00,1.2431,1.2455,1.24242,1.24464,4083 -2018-02-05 00:00:00,1.24465,1.24584,1.24404,1.24581,2901 -2018-02-05 01:00:00,1.24578,1.24584,1.24447,1.24542,2331 -2018-02-05 02:00:00,1.24547,1.24626,1.2444,1.24612,2271 -2018-02-05 03:00:00,1.2461,1.24665,1.24538,1.24549,1608 -2018-02-05 04:00:00,1.24555,1.24614,1.24536,1.2459,1201 -2018-02-05 05:00:00,1.24595,1.24641,1.24532,1.24605,1257 -2018-02-05 06:00:00,1.24602,1.24627,1.2447,1.24532,1700 -2018-02-05 07:00:00,1.2453,1.2463,1.24398,1.244,3907 -2018-02-05 08:00:00,1.24394,1.24679,1.24392,1.24625,5412 -2018-02-05 09:00:00,1.24626,1.2475,1.24549,1.24608,3328 -2018-02-05 10:00:00,1.2461,1.24721,1.24586,1.24626,2002 -2018-02-05 11:00:00,1.24625,1.24634,1.24464,1.24478,3326 -2018-02-05 12:00:00,1.24474,1.24502,1.24392,1.24408,3278 -2018-02-05 13:00:00,1.24411,1.24492,1.2436,1.24375,3791 -2018-02-05 14:00:00,1.24374,1.24381,1.23998,1.24076,5495 -2018-02-05 15:00:00,1.24072,1.24295,1.23988,1.24199,5707 -2018-02-05 16:00:00,1.24198,1.2428,1.2404,1.24161,4813 -2018-02-05 17:00:00,1.24163,1.24303,1.2406,1.24288,2727 -2018-02-05 18:00:00,1.24284,1.24286,1.24115,1.24212,3928 -2018-02-05 19:00:00,1.24208,1.24218,1.23942,1.23987,3671 -2018-02-05 20:00:00,1.23992,1.24221,1.2388,1.23882,22699 -2018-02-05 21:00:00,1.23877,1.23952,1.23625,1.23671,8122 -2018-02-05 22:00:00,1.23671,1.23865,1.2367,1.23758,1076 -2018-02-05 23:00:00,1.23756,1.23838,1.23652,1.23668,3567 -2018-02-06 00:00:00,1.23668,1.23872,1.23639,1.23831,7362 -2018-02-06 01:00:00,1.2383,1.23888,1.2369,1.23754,7568 -2018-02-06 02:00:00,1.23753,1.23786,1.23547,1.23714,10085 -2018-02-06 03:00:00,1.23711,1.23786,1.2363,1.23672,4577 -2018-02-06 04:00:00,1.2367,1.2376,1.23509,1.2356,4033 -2018-02-06 05:00:00,1.2356,1.23759,1.23558,1.23756,4582 -2018-02-06 06:00:00,1.23756,1.239,1.23712,1.23818,4132 -2018-02-06 07:00:00,1.23816,1.24046,1.23754,1.23962,8702 -2018-02-06 08:00:00,1.2396,1.24346,1.23924,1.24174,8584 -2018-02-06 09:00:00,1.24178,1.24208,1.23902,1.24028,5033 -2018-02-06 10:00:00,1.24026,1.24172,1.23959,1.24088,3414 -2018-02-06 11:00:00,1.24092,1.24118,1.23709,1.23726,4143 -2018-02-06 12:00:00,1.23721,1.23732,1.23352,1.23398,6541 -2018-02-06 13:00:00,1.23402,1.23475,1.23222,1.23438,8835 -2018-02-06 14:00:00,1.23444,1.23581,1.23266,1.23364,7365 -2018-02-06 15:00:00,1.2336,1.23468,1.23138,1.23444,8429 -2018-02-06 16:00:00,1.23444,1.23842,1.23414,1.23808,5641 -2018-02-06 17:00:00,1.23809,1.24052,1.23734,1.23912,6150 -2018-02-06 18:00:00,1.23914,1.24052,1.23864,1.23988,4328 -2018-02-06 19:00:00,1.23992,1.23995,1.23852,1.23916,2665 -2018-02-06 20:00:00,1.23918,1.23956,1.23698,1.23714,4940 -2018-02-06 21:00:00,1.23716,1.23818,1.23698,1.2377,1606 -2018-02-06 22:00:00,1.23763,1.23832,1.23706,1.23803,1050 -2018-02-06 23:00:00,1.23803,1.2386,1.23774,1.23806,1558 -2018-02-07 00:00:00,1.23802,1.23936,1.23758,1.23863,2770 -2018-02-07 01:00:00,1.23862,1.23908,1.23782,1.23891,2075 -2018-02-07 02:00:00,1.23888,1.23902,1.23784,1.23831,1341 -2018-02-07 03:00:00,1.23834,1.2393,1.23833,1.23859,1750 -2018-02-07 04:00:00,1.23857,1.23934,1.23832,1.23882,880 -2018-02-07 05:00:00,1.23877,1.2392,1.2384,1.23909,1127 -2018-02-07 06:00:00,1.23907,1.23983,1.2377,1.23959,2417 -2018-02-07 07:00:00,1.23958,1.24064,1.2381,1.23828,4369 -2018-02-07 08:00:00,1.23833,1.23886,1.23628,1.23778,5513 -2018-02-07 09:00:00,1.23777,1.23819,1.235,1.23506,3705 -2018-02-07 10:00:00,1.2351,1.23526,1.23375,1.2339,2872 -2018-02-07 11:00:00,1.2339,1.23548,1.23386,1.23501,2203 -2018-02-07 12:00:00,1.23501,1.23508,1.23342,1.23422,2325 -2018-02-07 13:00:00,1.23422,1.23459,1.23338,1.23372,2824 -2018-02-07 14:00:00,1.23374,1.23452,1.23238,1.23426,4065 -2018-02-07 15:00:00,1.23427,1.23444,1.22904,1.22904,6143 diff --git a/tests/unit/GOOG.csv b/tests/unit/GOOG.csv deleted file mode 100644 index 2378976..0000000 --- a/tests/unit/GOOG.csv +++ /dev/null @@ -1,2149 +0,0 @@ -,Open,High,Low,Close,Volume -2004-08-19,100,104.06,95.96,100.34,22351900 -2004-08-20,101.01,109.08,100.5,108.31,11428600 -2004-08-23,110.75,113.48,109.05,109.4,9137200 -2004-08-24,111.24,111.6,103.57,104.87,7631300 -2004-08-25,104.96,108,103.88,106,4598900 -2004-08-26,104.95,107.95,104.66,107.91,3551000 -2004-08-27,108.1,108.62,105.69,106.15,3109000 -2004-08-30,105.28,105.49,102.01,102.01,2601000 -2004-08-31,102.3,103.71,102.16,102.37,2461400 -2004-09-01,102.7,102.97,99.67,100.25,4573700 -2004-09-02,99.19,102.37,98.94,101.51,7566900 -2004-09-03,100.95,101.74,99.32,100.01,2578800 -2004-09-07,101.01,102,99.61,101.58,2926700 -2004-09-08,100.74,103.03,100.5,102.3,2495300 -2004-09-09,102.53,102.71,101,102.31,2032900 -2004-09-10,101.6,106.56,101.3,105.33,4353800 -2004-09-13,106.63,108.41,106.46,107.5,3926000 -2004-09-14,107.45,112,106.79,111.49,5419900 -2004-09-15,110.56,114.23,110.2,112,5361900 -2004-09-16,112.34,115.8,111.65,113.97,4637800 -2004-09-17,114.42,117.49,113.55,117.49,4741000 -2004-09-20,116.95,121.6,116.77,119.36,5319700 -2004-09-21,119.81,120.42,117.51,117.84,3618000 -2004-09-22,117.4,119.67,116.81,118.38,3794400 -2004-09-23,118.84,122.63,117.02,120.82,4272100 -2004-09-24,120.94,124.1,119.76,119.83,4566300 -2004-09-27,119.56,120.88,117.8,118.26,3536600 -2004-09-28,121.3,127.4,120.21,126.86,8473000 -2004-09-29,126.7,135.02,126.23,131.08,15273500 -2004-09-30,129.9,132.3,129,129.6,6885900 -2004-10-01,130.8,134.24,128.9,132.58,7570000 -2004-10-04,135.25,136.87,134.03,135.06,6517900 -2004-10-05,134.66,138.53,132.24,138.37,7494100 -2004-10-06,137.55,138.45,136,137.08,6697400 -2004-10-07,136.92,139.88,136.55,138.85,7064600 -2004-10-08,138.72,139.68,137.02,137.73,5540300 -2004-10-11,137,138.86,133.85,135.26,5241300 -2004-10-12,134.44,137.61,133.4,137.4,5838600 -2004-10-13,143.32,143.55,140.08,140.9,9893000 -2004-10-14,141.01,142.38,138.56,142,5226300 -2004-10-15,144.93,145.5,141.95,144.11,6604000 -2004-10-18,143.2,149.2,141.21,149.16,7025200 -2004-10-19,150.5,152.4,147.35,147.94,9064000 -2004-10-20,148.03,148.99,139.6,140.49,11372700 -2004-10-21,144.4,150.13,141.62,149.38,14589500 -2004-10-22,170.54,180.17,164.08,172.43,36891900 -2004-10-25,176.4,194.43,172.55,187.4,32764200 -2004-10-26,186.34,192.64,180,181.8,22307100 -2004-10-27,182.72,189.52,181.77,185.97,13356500 -2004-10-28,186.68,194.39,185.6,193.3,14846800 -2004-10-29,198.89,199.95,190.6,190.64,21162500 -2004-11-01,193.55,197.67,191.27,196.03,12224900 -2004-11-02,198.78,199.25,193.34,194.87,11346300 -2004-11-03,198.18,201.6,190.75,191.67,13888700 -2004-11-04,188.44,190.4,183.35,184.7,14409600 -2004-11-05,181.98,182.3,168.55,169.35,19833100 -2004-11-08,170.93,175.44,169.4,172.55,11191800 -2004-11-09,174.1,175.2,165.27,168.7,11064200 -2004-11-10,170.67,172.52,166.33,167.86,10644000 -2004-11-11,169.13,183.75,167.57,183.02,14985500 -2004-11-12,185.23,189.8,177.4,182,16746100 -2004-11-15,180.45,188.32,178.75,184.87,11901500 -2004-11-16,177.5,179.47,170.83,172.54,20917400 -2004-11-17,169.02,177.5,169,172.5,18132900 -2004-11-18,170.29,174.42,165.73,167.54,16629600 -2004-11-19,169.1,169.98,166.52,169.4,8769300 -2004-11-22,164.47,169.5,161.31,165.1,12368200 -2004-11-23,167.97,170.83,166.5,167.52,12413300 -2004-11-24,174.82,177.21,172.51,174.76,15281000 -2004-11-26,175.8,180.03,175.32,179.39,6480100 -2004-11-29,180.36,182.95,177.51,181.05,10666600 -2004-11-30,180.71,183,180.25,181.98,7700000 -2004-12-01,181.95,182.5,179.55,179.96,7864100 -2004-12-02,179.9,181.51,178.55,179.4,6260900 -2004-12-03,179.95,181.06,177.6,180.4,5869200 -2004-12-06,179.13,180.7,176.02,176.29,6254000 -2004-12-07,176,176.2,170.55,171.43,6870900 -2004-12-08,170.35,173.68,168.73,169.98,7541800 -2004-12-09,170.25,173.5,168.47,173.43,7654000 -2004-12-10,173.43,174.88,171.29,171.65,4317200 -2004-12-13,172.17,173.18,169.45,170.45,4818600 -2004-12-14,171,178.82,169.6,178.69,11088400 -2004-12-15,177.99,180.69,176.66,179.78,11471000 -2004-12-16,176.95,180.49,175.95,176.47,8572800 -2004-12-17,176.76,180.5,176.55,180.08,7386200 -2004-12-20,182,188.46,181.87,185.02,9834500 -2004-12-21,186.31,187.88,183.4,183.75,5516300 -2004-12-22,183.9,186.85,183.01,186.3,3907000 -2004-12-23,187.45,188.6,186,187.9,3614600 -2004-12-27,189.15,193.3,189.1,191.91,6104100 -2004-12-28,192.11,193.55,191.01,192.76,4145800 -2004-12-29,191.78,193.52,191.78,192.9,2678100 -2004-12-30,192.97,198.23,191.85,197.6,5904300 -2004-12-31,199.23,199.88,192.56,192.79,7668500 -2005-01-03,197.4,203.64,195.46,202.71,15844200 -2005-01-04,201.4,202.93,193.48,194.5,13755900 -2005-01-05,193.45,196.9,192.23,193.51,8236600 -2005-01-06,195.08,195.9,187.72,188.55,10387100 -2005-01-07,190.64,194.25,188.78,193.85,9662900 -2005-01-10,194.5,198.1,191.83,195.06,7539600 -2005-01-11,195.62,197.71,193.18,193.54,6958700 -2005-01-12,194.33,195.93,190.5,195.38,8177800 -2005-01-13,195.38,197.39,194.05,195.33,6849400 -2005-01-14,196,200.01,194.13,199.97,9640300 -2005-01-18,200.97,205.02,198.66,203.9,13172600 -2005-01-19,204.65,205.3,196.71,197.3,11257700 -2005-01-20,192.5,196.25,192,193.92,9001600 -2005-01-21,194.54,195.36,188.12,188.28,9258400 -2005-01-24,188.69,189.33,180.32,180.72,14022700 -2005-01-25,181.94,182.24,176.29,177.12,10659200 -2005-01-26,179.27,189.41,179.15,189.24,12307900 -2005-01-27,188.76,188.86,185.2,188.08,6627400 -2005-01-28,190.02,194.7,186.34,190.34,12208200 -2005-01-31,193.69,196.36,191.72,195.62,9596700 -2005-02-01,194.38,196.66,190.63,191.9,18839000 -2005-02-02,215.55,216.8,203.66,205.96,32799300 -2005-02-03,205.99,213.37,205.81,210.86,12988100 -2005-02-04,206.47,207.75,202.6,204.36,14819300 -2005-02-07,205.26,206.4,195.51,196.03,12960400 -2005-02-08,196.96,200.02,194.53,198.64,11480000 -2005-02-09,200.76,201.6,189.46,191.58,17171500 -2005-02-10,191.97,192.21,185.25,187.98,18982700 -2005-02-11,186.66,192.32,186.07,187.4,13116000 -2005-02-14,182.85,193.08,181,192.99,38562200 -2005-02-15,193.6,199.84,193.08,195.23,25782800 -2005-02-16,194.7,199.33,194.3,198.41,16532300 -2005-02-17,197.83,199.75,196.81,197.9,10414400 -2005-02-18,198.51,198.84,196.66,197.95,8485900 -2005-02-22,196.5,198.9,190.39,191.37,13483700 -2005-02-23,193.3,194.48,188.66,193.95,15586000 -2005-02-24,183.37,189.85,182.23,188.89,25814300 -2005-02-25,189.15,189.92,185.51,185.87,9973500 -2005-02-28,186,189.87,185.85,187.99,7818400 -2005-03-01,189.29,189.75,182,186.06,9311200 -2005-03-02,185.95,187.67,184.36,185.18,7285500 -2005-03-03,186.13,187.75,184.31,187.01,7608600 -2005-03-04,186.7,187.25,185.07,185.9,6774100 -2005-03-07,187.78,189.6,187.03,188.81,8667400 -2005-03-08,189.1,189.85,184.97,185.2,8046100 -2005-03-09,184.21,184.65,180.16,181.35,11360400 -2005-03-10,181.01,181.2,177.4,179.98,10960500 -2005-03-11,180.44,180.95,177.15,177.8,8028300 -2005-03-14,178.33,178.4,172.57,174.99,11146600 -2005-03-15,175.3,180,174.21,178.61,10422100 -2005-03-16,176.7,178.61,175.01,175.6,7106300 -2005-03-17,177.13,179.64,175.8,179.29,8260600 -2005-03-18,178.81,180.4,178.31,180.04,7090000 -2005-03-21,179.27,182.17,177.25,180.88,7483700 -2005-03-22,181.18,181.94,177.85,178.6,5631700 -2005-03-23,177.97,180.24,177.97,178.98,4845000 -2005-03-24,180.7,180.86,179.2,179.25,3705200 -2005-03-28,181.68,184.8,180.95,181.42,8738000 -2005-03-29,181.05,183.28,178.07,179.57,6473000 -2005-03-30,180.64,181.45,179.6,180.45,6236100 -2005-03-31,177.95,181.39,177.64,180.51,6768600 -2005-04-01,181.76,182.95,179.99,180.04,6182000 -2005-04-04,179.95,185.32,179.84,185.29,8076400 -2005-04-05,187.73,190.26,187.57,188.57,8736700 -2005-04-06,189.24,189.65,187.58,189.22,5252600 -2005-04-07,188.78,194.62,188.64,193.76,9692200 -2005-04-08,193.69,195.1,191.45,192.05,5116600 -2005-04-11,193.09,194.8,192.32,193.23,5410500 -2005-04-12,193,194.42,189.41,193.96,7319600 -2005-04-13,193.47,194.32,189.73,192.93,6555800 -2005-04-14,193.27,194.36,190.1,191.45,6152700 -2005-04-15,190.1,190.34,184.66,185,11577400 -2005-04-18,184.58,187.88,183.49,186.97,6550300 -2005-04-19,189.33,192,188.03,191.4,8430000 -2005-04-20,198.58,200.5,195.91,198.1,15451500 -2005-04-21,200.42,205,199.32,204.22,17751900 -2005-04-22,222.9,224,214.26,215.81,33205100 -2005-04-25,217.82,224.74,217.52,223.53,19840000 -2005-04-26,220.22,222,218.29,218.75,17272000 -2005-04-27,217.99,220.85,216.74,219.78,10264800 -2005-04-28,219.5,222.08,217.71,219.45,8682800 -2005-04-29,221.91,222.25,217.82,220,9170200 -2005-05-02,222.05,223.7,220.21,222.29,9767400 -2005-05-03,221.85,228.15,221.32,226.19,17780200 -2005-05-04,227.23,229.88,227,228.5,12083500 -2005-05-05,228.62,228.62,225.88,226.98,7509600 -2005-05-06,228.4,229.25,226.47,228.02,6763900 -2005-05-09,228,228.5,225.43,226.02,5536800 -2005-05-10,225.47,227.8,224.72,227.8,6345800 -2005-05-11,228.97,231.98,227.93,231.29,11478800 -2005-05-12,230.81,232.23,228.2,228.72,8948200 -2005-05-13,229.18,231.09,227.32,229.24,7415500 -2005-05-16,229.68,231.62,228.57,231.05,5681400 -2005-05-17,230.56,233.45,230.2,233.13,7808900 -2005-05-18,233.61,239.97,233.52,239.16,12312000 -2005-05-19,240.34,241.17,238.27,239.18,9716500 -2005-05-20,241.21,241.67,239.65,241.61,8163500 -2005-05-23,243.16,258.1,242.71,255.45,21388300 -2005-05-24,256.96,265.44,253.5,256,29043100 -2005-05-25,252.73,260.98,250.63,260.81,18057900 -2005-05-26,260.96,263.76,258.3,259.2,13546600 -2005-05-27,260.46,266.05,259.25,266,12184100 -2005-05-31,269.43,278.4,269.37,277.27,22236800 -2005-06-01,283.2,292.89,282.02,288,35191700 -2005-06-02,288.73,289.78,284.6,287.9,17974100 -2005-06-03,286.79,289.3,277.41,280.26,18782300 -2005-06-06,282.39,293.75,281.83,290.94,22525900 -2005-06-07,297.1,299.59,290.3,293.12,24323000 -2005-06-08,292.85,293.19,278,279.56,25700900 -2005-06-09,284.72,288.5,280.56,286.31,16441100 -2005-06-10,286.99,287.28,280.02,282.5,12696600 -2005-06-13,279.82,284.19,276.52,282.75,12803200 -2005-06-14,278.59,281.24,277.75,278.35,10091900 -2005-06-15,275,277.3,267.43,274.8,20883100 -2005-06-16,274.26,278.3,273.07,277.44,12462400 -2005-06-17,279,280.3,275.9,280.3,10434400 -2005-06-20,276.09,287.67,271.73,286.7,21024700 -2005-06-21,288.07,290.3,284.97,287.84,15132300 -2005-06-22,289.67,292.32,288.67,289.3,10474000 -2005-06-23,288,294.81,286.5,289.71,14056400 -2005-06-24,290.9,298,289.58,297.25,17771200 -2005-06-27,298.9,304.47,293.86,304.1,17802900 -2005-06-28,306.28,309.25,302,302,19036500 -2005-06-29,302.5,304.38,292.15,292.72,18298700 -2005-06-30,294.34,298.93,291.04,294.15,15094400 -2005-07-01,295.04,296.24,289.22,291.25,9227600 -2005-07-05,292.1,295.98,290.23,295.71,7494000 -2005-07-06,297.3,297.6,291.38,291.52,8000300 -2005-07-07,289.39,295.8,288.51,295.54,10672100 -2005-07-08,296.25,297.5,294.05,296.23,7457600 -2005-07-11,296.4,296.6,291.02,293.35,8390300 -2005-07-12,293.39,294.4,290.93,291.78,5864900 -2005-07-13,292.51,299.24,292.1,298.86,11437900 -2005-07-14,305.34,306.75,300.07,300.89,10667700 -2005-07-15,301.24,303.4,299.78,301.19,8438400 -2005-07-18,300,301.9,297.75,299.54,6207800 -2005-07-19,302.1,310.35,301.8,309.9,12621400 -2005-07-20,305.57,312.61,301.8,312,14310400 -2005-07-21,314.05,317.8,311.21,313.94,19789400 -2005-07-22,306.37,309.25,296.33,302.4,23386800 -2005-07-25,302.39,303.29,294.96,295.85,9658800 -2005-07-26,295.01,298,292.09,296.09,9816900 -2005-07-27,297.74,298.23,292.4,296.93,7217900 -2005-07-28,297.41,297.41,293.28,293.5,5925600 -2005-07-29,292.14,292.84,286.99,287.76,8363300 -2005-08-01,288.12,292.5,288.1,291.61,5662400 -2005-08-02,291.6,299.52,291.12,299.19,7290200 -2005-08-03,298,299.72,295.6,297.3,5930600 -2005-08-04,295.55,299,295.25,297.73,5236500 -2005-08-05,297.5,298.51,291.31,292.35,5939700 -2005-08-08,293.6,295.65,290.49,291.25,4481800 -2005-08-09,291.96,292.68,288.51,291.57,5779300 -2005-08-10,291.3,292.33,284.88,285.68,6879000 -2005-08-11,285.89,286.58,280.62,284.05,7514900 -2005-08-12,283.36,290.2,281.64,289.72,6585900 -2005-08-15,289.8,292.77,283.77,284,8174700 -2005-08-16,284.88,287.79,283.34,285.65,7109200 -2005-08-17,285.51,286.57,284,285.1,3883300 -2005-08-18,275.91,280.5,275,279.99,11872800 -2005-08-19,280.99,281.45,279.62,280,5542900 -2005-08-22,281.24,281.47,273.35,274.01,6813000 -2005-08-23,276.16,279.74,274.12,279.58,5821700 -2005-08-24,277.57,284.75,276.45,282.57,8593100 -2005-08-25,282.55,284,279.97,282.59,4376600 -2005-08-26,283.48,285.02,282.66,283.58,3755300 -2005-08-29,282.24,289.12,282.24,288.45,5903000 -2005-08-30,287.39,289.51,285.88,287.27,4792000 -2005-08-31,288.23,288.5,284.36,286,5034000 -2005-09-01,285.91,287.5,285,286.25,2742100 -2005-09-02,286.51,289.99,286.44,288.45,3434500 -2005-09-06,289,289.39,286.8,287.11,4212300 -2005-09-07,285.89,295.5,285.28,294.87,7499500 -2005-09-08,294.83,299.28,293.36,295.39,6613300 -2005-09-09,297.28,299.1,296.56,299.09,4390500 -2005-09-12,301.75,311.42,301,309.74,10386500 -2005-09-13,309,315.53,306.17,311.68,10299900 -2005-09-14,308.73,313.28,300.3,303,11275800 -2005-09-15,299.52,306.75,297.91,302.62,15466200 -2005-09-16,304.02,304.5,299.87,300.2,7579800 -2005-09-19,301,306,300.71,303.79,5761900 -2005-09-20,306.15,311.3,305.23,307.91,9351000 -2005-09-21,308.41,313.76,305.96,311.9,10119700 -2005-09-22,311.5,319.22,310.17,311.37,13006400 -2005-09-23,313,317.21,312.59,315.36,8483800 -2005-09-26,319.5,320.95,312.56,314.28,9894400 -2005-09-27,314.95,318.41,313.38,313.94,6873100 -2005-09-28,314.22,315.1,305.6,306,7997400 -2005-09-29,306.68,310.72,306.08,309.62,5613800 -2005-09-30,314.22,317.5,312.29,316.46,9151300 -2005-10-03,313.63,320.11,312.79,318.68,9160300 -2005-10-04,319.95,321.28,310.74,311,9144300 -2005-10-05,312.69,314.9,308,310.71,8328400 -2005-10-06,314.14,314.48,310.09,312.75,7993800 -2005-10-07,314.79,316.67,310.54,312.99,6770300 -2005-10-10,313.31,314.82,309.15,310.65,5572200 -2005-10-11,310.61,312.65,304.86,306.1,8542600 -2005-10-12,305.2,307.19,299,300.97,9306200 -2005-10-13,302,302,290.68,297.44,10567700 -2005-10-14,299.9,300.23,292.54,296.14,8519100 -2005-10-17,297.5,305.2,294.56,305,7566700 -2005-10-18,304.96,307.96,302.74,303.28,7077800 -2005-10-19,304,309.87,303.96,308.7,7010700 -2005-10-20,309.99,311.13,301.21,303.2,13911700 -2005-10-21,345.8,346.43,333,339.9,22892400 -2005-10-24,343.37,349.3,342.19,348.65,9431700 -2005-10-25,345.78,347.4,342.86,346.91,6878300 -2005-10-26,346.28,356,346.19,355.44,8907500 -2005-10-27,356.6,357.09,351.68,353.06,5134400 -2005-10-28,355.27,358.95,355.02,358.17,5903500 -2005-10-31,360.24,374.75,359.51,372.14,14342900 -2005-11-01,371.86,383.9,369.01,379.38,16356100 -2005-11-02,381.7,385,377.17,379.68,10565400 -2005-11-03,382.41,386.58,381.38,385.95,7448400 -2005-11-04,389.98,391.79,385.45,390.43,8824900 -2005-11-07,395.1,397.47,392.15,395.03,9591500 -2005-11-08,394.25,395.59,388.58,389.9,7897500 -2005-11-09,386.67,388.29,378.03,379.15,10466900 -2005-11-10,378.36,391.35,377.43,391.1,9128700 -2005-11-11,395.12,396.9,388.85,390.4,7063900 -2005-11-14,392.12,398.22,391.53,396.97,7807900 -2005-11-15,394.38,397,390.95,392.8,8624900 -2005-11-16,396.2,398.85,394.11,398.15,8695200 -2005-11-17,401.8,403.81,399.53,403.45,9212200 -2005-11-18,403.49,404.5,399.85,400.21,7025700 -2005-11-21,399.17,409.98,393.49,409.36,10335100 -2005-11-22,408.65,417.31,406.23,416.47,9596000 -2005-11-23,417.04,424.72,415.78,422.86,10085000 -2005-11-25,425.78,428.75,425.3,428.62,4840100 -2005-11-28,429.82,431.24,422.44,423.48,11008400 -2005-11-29,424.46,426.4,402.14,403.54,21495800 -2005-11-30,404.26,408.45,395.56,404.91,15596600 -2005-12-01,409.2,415.44,408.29,414.09,9744900 -2005-12-02,416.94,419.53,413.86,417.7,7543500 -2005-12-05,417,417.5,404.28,405.85,10289400 -2005-12-06,408.7,416.41,401.7,404.54,15114700 -2005-12-07,406.16,406.7,399.01,404.22,11665900 -2005-12-08,405.3,410.65,402.64,410.65,8910100 -2005-12-09,415,415.78,408.56,409.2,7643400 -2005-12-12,414.63,415.21,409.95,412.61,6950100 -2005-12-13,412.5,418,411.64,417.49,8157000 -2005-12-14,417.04,419.73,415.49,418.96,6630400 -2005-12-15,419.11,423.14,416.5,422.55,6045800 -2005-12-16,425.34,432.5,422.75,430.15,16330500 -2005-12-19,432.2,446.21,420.11,424.6,21936800 -2005-12-20,427.86,432.2,424.67,429.74,10084700 -2005-12-21,433.55,436.86,420.71,426.33,11221900 -2005-12-22,431.77,432.86,425.93,432.04,7546600 -2005-12-23,432.15,432.5,428.78,430.93,4595100 -2005-12-27,431.86,431.86,422.76,424.64,6702800 -2005-12-28,424.34,427.78,421.26,426.69,7117900 -2005-12-29,427.98,428.73,419.17,420.15,6945800 -2005-12-30,417.27,418.21,413.74,414.86,7587100 -2006-01-03,422.52,435.67,418.22,435.23,13121200 -2006-01-04,443.9,448.96,439.75,445.24,15286400 -2006-01-05,446,451.55,441.5,451.24,10808300 -2006-01-06,456.87,470.5,453.24,465.66,17756900 -2006-01-09,466.41,473.4,460.94,466.9,12791900 -2006-01-10,464.42,470.25,462.04,469.76,9097100 -2006-01-11,471.27,475.11,469.18,471.63,9007400 -2006-01-12,473.72,474.99,461.5,463.63,10125300 -2006-01-13,464.31,466.89,461.61,466.25,7656600 -2006-01-17,463.06,469.9,462.53,467.11,8270300 -2006-01-18,447.3,457.36,443.25,444.91,20485700 -2006-01-19,451.17,453.49,433,436.45,14537300 -2006-01-20,438.7,440.03,394.74,399.46,41116700 -2006-01-23,407.38,428.39,405.73,427.5,22741400 -2006-01-24,436.03,444.95,434.48,443.03,15464600 -2006-01-25,451.26,454.23,429.22,433,18739800 -2006-01-26,439.54,439.99,423.56,434.27,12926100 -2006-01-27,435,438.22,428.98,433.49,8452200 -2006-01-30,429.23,433.28,425,426.82,8588900 -2006-01-31,430.57,439.6,423.97,432.66,22066000 -2006-02-01,389.03,402,387.52,401.78,27122500 -2006-02-02,403.82,406.5,395.98,396.04,11807700 -2006-02-03,393.62,393.9,372.57,381.55,18281800 -2006-02-06,385.31,389.9,379.56,385.1,8940400 -2006-02-07,382.99,383.7,363.35,367.92,16630200 -2006-02-08,368.48,370.69,354.67,369.08,20804100 -2006-02-09,371.2,374.4,356.11,358.77,11912400 -2006-02-10,361.95,364.5,353.14,362.61,15223500 -2006-02-13,346.64,350.6,341.89,345.7,19717800 -2006-02-14,345.33,351.69,342.4,343.32,14654000 -2006-02-15,341.27,346,337.83,342.38,12947000 -2006-02-16,345.67,367,344.49,366.46,21315500 -2006-02-17,369.86,372.14,363.62,368.75,14320200 -2006-02-21,366.44,373.54,365.11,366.59,8686000 -2006-02-22,367.15,368.95,363.86,365.49,6476200 -2006-02-23,365.61,381.24,365.39,378.07,12551600 -2006-02-24,377.3,380.07,373.49,377.4,6484300 -2006-02-27,381.27,391.7,380.28,390.38,10212200 -2006-02-28,393.2,397.54,338.51,362.62,39437600 -2006-03-01,368.56,369.45,361.3,364.8,12061200 -2006-03-02,364.28,381.1,362.2,376.45,18330300 -2006-03-03,384.3,387.24,375.76,378.18,11962000 -2006-03-06,380.91,383.4,367.14,368.1,8939700 -2006-03-07,365.02,368.45,358.15,364.45,10378800 -2006-03-08,353.93,360.03,350.54,353.88,11745600 -2006-03-09,355.39,358.53,341.5,343,13910400 -2006-03-10,343.5,344.5,331.55,337.5,19325600 -2006-03-13,340.93,346.1,335.45,337.06,13642400 -2006-03-14,337.14,352.37,332.62,351.16,18450700 -2006-03-15,350.77,352.3,340.53,344.5,12768800 -2006-03-16,348.61,348.75,337.9,338.77,10016700 -2006-03-17,338.8,341.78,334.93,339.79,8551700 -2006-03-20,342.34,350.09,341.54,348.19,10407600 -2006-03-21,350.01,351.66,339.08,339.92,9831100 -2006-03-22,339.75,344.1,337.5,340.22,7596000 -2006-03-23,342.35,345.75,340.2,341.89,7434700 -2006-03-24,368.62,370.09,362.51,365.8,15180600 -2006-03-27,367.09,371.71,365,369.69,7023700 -2006-03-28,371.71,377.86,371.17,377.2,8945800 -2006-03-29,379.94,399,379.51,394.98,19027500 -2006-03-30,389.19,393.5,383.61,388.44,14711700 -2006-03-31,388.74,391.87,384.03,390,36521400 -2006-04-03,389.53,392.47,387.93,389.7,8122700 -2006-04-04,389.9,404.9,388.14,404.34,15715700 -2006-04-05,408.2,414.57,402.82,407.99,13410500 -2006-04-06,406.49,413.89,405.43,411.18,8598500 -2006-04-07,412.41,412.85,404.02,406.16,7025900 -2006-04-10,407.08,417.17,405.25,416.38,9320100 -2006-04-11,416.42,419.1,406.22,409.66,11107200 -2006-04-12,409,411.33,405.19,408.95,6017000 -2006-04-13,408.63,409.76,400.5,402.16,6552900 -2006-04-17,403.45,412.5,400.84,406.82,8259500 -2006-04-18,407.93,409.83,401.5,404.24,8137600 -2006-04-19,412.57,413.64,406.73,410.5,6781700 -2006-04-20,411.01,416,408.2,415,12271500 -2006-04-21,448.9,450.72,436.17,437.1,22551300 -2006-04-24,439.4,444.7,436.52,440.5,8836400 -2006-04-25,439.63,441.04,426,427.16,9569000 -2006-04-26,427.74,430.04,423.53,425.97,7277800 -2006-04-27,422.91,426.91,419.39,420.03,8337900 -2006-04-28,418.63,425.73,416.3,417.94,7421300 -2006-05-01,418.47,419.44,398.55,398.9,10361200 -2006-05-02,401.08,402.49,388.4,394.8,13104300 -2006-05-03,396.35,401.5,390.88,394.17,8072200 -2006-05-04,395.03,398.87,392.21,394.75,4652000 -2006-05-05,397.6,400.68,391.78,394.3,6065000 -2006-05-08,395.11,397.12,390.05,394.78,5118600 -2006-05-09,395.7,409,393.75,408.8,9140600 -2006-05-10,408.31,411.71,401.86,402.98,6187200 -2006-05-11,403.42,404.71,384.98,387,8892800 -2006-05-12,383.54,384.87,373.55,374.13,10087600 -2006-05-15,375.93,380.15,368.25,376.2,8590100 -2006-05-16,375.99,376.86,369.89,371.3,6491100 -2006-05-17,370.61,379.84,370.22,374.5,10643800 -2006-05-18,378.78,381.81,370.71,370.99,5835000 -2006-05-19,373.28,374.5,360.57,370.02,11398200 -2006-05-22,367.85,373.03,365.25,370.95,8604400 -2006-05-23,374.21,383.88,373.56,375.58,8983000 -2006-05-24,377.35,383.44,371.61,381.25,9553800 -2006-05-25,379.08,383,372.31,382.99,8194600 -2006-05-26,384.55,385.88,380.03,381.35,3667000 -2006-05-30,378.28,381,371.45,371.94,4316000 -2006-05-31,373.8,378.25,366.78,371.82,7981300 -2006-06-01,373.54,382.99,371.6,382.62,6278000 -2006-06-02,386.84,387.08,377.45,379.44,6386400 -2006-06-05,376.18,381.45,374.15,374.44,5558500 -2006-06-06,376.58,390,376.3,389.99,10259800 -2006-06-07,393.24,394.86,386.5,386.51,8911300 -2006-06-08,387.75,394.27,378.59,393.3,10359500 -2006-06-09,392.19,395.43,385.35,386.57,6157500 -2006-06-12,388.34,390.49,381,381.54,5019100 -2006-06-13,380.9,387,378.12,386.52,7659100 -2006-06-14,389.83,391.1,378.52,384.39,7772000 -2006-06-15,386.62,392.25,383,391,6785700 -2006-06-16,389.1,390.93,388,390.7,5304600 -2006-06-19,390.85,394.8,386.98,388.14,7633100 -2006-06-20,388.03,391.87,386.51,387.17,4039900 -2006-06-21,391.06,404,389.75,402.13,8744400 -2006-06-22,401.58,406,388,399.95,5911900 -2006-06-23,402.76,409.75,400.74,404.86,5314800 -2006-06-26,406.75,408.3,403.25,404.22,3551200 -2006-06-27,405.71,408,401.01,402.32,4107100 -2006-06-28,404.01,406.48,401.13,406.11,3710500 -2006-06-29,407.99,418.2,405.82,417.81,6658200 -2006-06-30,415.6,419.33,412.33,419.33,6258000 -2006-07-03,420.04,423.77,419.45,423.2,2156700 -2006-07-05,421.52,422.8,415.64,421.46,4985600 -2006-07-06,423.38,425.38,421.98,423.19,3687100 -2006-07-07,426.05,427.89,415.88,420.45,6041900 -2006-07-10,423.44,425.23,416.38,418.2,4436400 -2006-07-11,418.51,425.05,413.03,424.56,5971300 -2006-07-12,422.09,422.74,416.73,417.25,4906700 -2006-07-13,414,418.34,406.83,408.83,6924500 -2006-07-14,410.33,411.49,398.61,403.5,7552100 -2006-07-17,404.63,411,403.72,407.89,5811900 -2006-07-18,409.75,410.57,397.74,403.05,8536800 -2006-07-19,395.01,401.14,394.66,399,8518500 -2006-07-20,404.28,404.44,385.66,387.12,12538700 -2006-07-21,386.14,391.75,377.69,390.11,11754600 -2006-07-24,392.82,393.89,381.21,390.9,8086100 -2006-07-25,385.02,391.31,383.8,389.36,5761100 -2006-07-26,388.2,391.91,383,385.5,5531900 -2006-07-27,387.37,387.49,377.95,382.4,5641100 -2006-07-28,382,389.56,381.73,388.12,4083600 -2006-07-31,388,389.17,383.31,386.6,4595300 -2006-08-01,385.11,385.77,375.51,375.51,5463200 -2006-08-02,375.6,377.17,365.2,367.23,7097800 -2006-08-03,364.98,377.91,363.36,375.39,6327000 -2006-08-04,379.56,380.68,371.75,373.85,5095200 -2006-08-07,371.5,379.73,371.15,377.95,3946900 -2006-08-08,382.82,384.5,379.09,381,5743200 -2006-08-09,382.8,384.68,376.36,376.94,4311000 -2006-08-10,373.88,377.67,372.46,374.2,4261900 -2006-08-11,374.4,375.28,368,368.5,3766500 -2006-08-14,371.5,375.13,368.67,369.43,4968300 -2006-08-15,374.11,381.67,372.6,380.97,6698200 -2006-08-16,383.48,388.45,382.12,387.72,5853200 -2006-08-17,386.39,390,383.92,385.8,5080200 -2006-08-18,386.31,387.09,380.75,383.36,4952200 -2006-08-21,378.1,379,375.22,377.3,4023300 -2006-08-22,377.73,379.26,374.84,378.29,4164100 -2006-08-23,377.64,378.27,372.66,373.43,3642300 -2006-08-24,374.44,376.4,372.26,373.73,3482500 -2006-08-25,373.08,375.32,372.5,373.26,2466700 -2006-08-28,375.61,380.95,375,380.95,4164000 -2006-08-29,380.78,382.32,377.2,378.95,4460000 -2006-08-30,379.21,384.65,378.51,380.75,4044400 -2006-08-31,381.49,382.15,378.2,378.53,2959900 -2006-09-01,380.99,381.28,377.19,378.6,2672900 -2006-09-05,379.87,385.4,377.44,384.36,4074300 -2006-09-06,382.1,383.19,379.66,380.14,3724100 -2006-09-07,379.39,381.75,377.4,378.49,3842000 -2006-09-08,376.72,380.79,376.72,377.85,3083400 -2006-09-11,378.26,384.69,377.77,384.09,4529200 -2006-09-12,385,392.73,384.88,391.9,5442200 -2006-09-13,395.15,406.76,395.1,406.57,9768200 -2006-09-14,404.3,406.28,401.93,403.98,5366100 -2006-09-15,407.48,410.05,406.74,409.88,7838200 -2006-09-18,410,418.69,409.47,414.69,7106700 -2006-09-19,415.46,415.49,392.74,403.81,14292900 -2006-09-20,407.1,407.39,394.62,397,9147800 -2006-09-21,400.3,408.45,399.86,406.85,10692100 -2006-09-22,404.98,407.45,401.36,403.78,4649600 -2006-09-25,405.58,409.45,402.5,403.98,5737300 -2006-09-26,405.5,407.68,401.77,406.87,5289400 -2006-09-27,406.3,411.22,402.37,402.92,5876700 -2006-09-28,404.08,406.98,400.54,403.58,5107400 -2006-09-29,405.13,405.62,401.41,401.9,3310900 -2006-10-02,401.9,406,400.8,401.44,3651900 -2006-10-03,401.29,406.46,398.19,404.04,5464700 -2006-10-04,404.97,415.77,403.05,415.7,6661800 -2006-10-05,414.7,418.24,410.86,411.81,5789800 -2006-10-06,410.22,421.91,409.75,420.5,7336500 -2006-10-09,424.8,431.95,423.42,429,7583300 -2006-10-10,431.56,437.85,422.39,426.65,9788600 -2006-10-11,425.02,429.91,423.76,426.5,5635400 -2006-10-12,428.56,429.68,424,427.44,4844000 -2006-10-13,427.76,429.5,425.56,427.3,3622500 -2006-10-16,427.7,429.2,421.34,421.75,4319400 -2006-10-17,420.3,423.75,416.7,420.64,5211000 -2006-10-18,422.99,424.75,417.5,419.31,6017300 -2006-10-19,420.23,429.5,419.57,426.06,11503500 -2006-10-20,458.99,460.1,453.59,459.67,11647900 -2006-10-23,462.28,484.64,460.37,480.78,15104500 -2006-10-24,476.28,477.86,471.41,473.31,8660200 -2006-10-25,477.49,488.5,475.11,486.6,9187500 -2006-10-26,487.68,491.96,484.2,485.1,7031700 -2006-10-27,483.9,485.24,472.49,475.2,6604000 -2006-10-30,474.82,480.46,470.01,476.57,6563100 -2006-10-31,478.06,482.16,473.84,476.39,6285400 -2006-11-01,478.76,479.13,465.26,467.5,5426300 -2006-11-02,467.5,473.73,466.38,469.91,5236700 -2006-11-03,472.23,473.75,465.06,471.8,4907700 -2006-11-06,473.77,479.66,472.33,476.95,4991500 -2006-11-07,476.95,479.02,471.77,472.57,4897100 -2006-11-08,470.35,481.74,468.6,475,7965000 -2006-11-09,476.5,479.49,471.86,472.63,4879200 -2006-11-10,473.78,474.72,470.29,473.55,2796700 -2006-11-13,474.9,481.17,474.14,481.03,4341900 -2006-11-14,480.7,489.95,480.5,489.3,7223400 -2006-11-15,493.43,499.85,491.93,491.93,8370700 -2006-11-16,495,497.68,492.56,495.9,5092600 -2006-11-17,493.25,499.66,493,498.79,5511000 -2006-11-20,498.4,498.4,492.65,495.05,5124500 -2006-11-21,496.54,510,495.83,509.65,8427500 -2006-11-22,510.97,513,505.78,508.01,4500700 -2006-11-24,504.5,507.5,504,505,1732700 -2006-11-27,501.37,501.78,484.75,484.75,7324700 -2006-11-28,481.13,489.86,477.03,489.5,7797600 -2006-11-29,494.24,494.74,482.25,484.65,6315300 -2006-11-30,484.19,490.4,481.55,484.81,5577500 -2006-12-01,485.98,488.39,478.5,480.8,5631400 -2006-12-04,483,487.43,479.35,484.85,4899900 -2006-12-05,487.4,489.44,484.89,487,4103000 -2006-12-06,486.96,492.4,484.52,488.71,4450300 -2006-12-07,490.23,491.8,482.42,482.64,4664300 -2006-12-08,481.94,488.6,480,484.11,3974900 -2006-12-11,484.92,488.9,483.8,483.93,3263400 -2006-12-12,483.85,486.36,480.28,481.78,4181000 -2006-12-13,484.69,485.5,477.02,478.99,4662100 -2006-12-14,480.25,483.75,477.26,482.12,4748900 -2006-12-15,482.64,484.11,479.84,480.3,5190800 -2006-12-18,482.51,482.74,460.72,462.8,8016600 -2006-12-19,461.72,469.31,458.5,468.63,6587000 -2006-12-20,470,471.5,462.33,462.9,4367800 -2006-12-21,464.18,465.25,452.34,456.2,6953300 -2006-12-22,457.5,458.64,452.73,455.58,3988300 -2006-12-26,456.52,459.47,454.59,457.53,2074300 -2006-12-27,460,468.08,459.1,468.03,4231500 -2006-12-28,467.12,468.58,462.25,462.56,3116200 -2006-12-29,462.1,464.47,459.86,460.48,2559200 -2007-01-03,466,476.66,461.11,467.59,7706500 -2007-01-04,469,483.95,468.35,483.26,7887600 -2007-01-05,482.5,487.5,478.11,487.19,6872100 -2007-01-08,487.69,489.87,482.2,483.58,4754400 -2007-01-09,485.45,488.25,481.2,485.5,5381400 -2007-01-10,484.43,493.55,482.04,489.46,5968500 -2007-01-11,497.2,501.75,496.18,499.72,7208200 -2007-01-12,501.99,505,500,505,4473700 -2007-01-16,507.55,513,503.3,504.28,7568900 -2007-01-17,503.39,507.77,494.38,497.28,6699100 -2007-01-18,494.52,496.48,487.43,487.83,5932000 -2007-01-19,487.98,490.76,486.74,489.75,4978300 -2007-01-22,492.5,492.65,478.5,480.84,5404300 -2007-01-23,480.79,484.75,477.29,479.05,4665500 -2007-01-24,484.45,499.54,483.29,499.07,6059300 -2007-01-25,501,504.5,485.66,488.09,6368500 -2007-01-26,490.93,497.9,487.03,495.84,5496500 -2007-01-29,498,498.75,490.5,492.47,4775700 -2007-01-30,494,498,491.22,494.32,4180500 -2007-01-31,496.49,505,495.51,501.5,12206100 -2007-02-01,506,506.01,481.53,481.75,15658700 -2007-02-02,482.61,485,477.81,481.5,6286500 -2007-02-05,477.5,478,466.19,467.16,7206900 -2007-02-06,468.1,473.3,467.26,471.48,5321900 -2007-02-07,473.82,474.35,468.78,470.01,4119800 -2007-02-08,468.05,473.75,465.15,471.03,4076700 -2007-02-09,471.65,472.68,461.5,461.89,4858600 -2007-02-12,460.68,462.39,455.02,458.29,5754500 -2007-02-13,459.15,462.78,457.26,459.1,4062600 -2007-02-14,460,469.13,459.22,465.93,5698800 -2007-02-15,466,466.13,460.72,461.47,4042400 -2007-02-16,462.8,470.15,462.06,469.94,6177000 -2007-02-20,468.47,472.75,464.71,472.1,4067600 -2007-02-21,469.84,478.68,467.74,475.86,5640600 -2007-02-22,478.69,484.24,474.39,475.85,5743900 -2007-02-23,475.75,476.95,467.8,470.62,3882600 -2007-02-26,472.83,475.25,463.75,464.93,3969900 -2007-02-27,455,459.8,447.17,448.77,9312800 -2007-02-28,450.41,453.67,443.04,449.45,8032300 -2007-03-01,442.67,452.42,440,448.23,8685200 -2007-03-02,445.11,448.7,438.68,438.68,6583600 -2007-03-05,437.02,445.5,437,440.95,6355100 -2007-03-06,447.47,459,447.38,457.55,7533700 -2007-03-07,462.69,463.14,454.29,455.64,6534100 -2007-03-08,459.22,465.5,454.1,454.72,5362800 -2007-03-09,458,458.4,450.1,452.96,4977700 -2007-03-12,452.57,455.25,451.11,454.75,3465400 -2007-03-13,450.11,451.93,442.83,443.03,6377300 -2007-03-14,443.23,448.66,439,448,8016900 -2007-03-15,447.86,449.82,443.94,446.19,3944200 -2007-03-16,445.65,446.7,439.89,440.85,5659100 -2007-03-19,443.25,448.5,440.63,447.23,5197700 -2007-03-20,445.79,447.6,443.6,445.28,3421500 -2007-03-21,445.3,456.57,445.21,456.55,5798300 -2007-03-22,455.61,462.17,452.53,462.04,5680700 -2007-03-23,461.45,463.39,457.08,461.83,4111300 -2007-03-26,460.55,465,455.62,465,4710300 -2007-03-27,463.55,465.23,460.34,463.62,3741200 -2007-03-28,461.87,465.44,460.15,461.88,4591600 -2007-03-29,464.55,466,455,460.92,3988500 -2007-03-30,462.1,463.4,456.14,458.16,3380200 -2007-04-02,457.76,458.53,452.12,458.53,3448500 -2007-04-03,464.05,474.25,464,472.6,6501800 -2007-04-04,472.14,473,469.58,471.02,3778800 -2007-04-05,471.3,472.09,469.62,471.51,2715800 -2007-04-09,472.98,473,465.59,468.21,3062100 -2007-04-10,467.09,470.79,465.16,466.5,2979300 -2007-04-11,466.06,469.4,462.61,464.53,3812000 -2007-04-12,464,468,462.24,467.39,2707900 -2007-04-13,468.45,468.77,463.36,466.29,2794800 -2007-04-16,468.46,476.99,468.15,474.27,5077900 -2007-04-17,473.8,476.39,471.6,472.8,3210100 -2007-04-18,471.26,479.9,469.53,476.01,5670500 -2007-04-19,474.5,481.95,469.59,471.65,11009600 -2007-04-20,490.52,492.5,482.02,482.48,12161500 -2007-04-23,480.1,485,478.26,479.08,5674600 -2007-04-24,478.61,479.98,475.55,477.53,3694700 -2007-04-25,480,481.37,476.11,477.99,3966800 -2007-04-26,478.1,484.45,477.11,481.18,4124900 -2007-04-27,480.07,482.4,478.33,479.01,2925700 -2007-04-30,479.15,481.35,471.38,471.38,3641200 -2007-05-01,472.19,472.81,464.17,469,3658200 -2007-05-02,468.65,471.08,465.73,465.78,3062700 -2007-05-03,466.22,474.07,465.29,473.23,3594200 -2007-05-04,470.12,474.84,465.88,471.12,3950000 -2007-05-07,472.14,472.82,466.47,467.27,3020100 -2007-05-08,466.13,468.17,464.73,466.81,2905100 -2007-05-09,466.15,471.73,463.88,469.25,3889900 -2007-05-10,467.04,469.49,461.02,461.47,3686300 -2007-05-11,461.83,467,461,466.74,2944100 -2007-05-14,465.48,467.51,460,461.78,3872700 -2007-05-15,461.96,462.54,457.41,458,4119000 -2007-05-16,462,473.14,459.02,472.61,6554200 -2007-05-17,472.46,475.22,470.81,470.96,4660600 -2007-05-18,472.03,472.7,469.75,470.32,3695900 -2007-05-21,469.53,479.2,466.72,470.6,6159300 -2007-05-22,473,479.01,473,475.86,3839000 -2007-05-23,480.82,483.41,473.75,473.97,5060200 -2007-05-24,475.15,479.2,471.5,474.33,4173600 -2007-05-25,479.7,484.95,477.27,483.52,5348500 -2007-05-29,485,491.8,484,487.11,5218000 -2007-05-30,484.5,498.84,483,498.6,7245800 -2007-05-31,500.56,508.78,497.06,497.91,8924300 -2007-06-01,501,505.02,497.93,500.4,4799000 -2007-06-04,497.91,510.51,497.59,507.07,7101000 -2007-06-05,509.75,519,506.61,518.84,10447100 -2007-06-06,516.75,520.78,515.26,518.25,7886700 -2007-06-07,519.75,526.5,512.51,515.06,10630500 -2007-06-08,516.2,519.64,509.46,515.49,6358200 -2007-06-11,514.02,518.25,510,511.34,4647700 -2007-06-12,508.71,511.67,503.17,504.77,6419500 -2007-06-13,507.09,508.54,498.69,505.24,7034000 -2007-06-14,505.38,505.88,501.7,502.84,4621200 -2007-06-15,508.19,509,501.23,505.89,6174100 -2007-06-18,506.18,516,504.24,515.2,4835900 -2007-06-19,514.01,517.25,511.54,514.31,4355300 -2007-06-20,516.96,518.75,509.06,509.97,4338200 -2007-06-21,510.98,515.29,506.28,514.11,4409700 -2007-06-22,516.42,524.99,516.1,524.98,7203700 -2007-06-25,528.98,534.99,523.38,527.42,7925000 -2007-06-26,532.73,533.2,526.24,530.26,5689500 -2007-06-27,525,527.99,519.56,526.29,6123100 -2007-06-28,524.88,529.5,523.8,525.01,4168400 -2007-06-29,526.02,527.4,519.46,522.7,3880600 -2007-07-02,525.49,531.85,524.2,530.38,3487600 -2007-07-03,531.06,534.4,527.5,534.34,1871800 -2007-07-05,535.56,544.4,532.15,541.63,4942900 -2007-07-06,541.25,543.87,538.73,539.4,2747000 -2007-07-09,543,548.74,540.26,542.56,3729800 -2007-07-10,543.79,547,541.65,543.34,3856000 -2007-07-11,543.61,546.5,540.01,544.47,3309300 -2007-07-12,545.86,547.32,540.22,545.33,3441600 -2007-07-13,547.91,552.67,547.25,552.16,5237100 -2007-07-16,550.3,558.58,549.31,552.99,6599500 -2007-07-17,555.04,557.73,552.38,555,4328600 -2007-07-18,553.89,554.5,543.81,549.5,6080000 -2007-07-19,553.46,553.52,542.24,548.59,11127200 -2007-07-20,511.9,523.18,509.5,520.12,17772300 -2007-07-23,519.01,520,512.15,512.51,6356700 -2007-07-24,509.3,518.69,507.11,514,5572100 -2007-07-25,516.98,517.02,505.56,509.76,5545000 -2007-07-26,508.74,512.59,498.88,508,6883400 -2007-07-27,508.53,516.62,505.5,511.89,5509100 -2007-07-30,512.92,519.34,510.5,516.11,3963300 -2007-07-31,520.23,520.44,510,510,4270500 -2007-08-01,510.5,516.51,508.14,512.94,4421500 -2007-08-02,513.72,514.99,509,511.01,3154900 -2007-08-03,510.05,513.2,503,503,3176200 -2007-08-06,503,510.15,502.5,510,3651500 -2007-08-07,509.75,519.88,509.04,516.02,4264300 -2007-08-08,519.34,525.78,517.09,525.78,4068800 -2007-08-09,520.8,526.82,514.63,514.73,4846500 -2007-08-10,510.18,518.72,505.63,515.75,5875200 -2007-08-13,519.54,519.75,513.03,515.5,3179300 -2007-08-14,515.72,517.4,508,508.6,3633700 -2007-08-15,509,511.69,496.71,497.55,5409500 -2007-08-16,492.02,496.43,480.46,491.52,8645600 -2007-08-17,497.44,501,491.65,500.04,5479400 -2007-08-20,502.46,502.56,496,497.92,2697300 -2007-08-21,498.94,508.16,497.77,506.61,3610600 -2007-08-22,509.96,516.25,509.25,512.75,3252700 -2007-08-23,516,516.13,507,512.19,3076700 -2007-08-24,512.61,515.55,508.5,515,2472700 -2007-08-27,514.43,517.45,511.4,513.26,2325100 -2007-08-28,511.53,514.98,505.79,506.4,3273900 -2007-08-29,507.84,513.3,507.23,512.88,2549300 -2007-08-30,512.36,515.4,510.58,511.4,2651700 -2007-08-31,513.1,516.5,511.47,515.25,2977600 -2007-09-04,515.02,528,514.62,525.15,3693700 -2007-09-05,523.4,529.48,522.25,527.8,3312900 -2007-09-06,529.36,529.83,518.24,523.52,3625900 -2007-09-07,517.86,521.24,516.8,519.35,3663600 -2007-09-10,521.28,522.07,510.88,514.48,3225800 -2007-09-11,516.99,521.65,515.73,521.33,2703600 -2007-09-12,520.53,527.98,519,522.65,2986000 -2007-09-13,524.06,527.21,523.22,524.78,1891100 -2007-09-14,523.2,530.27,522.22,528.75,2764900 -2007-09-17,526.53,529.28,524.07,525.3,2197500 -2007-09-18,526.52,537.25,524.27,535.27,4215700 -2007-09-19,539.27,549.45,538.86,546.85,5526900 -2007-09-20,547,556.8,546.03,552.83,5525000 -2007-09-21,556.34,560.79,552.83,560.1,8011700 -2007-09-24,561,571.46,560,568.02,5297000 -2007-09-25,564,569.56,562.86,569,2730600 -2007-09-26,570.4,571.79,563.81,568.16,3346100 -2007-09-27,571.73,571.74,565.78,567.5,2056300 -2007-09-28,567,569.55,564.12,567.27,2639500 -2007-10-01,569.97,584.35,569.61,582.55,4711300 -2007-10-02,583.38,596.81,580.01,584.39,7067500 -2007-10-03,586.25,588.99,580.36,584.02,3879500 -2007-10-04,585.09,585.09,577.06,579.03,2986700 -2007-10-05,587.11,596,587.01,594.05,5068700 -2007-10-08,595,610.26,593.95,609.62,5028000 -2007-10-09,615.11,623.78,608.39,615.18,8767800 -2007-10-10,621.36,625.68,616.8,625.39,5385600 -2007-10-11,633.64,641.41,609,622,11799000 -2007-10-12,623.98,638.4,618.24,637.39,6823700 -2007-10-15,638.47,639.86,615.55,620.11,6943800 -2007-10-16,618.49,625.92,611.99,616,6025300 -2007-10-17,630.45,634,621.59,633.48,6030500 -2007-10-18,635.41,641.37,628.5,639.62,12289200 -2007-10-19,654.56,658.49,643.23,644.71,15789000 -2007-10-22,638.67,655,636.28,650.75,6664400 -2007-10-23,661.25,677.6,660,675.77,6793700 -2007-10-24,672.71,677.47,659.56,675.82,7404200 -2007-10-25,678.68,678.97,663.55,668.51,5795500 -2007-10-26,674.03,676.54,668.06,674.6,3353900 -2007-10-29,677.77,680,672.09,679.23,3066300 -2007-10-30,677.51,699.91,677.51,694.77,6900600 -2007-10-31,700.69,707,696.04,707,6876800 -2007-11-01,702.79,713.72,701.78,703.21,6527200 -2007-11-02,710.51,713.58,697.34,711.25,5841500 -2007-11-05,706.99,730.23,706.07,725.65,8883700 -2007-11-06,737.56,741.79,725,741.79,8436300 -2007-11-07,741.13,747.24,723.14,732.94,8252900 -2007-11-08,734.6,734.89,677.18,693.84,16512200 -2007-11-09,675.78,681.88,661.21,663.97,11388100 -2007-11-12,657.74,669.93,626.21,632.07,10227300 -2007-11-13,644.99,660.92,632.07,660.55,8426100 -2007-11-14,673.28,675.49,636.27,641.68,8094700 -2007-11-15,638.57,647.5,624,629.65,6967700 -2007-11-16,633.94,635.49,616.02,633.63,9042800 -2007-11-19,629.59,636.77,618.5,625.85,5527400 -2007-11-20,636.48,659.1,632.87,648.54,9840600 -2007-11-21,643.77,669.97,642.08,660.52,7013500 -2007-11-23,670,678.28,668.11,676.7,2738700 -2007-11-26,680.2,693.4,665,666,6790100 -2007-11-27,674.8,676.43,650.26,673.57,8904500 -2007-11-28,682.11,694.3,672.14,692.26,7916500 -2007-11-29,690.75,702.79,687.77,697,6208000 -2007-11-30,711,711.06,682.11,693,7895500 -2007-12-03,691.01,695,681.14,681.53,4325100 -2007-12-04,678.31,692,677.12,684.16,4231800 -2007-12-05,692.73,698.93,687.5,698.51,4209600 -2007-12-06,697.8,716.56,697.01,715.26,4909000 -2007-12-07,714.99,718,710.5,714.87,3852100 -2007-12-10,715.99,724.8,714,718.42,3856200 -2007-12-11,719.94,720.99,698.78,699.2,6139100 -2007-12-12,714,714.32,688.5,699.35,6159100 -2007-12-13,696.31,697.62,681.21,694.05,5040800 -2007-12-14,687.51,699.7,687.26,689.96,3673500 -2007-12-17,688,695.42,663.67,669.23,5486000 -2007-12-18,674.16,676.71,652.5,673.35,7166700 -2007-12-19,674.21,679.5,669,677.37,4421100 -2007-12-20,685.83,691,680.61,689.69,4422200 -2007-12-21,697.88,699.26,693.24,696.69,5382000 -2007-12-24,694.99,700.73,693.06,700.73,1628400 -2007-12-26,698.99,713.22,698.21,710.84,2530000 -2007-12-27,707.07,716,700.74,700.74,2942500 -2007-12-28,704.93,707.95,696.54,702.53,2562700 -2007-12-31,698.57,702.49,690.58,691.48,2376200 -2008-01-02,692.87,697.37,677.73,685.19,4306900 -2008-01-03,685.26,686.85,676.52,685.33,3252500 -2008-01-04,679.69,680.96,655,657,5359800 -2008-01-07,653.94,662.28,637.35,649.25,6403400 -2008-01-08,653,659.96,631,631.68,5339100 -2008-01-09,630.04,653.34,622.51,653.2,6739700 -2008-01-10,645.01,657.2,640.11,646.73,6334200 -2008-01-11,642.7,649.47,630.11,638.25,4977000 -2008-01-14,651.14,657.4,645.25,653.82,4447500 -2008-01-15,645.9,649.05,635.38,637.65,5568200 -2008-01-16,628.97,639.99,601.93,615.95,10560000 -2008-01-17,620.76,625.74,598.01,600.79,8216800 -2008-01-18,608.36,609.99,598.45,600.25,8539600 -2008-01-22,562.03,597.5,561.2,584.35,9501500 -2008-01-23,560.71,568,519,548.62,16965700 -2008-01-24,558.8,579.69,554.14,574.49,9400900 -2008-01-25,591.81,595,566.18,566.4,6966000 -2008-01-28,570.97,572.24,548.6,555.98,5816700 -2008-01-29,560.47,561.33,540.67,550.52,6283000 -2008-01-30,549.19,560.43,543.51,548.27,7939600 -2008-01-31,539.01,573,534.29,564.3,14871300 -2008-02-01,528.67,536.67,510,515.9,17600500 -2008-02-04,509.07,512.78,492.55,495.43,13157100 -2008-02-05,489.43,509,488.52,506.8,11203300 -2008-02-06,511.14,511.17,497.93,501.71,7636400 -2008-02-07,496.86,514.19,494.76,504.95,7928900 -2008-02-08,509.41,517.73,508.7,516.69,6828900 -2008-02-11,520.52,523.71,513.4,521.16,5826000 -2008-02-12,523.39,530.6,513.03,518.09,6662300 -2008-02-13,522.5,534.99,518.69,534.62,6624700 -2008-02-14,538.35,541.04,531,532.25,6476700 -2008-02-15,528.31,532.66,524.33,529.64,5240100 -2008-02-19,534.94,535.06,506.5,508.95,6350400 -2008-02-20,503.51,511.01,498.82,509,6662200 -2008-02-21,512.85,513.21,499.5,502.86,5677800 -2008-02-22,502.06,509,497.55,507.8,5515900 -2008-02-25,505.95,506.5,485.74,486.44,8372800 -2008-02-26,461.2,466.47,446.85,464.19,23287300 -2008-02-27,460.13,475.49,459.64,472.86,10121900 -2008-02-28,470.5,479.09,467.36,475.39,6586900 -2008-02-29,471.87,479.74,464.65,471.18,9425400 -2008-03-03,471.51,472.72,450.11,457.02,7554500 -2008-03-04,450.95,453.36,435.78,444.6,13621700 -2008-03-05,445.25,454.17,444,447.7,7436600 -2008-03-06,447.69,453.3,431.18,432.7,7470100 -2008-03-07,428.88,440,426.24,433.35,8071800 -2008-03-10,428.83,431,413.04,413.62,7987600 -2008-03-11,425.26,440.15,424.65,439.84,8826900 -2008-03-12,440.01,447.88,438.07,440.18,6651900 -2008-03-13,432.67,446.98,428.78,443.01,7726600 -2008-03-14,442.98,449.34,430.62,437.92,6574400 -2008-03-17,427.99,433.71,412.11,419.87,7888200 -2008-03-18,428.98,440.84,425.53,439.16,7237200 -2008-03-19,441.11,447.5,431.67,432,6179000 -2008-03-20,427.32,435.7,417.5,433.55,9913400 -2008-03-24,438.43,465.78,437.72,460.56,6763500 -2008-03-25,457.46,457.47,446,450.78,5831600 -2008-03-26,452.59,462.87,449.29,458.19,5225700 -2008-03-27,446,448.61,440.49,444.08,5832200 -2008-03-28,447.46,453.57,434.31,438.08,4376200 -2008-03-31,435.64,442.69,432.01,440.47,4446400 -2008-04-01,447.74,466.5,446.87,465.71,6093100 -2008-04-02,469.9,475.74,460.39,465.7,5999000 -2008-04-03,461.73,463.29,448.13,455.12,6778400 -2008-04-04,457.01,477.83,456.2,471.09,5897200 -2008-04-07,477.03,485.44,473.53,476.82,5943500 -2008-04-08,473.04,474.14,462.01,467.81,4547000 -2008-04-09,469.13,472,457.54,464.19,6048100 -2008-04-10,464.96,473.86,461.85,469.08,5072400 -2008-04-11,464.07,467.26,455.01,457.45,4169700 -2008-04-14,457.16,457.45,450.15,451.66,3842600 -2008-04-15,458.13,459.72,443.72,446.84,4577600 -2008-04-16,444.4,458.28,441,455.03,7630700 -2008-04-17,455.63,459.37,446.52,449.54,13353000 -2008-04-18,535.21,547.7,524.77,539.41,18235600 -2008-04-21,539.39,542.59,530.29,537.79,7439700 -2008-04-22,537.57,560.83,537.56,555,7938500 -2008-04-23,557.94,559.31,540.95,546.49,4921500 -2008-04-24,551.29,554.49,540.02,543.04,4135100 -2008-04-25,549.02,553,542.73,544.06,4164400 -2008-04-28,545.88,556.81,539,552.12,4008600 -2008-04-29,550.83,563.4,550.01,558.47,4346000 -2008-04-30,562.21,584.86,558.47,574.29,7903000 -2008-05-01,578.31,594.93,576.97,593.08,6602800 -2008-05-02,598.49,602.45,579.3,581.29,6998800 -2008-05-05,598.86,599,587.13,594.9,6281000 -2008-05-06,591,592,583,586.36,4629300 -2008-05-07,590.27,599.49,576.43,579,6613000 -2008-05-08,586.2,589.3,578.91,583.01,5122900 -2008-05-09,579,585,571.3,573.2,4484900 -2008-05-12,574.75,586.75,568.91,584.94,4863900 -2008-05-13,586.23,587.95,578.55,583,5163500 -2008-05-14,586.49,591.19,575.25,576.3,4375800 -2008-05-15,579,582.95,575.61,581,4342700 -2008-05-16,581.43,584.68,578.32,580.07,4274100 -2008-05-19,578.55,588.88,573.52,577.52,5604500 -2008-05-20,574.63,582.48,572.91,578.6,3313600 -2008-05-21,578.52,581.41,547.89,549.99,6468100 -2008-05-22,551.95,554.21,540.25,549.46,5076300 -2008-05-23,546.96,553,537.81,544.62,4431500 -2008-05-27,544.96,562.6,543.85,560.9,3865500 -2008-05-28,567.94,571.49,561.1,568.24,4050400 -2008-05-29,574.79,585.88,573.2,583,4845000 -2008-05-30,583.47,589.92,581.3,585.8,3225200 -2008-06-02,582.5,583.89,571.27,575,3674200 -2008-06-03,576.5,580.5,560.61,567.3,4305300 -2008-06-04,565.33,578,564.55,572.22,3363200 -2008-06-05,577.08,588.04,576.21,586.3,3916700 -2008-06-06,579.75,580.72,567,567,4734500 -2008-06-09,568.06,570,545.4,557.87,5288300 -2008-06-10,549.56,558.82,546.78,554.17,3657400 -2008-06-11,556.24,557.34,544.46,545.2,3812900 -2008-06-12,548.76,558,546.88,552.95,5491600 -2008-06-13,561.49,575.7,561.34,571.51,6184400 -2008-06-16,566.5,579.1,566.5,572.81,3542800 -2008-06-17,576.35,578.07,568.38,569.46,3462900 -2008-06-18,564.51,568.99,559.16,562.38,3381200 -2008-06-19,555.35,563.78,550.81,560.2,5683100 -2008-06-20,556.98,556.98,544.51,546.43,5983100 -2008-06-23,545.36,553.15,542.02,545.21,3635900 -2008-06-24,545.14,551.19,535.1,542.3,4672600 -2008-06-25,544.97,557.8,543.67,551,4122200 -2008-06-26,544.1,544.93,528.26,528.82,5659500 -2008-06-27,527.68,530,515.09,528.07,5447500 -2008-06-30,532.47,538,523.06,526.42,3765300 -2008-07-01,519.58,536.72,517,534.73,4959900 -2008-07-02,536.51,540.38,526.06,527.04,4223000 -2008-07-03,530.88,539.23,527.5,537,2400500 -2008-07-07,542.3,549,535.6,543.91,4255200 -2008-07-08,545.99,555.19,540,554.53,4932400 -2008-07-09,550.76,555.68,540.73,541.55,4154000 -2008-07-10,545,549.5,530.72,540.57,4331700 -2008-07-11,536.5,539.5,519.43,533.8,4981400 -2008-07-14,539,540.06,515.45,521.62,4424800 -2008-07-15,516.28,527.5,501.1,516.09,6071000 -2008-07-16,514.04,536.5,510.6,535.6,4742200 -2008-07-17,534.16,537.05,524.5,533.44,8787400 -2008-07-18,498.35,498.98,478.19,481.32,11292400 -2008-07-21,480.88,484.09,465.7,468.8,5901500 -2008-07-22,466.72,480.25,465.6,477.11,4691500 -2008-07-23,481.61,497.23,478.1,489.22,4894100 -2008-07-24,496.7,496.87,475.62,475.62,3540900 -2008-07-25,486.49,493.13,481.5,491.98,3183500 -2008-07-28,492.09,492.09,475.13,477.12,3160000 -2008-07-29,479.3,487.26,478,483.11,2802800 -2008-07-30,485.5,486.02,472.81,482.7,3490700 -2008-07-31,474.56,480.89,471.44,473.75,2865100 -2008-08-01,472.51,473.22,462.5,467.86,3007900 -2008-08-04,468.12,473.01,461.9,463,2487000 -2008-08-05,467.59,480.08,466.33,479.85,3584500 -2008-08-06,478.37,489.77,472.51,486.34,3375800 -2008-08-07,482,484,476.41,479.12,2773800 -2008-08-08,480.15,495.75,475.69,495.01,3739300 -2008-08-11,492.47,508.88,491.78,500.84,4239300 -2008-08-12,502,506.13,498,502.61,2755700 -2008-08-13,501.6,503.54,493.88,500.03,3625500 -2008-08-14,497.7,507.61,496.29,505.49,2918600 -2008-08-15,506.99,510.66,505.5,510.15,3545700 -2008-08-18,509.84,510,495.51,498.3,3333900 -2008-08-19,490.43,498.28,486.63,490.5,3046500 -2008-08-20,494.72,496.69,482.57,485,3982100 -2008-08-21,482.92,489.9,479.27,486.53,3514100 -2008-08-22,491.5,494.88,489.48,490.59,2297200 -2008-08-25,486.11,497,481.5,483.01,2014300 -2008-08-26,483.46,483.46,470.59,474.16,3308200 -2008-08-27,473.73,474.83,464.84,468.58,4387100 -2008-08-28,472.49,476.45,470.33,473.78,3029700 -2008-08-29,469.75,471.01,462.33,463.29,3848200 -2008-09-02,476.77,482.18,461.42,465.25,6111500 -2008-09-03,468.73,474.29,459.58,464.41,4314600 -2008-09-04,460,463.24,449.4,450.26,4848500 -2008-09-05,445.49,452.46,440.08,444.25,4534300 -2008-09-08,452.02,452.94,417.55,419.95,9017900 -2008-09-09,423.17,432.38,415,418.66,7229600 -2008-09-10,424.47,424.48,409.68,414.16,6226800 -2008-09-11,408.35,435.09,406.38,433.75,6471400 -2008-09-12,430.21,441.99,429,437.66,6028000 -2008-09-15,424,441.97,423.71,433.86,6567400 -2008-09-16,425.96,449.28,425.49,442.93,6990700 -2008-09-17,438.48,439.14,413.44,414.49,9126900 -2008-09-18,422.64,439.18,410.5,439.08,8589400 -2008-09-19,461,462.07,443.28,449.15,10006000 -2008-09-22,454.13,454.13,429,430.14,4407300 -2008-09-23,433.25,440.79,425.72,429.27,5204200 -2008-09-24,430.34,445,430.11,435.11,4242000 -2008-09-25,438.84,450,435.98,439.6,5020300 -2008-09-26,428,437.16,421.03,431.04,5292500 -2008-09-29,419.51,423.51,380.71,381,10762900 -2008-09-30,395.98,425.08,392.32,400.52,3086300 -2008-10-01,411.15,416.98,403.1,411.72,6234800 -2008-10-02,409.79,409.98,386,390.49,5984900 -2008-10-03,397.35,412.5,383.07,386.91,7992900 -2008-10-06,373.98,375.99,357.16,371.21,11220600 -2008-10-07,373.33,374.98,345.37,346.01,11054400 -2008-10-08,330.16,358.99,326.11,338.11,11826400 -2008-10-09,344.52,348.57,321.67,328.98,8075000 -2008-10-10,313.16,341.89,310.3,332,10597800 -2008-10-13,355.79,381.95,345.75,381.02,8905500 -2008-10-14,393.53,394.5,357,362.71,7784800 -2008-10-15,354.65,359,338.83,339.17,6721400 -2008-10-16,332.76,356.5,309.44,353.02,16239700 -2008-10-17,378.96,386,363.55,372.54,14249200 -2008-10-20,379.75,380.98,359.59,379.32,6753400 -2008-10-21,372.39,383.78,362,362.75,5782000 -2008-10-22,356.99,369.69,344,355.67,6560000 -2008-10-23,353.65,358,337.99,352.32,6478900 -2008-10-24,326.47,350.47,324.74,339.29,7359000 -2008-10-27,334.81,343,325.6,329.49,6200700 -2008-10-28,339.05,369.31,328.51,368.75,8105400 -2008-10-29,365.79,371,352.37,358,9756600 -2008-10-30,368.46,372,358.37,359.69,7988900 -2008-10-31,356.16,371.96,354.27,359.36,7423300 -2008-11-03,357.58,362.99,341.43,346.49,5954500 -2008-11-04,353.44,372.36,345.5,366.94,7349900 -2008-11-05,362.15,368.88,341.31,342.24,6946500 -2008-11-06,339.97,344.42,325.81,331.22,8574800 -2008-11-07,333.12,341.15,325.33,331.14,4681300 -2008-11-10,328,329.44,309.47,318.78,8080100 -2008-11-11,308.69,316.3,300.52,311.46,10146600 -2008-11-12,302.05,312.49,287.76,291,10051100 -2008-11-13,291.77,313,280,312.08,13234700 -2008-11-14,303.25,324.99,302.56,310.02,9517100 -2008-11-17,303,310.16,297.95,300.12,7543800 -2008-11-18,301.57,303.73,285.35,297.42,8346100 -2008-11-19,295.39,300.19,278.58,280.18,7834600 -2008-11-20,274.89,282.94,259.04,259.56,9779400 -2008-11-21,262.51,269.37,247.3,262.43,10244500 -2008-11-24,269.26,269.95,249.01,257.44,10054700 -2008-11-25,268.68,286.66,267.32,282.05,10771200 -2008-11-26,280.28,295.46,276.2,292.09,6356600 -2008-11-28,290.58,296.45,288.28,292.96,2565500 -2008-12-01,286.68,287.38,265.98,265.99,5711200 -2008-12-02,269.73,277.78,262.58,275.11,5839700 -2008-12-03,269.85,281.36,265.34,279.43,5904800 -2008-12-04,276.53,283.49,268.77,274.34,4886600 -2008-12-05,271.02,284.24,264.02,283.99,6521200 -2008-12-08,289.99,309.44,282,302.11,8144300 -2008-12-09,297.69,318,297.01,305.97,6889900 -2008-12-10,309.24,314.9,304.51,308.82,5237000 -2008-12-11,304.17,312.88,297.8,300.22,6179200 -2008-12-12,295.71,316.47,294,315.76,5722100 -2008-12-15,314.01,318.49,305.11,310.67,6737900 -2008-12-16,314.52,329.5,311.27,325.28,7059600 -2008-12-17,318.64,322.13,312.42,315.24,5789700 -2008-12-18,316.7,320.35,309.11,310.28,4763500 -2008-12-19,310.99,317.79,309,310.17,5612600 -2008-12-22,308.56,309.5,290.63,297.11,3917600 -2008-12-23,300.43,303.31,296.67,298.02,3777700 -2008-12-24,301.48,306.34,298.38,302.95,1921500 -2008-12-26,304.07,305.26,298.31,300.36,1959100 -2008-12-29,300.22,301.38,291.58,297.42,3701900 -2008-12-30,300.8,306.81,298.71,303.11,3843500 -2008-12-31,304.2,311,302.61,307.65,2886800 -2009-01-02,308.6,321.82,305.5,321.32,3610500 -2009-01-05,321,331.24,315,328.05,4889000 -2009-01-06,332.98,340.8,326.39,334.06,6425200 -2009-01-07,328.32,330.91,318.75,322.01,4494500 -2009-01-08,318.28,325.19,317.34,325.19,3600700 -2009-01-09,327.5,327.5,313.4,315.07,4340500 -2009-01-12,316.31,318.95,310.23,312.69,3304300 -2009-01-13,311.77,320.6,310.39,314.32,4432500 -2009-01-14,310,313.8,297.75,300.97,5467900 -2009-01-15,297.57,303.58,286.79,298.99,5934500 -2009-01-16,305.02,308.25,295.7,299.67,5224400 -2009-01-20,299.14,299.5,282.75,282.75,5048200 -2009-01-21,288.35,303.5,288.35,303.08,4924500 -2009-01-22,298.04,309.35,295.15,306.5,8267000 -2009-01-23,309.27,331.96,304.22,324.7,10732800 -2009-01-26,324.85,328,320.56,323.87,4610700 -2009-01-27,326.45,333.87,324.27,331.48,4927300 -2009-01-28,337.98,352.33,336.31,348.67,7691400 -2009-01-29,344.54,345.05,340.11,343.32,7283800 -2009-01-30,344.69,348.8,336,338.53,4672000 -2009-02-02,334.29,345,332,340.57,5206900 -2009-02-03,342.57,343,333.83,340.45,6556500 -2009-02-04,340.07,354.44,339.17,343,6817400 -2009-02-05,340.91,355.38,337,353.72,7264400 -2009-02-06,356.46,373.81,355.44,371.28,7038100 -2009-02-09,371.28,381,367.3,378.77,4977300 -2009-02-10,375.98,377.5,357.89,358.51,7103700 -2009-02-11,358.95,365,353,358.04,5231600 -2009-02-12,353.16,363.62,351.48,363.05,5550300 -2009-02-13,362.19,362.99,355.23,357.68,4146700 -2009-02-17,346.51,347.09,339.69,342.66,5680400 -2009-02-18,347.24,353.38,340.52,353.11,6024500 -2009-02-19,357.47,359.8,341.41,342.64,4988700 -2009-02-20,338.05,348.92,335,346.45,6217100 -2009-02-23,347,349.8,329.55,330.06,5221100 -2009-02-24,331.02,349.62,330.89,345.45,6095900 -2009-02-25,342.15,352.3,338.92,341.64,6439100 -2009-02-26,345.96,352.49,337.16,337.18,5605600 -2009-02-27,332.95,343.82,331.11,337.99,5420000 -2009-03-02,333.33,340.7,326,327.16,5788500 -2009-03-03,330.07,333.69,322.35,325.48,6524800 -2009-03-04,323.16,329,315.38,318.92,7818400 -2009-03-05,316.48,319.08,302.64,305.64,6529900 -2009-03-06,307.22,310.19,294.25,308.57,7234200 -2009-03-09,299.98,306.57,289.45,290.89,6471300 -2009-03-10,298.25,310.5,294.25,308.17,6730200 -2009-03-11,310.1,320,305.71,317.91,5923600 -2009-03-12,317.54,325,313.65,323.53,5024100 -2009-03-13,326.1,327.46,319.03,324.42,3906400 -2009-03-16,325.99,329.73,318.59,319.69,4946800 -2009-03-17,320.18,335.34,319.09,335.34,4712500 -2009-03-18,334.81,340,328.05,333.1,5012200 -2009-03-19,331.68,336,327.38,329.94,4111200 -2009-03-20,330.3,332.99,326.34,330.16,4737900 -2009-03-23,333.56,349.45,333.03,348.6,4271500 -2009-03-24,346.5,353.84,344,347.17,3820000 -2009-03-25,350.4,351.34,336.25,344.07,4336300 -2009-03-26,353.13,359.16,348.5,353.29,6003300 -2009-03-27,350,352,345.47,347.7,3322800 -2009-03-30,342.55,343.81,336.05,342.69,3094100 -2009-03-31,348.93,353.51,346.18,348.06,3655300 -2009-04-01,343.78,355.24,340.61,354.09,3301200 -2009-04-02,363.31,369.76,360.32,362.5,4488000 -2009-04-03,364.5,371.72,358,369.78,3789800 -2009-04-06,367,369.82,361.4,368.24,3280300 -2009-04-07,362.6,363.75,355.31,358.65,3680100 -2009-04-08,363.5,365,356.21,362,2765200 -2009-04-09,369.5,374.35,366.25,372.5,3382600 -2009-04-13,371.33,379.1,370.3,378.11,3050100 -2009-04-14,376.94,376.99,365.6,368.91,3428600 -2009-04-15,367.1,381.06,364.16,379.5,4930700 -2009-04-16,381.5,392.9,381.02,388.74,10185100 -2009-04-17,386.02,399.82,384.81,392.24,10730800 -2009-04-20,386.15,390.65,375.89,379.3,4428900 -2009-04-21,376.17,384.3,376.1,381.47,3695400 -2009-04-22,381.75,390,379.01,383.86,3501800 -2009-04-23,387.51,389.75,381.11,384.69,2609000 -2009-04-24,386.05,393.18,380.5,389.49,3385400 -2009-04-27,384.34,389.49,382.75,385.95,2290600 -2009-04-28,383.75,389.05,381.54,383.71,2943600 -2009-04-29,385.97,394.97,385.83,391.47,3610000 -2009-04-30,395.76,403.75,394.8,395.97,4355700 -2009-05-01,395.03,397.59,391.55,393.69,2427700 -2009-05-04,398.17,402.4,394.79,401.98,3203000 -2009-05-05,399.98,405,397.25,402.99,2400800 -2009-05-06,406.79,408.28,401,403.47,2632900 -2009-05-07,404.1,404.99,392.5,396.61,2999800 -2009-05-08,402.85,410.13,395,407.33,3865100 -2009-05-11,402.8,412,401.2,407.98,2559300 -2009-05-12,410.01,410.99,395.11,399.01,3790800 -2009-05-13,394.09,396.39,388.35,389.54,2842800 -2009-05-14,388.8,392.21,384.69,387.5,2937000 -2009-05-15,391.1,394.11,389.09,390,3008700 -2009-05-18,394.73,397.31,385.4,396.84,3351700 -2009-05-19,396.1,401.64,393,398.88,2837500 -2009-05-20,402.09,405.67,395,397.18,2284000 -2009-05-21,396.3,402.84,393.84,396.5,2719800 -2009-05-22,396.66,398.65,392,393.5,1718600 -2009-05-26,391.95,405,390,404.36,3104500 -2009-05-27,405.64,411.86,404.81,405.56,3034300 -2009-05-28,408.68,411.62,404.61,410.4,2668800 -2009-05-29,412.11,417.23,410.7,417.23,2648200 -2009-06-01,418.73,429.6,418.53,426.56,3322400 -2009-06-02,426.25,429.96,423.4,428.4,2623600 -2009-06-03,426,432.46,424,431.65,3532800 -2009-06-04,435.3,441.24,434.5,440.28,3638100 -2009-06-05,445.07,447.34,439.46,444.32,3680800 -2009-06-08,439.5,440.92,434.12,438.77,3098700 -2009-06-09,438.58,440.5,431.76,435.62,3254900 -2009-06-10,436.23,437.89,426.67,432.6,3358900 -2009-06-11,431.77,433.73,428.37,429,2865200 -2009-06-12,426.86,427.7,421.21,424.84,2918400 -2009-06-15,421.5,421.5,414,416.77,3736900 -2009-06-16,419.31,421.09,415.42,416,3049700 -2009-06-17,416.19,419.72,411.56,415.16,3490100 -2009-06-18,415.68,418.69,413,414.06,3085200 -2009-06-19,418.21,420.46,414.58,420.09,4259100 -2009-06-22,416.95,417.49,401.89,407.35,4124400 -2009-06-23,406.65,408.99,402.55,405.68,2899600 -2009-06-24,408.74,412.23,406.56,409.29,2457800 -2009-06-25,407,415.9,406.51,415.77,3044500 -2009-06-26,413.68,428.23,413.11,425.32,3256700 -2009-06-29,426,427.8,422.24,424.14,2169300 -2009-06-30,424,427.21,418.22,421.59,2593900 -2009-07-01,424.2,426.4,418.15,418.99,2310800 -2009-07-02,415.41,415.41,406.81,408.49,2517600 -2009-07-06,406.5,410.64,401.66,409.61,2262600 -2009-07-07,408.24,409.19,395.98,396.63,3259300 -2009-07-08,400,406,398.06,402.49,3441200 -2009-07-09,406.12,414.45,405.8,410.39,3275600 -2009-07-10,409.58,417.37,408.7,414.4,2926600 -2009-07-13,416.17,424.52,415.18,424.3,4045700 -2009-07-14,423.71,426.73,420.87,424.69,2895800 -2009-07-15,429.66,438.68,428.49,438.17,3777000 -2009-07-16,436.68,445.75,434.1,442.6,6554500 -2009-07-17,433,435.48,426.7,430.25,6854100 -2009-07-20,429.88,432.85,426.25,430.17,3153500 -2009-07-21,430.94,431.9,425.72,427.9,2968200 -2009-07-22,428,430.2,423.5,427.69,2586700 -2009-07-23,428.68,441.21,425.5,437.34,3478200 -2009-07-24,435.81,450.49,435,446.72,3626900 -2009-07-27,446.04,446.75,437.61,444.8,2504400 -2009-07-28,441,442.81,436.1,439.85,2532500 -2009-07-29,437.23,437.8,431.89,436.24,1987000 -2009-07-30,442.61,451.47,442.61,445.64,3198600 -2009-07-31,449.98,452.7,442.43,443.05,2860400 -2009-08-03,448.74,453.9,447.64,452.21,2590300 -2009-08-04,449.37,454,448.43,453.73,2389800 -2009-08-05,456,456.91,447.88,451.14,2342000 -2009-08-06,454.3,454.88,448.53,450.36,2110900 -2009-08-07,455.67,459.42,454.99,457.1,2543100 -2009-08-10,455.14,458.41,453.79,456.61,1742000 -2009-08-11,453.67,457.23,452.38,453.94,1712500 -2009-08-12,455.41,461.75,454.92,458.58,2341400 -2009-08-13,462.15,464.72,458.91,462.28,1995200 -2009-08-14,462.78,463.18,456.89,460,1675100 -2009-08-17,451.5,451.99,443.12,444.89,2620200 -2009-08-18,445.1,447.7,442.32,445.28,2351100 -2009-08-19,439.99,445,438.56,443.97,2255000 -2009-08-20,452,462.18,451.23,460.41,3998900 -2009-08-21,465.54,466.09,462.65,465.24,3560500 -2009-08-24,467.35,470.09,464.42,468.73,2453400 -2009-08-25,469.13,474.35,468.72,471.37,2341000 -2009-08-26,472.76,473,466.7,468,1987800 -2009-08-27,468.58,468.58,460.73,466.06,1998900 -2009-08-28,469.26,472.37,463.38,464.75,1771600 -2009-08-31,459.79,461.86,458,461.67,1957900 -2009-09-01,459.68,466.82,454.42,455.76,2594900 -2009-09-02,455.82,458.33,452.59,453.01,1804800 -2009-09-03,455.82,458.25,455,457.52,1646200 -2009-09-04,457.57,462.6,455.78,461.3,1499200 -2009-09-08,464.29,466.99,455.84,458.62,2656700 -2009-09-09,459.06,466.27,458.8,463.97,2195400 -2009-09-10,466.65,470.94,462,470.94,2534600 -2009-09-11,470.4,473.3,467.63,472.14,1902900 -2009-09-14,470.51,476.8,470.05,475.12,1975700 -2009-09-15,475.08,478.91,472.71,477.54,2398100 -2009-09-16,479.8,489.37,478.48,488.29,2585300 -2009-09-17,490.57,497.37,487.15,491.72,4483100 -2009-09-18,496.77,496.98,491.23,491.46,3283500 -2009-09-21,487.74,498.9,486.22,497,2116400 -2009-09-22,500.92,501.99,497.81,499.06,3041200 -2009-09-23,500.78,507,497.71,498.46,2704200 -2009-09-24,500.47,501.41,493,496.77,2527600 -2009-09-25,494.29,499.93,492,492.48,2049600 -2009-09-28,494.84,501.5,493.3,498.53,1839300 -2009-09-29,499.53,499.75,493.01,498.53,2099200 -2009-09-30,500,500.14,487.24,495.85,3141700 -2009-10-01,493,496.47,487,487.2,2813200 -2009-10-02,483.74,491.74,482.6,484.58,2600800 -2009-10-05,487.65,492.43,483.34,488.52,2144600 -2009-10-06,491.7,499.37,491.7,498.74,2732300 -2009-10-07,499,518.99,497.81,517.54,4874200 -2009-10-08,519.57,523.25,513.34,514.18,4303800 -2009-10-09,516.65,521.51,514.5,516.25,2738100 -2009-10-12,523.42,525.76,519.32,524.04,3322200 -2009-10-13,524.39,527.46,521.38,526.11,3037400 -2009-10-14,532.46,535.58,530,535.32,3258400 -2009-10-15,533.75,536.9,527.27,529.91,6100400 -2009-10-16,547.33,554.75,544.53,549.85,8841900 -2009-10-19,552.69,553.6,548.73,552.09,3217900 -2009-10-20,551.64,552.95,540.7,551.72,4043700 -2009-10-21,549.91,559.35,549,551.1,3670600 -2009-10-22,550,555,548,554.09,2336500 -2009-10-23,555.25,557.89,551.2,553.69,2392700 -2009-10-26,555.75,561.64,550.89,554.21,2970400 -2009-10-27,550.97,554.56,544.16,548.29,3216500 -2009-10-28,547.87,550,538.25,540.3,2567800 -2009-10-29,543.01,551.83,541,551.05,2522600 -2009-10-30,550,550.17,534.24,536.12,3468500 -2009-11-02,537.08,539.46,528.24,533.99,3202100 -2009-11-03,530.01,537.5,528.3,537.29,2380200 -2009-11-04,540.8,545.5,536.42,540.33,2332700 -2009-11-05,543.49,549.77,542.66,548.65,1847700 -2009-11-06,547.72,551.78,545.5,551.1,1826700 -2009-11-09,555.45,562.58,554.23,562.51,2649900 -2009-11-10,562.73,568.78,562,566.76,2230800 -2009-11-11,570.48,573.5,565.86,570.56,2319700 -2009-11-12,569.56,572.9,565.5,567.85,1886300 -2009-11-13,569.29,572.51,566.61,572.05,1666800 -2009-11-16,575,576.99,572.78,576.28,2199200 -2009-11-17,574.87,577.5,573.72,577.49,1916700 -2009-11-18,576.65,578.78,572.07,576.65,1549600 -2009-11-19,573.77,574,570,572.99,2168000 -2009-11-20,569.5,571.6,569.4,569.96,2006200 -2009-11-23,576.49,586.6,575.86,582.35,2547500 -2009-11-24,582.52,584.29,576.54,583.09,1605200 -2009-11-25,586.41,587.06,582.69,585.74,1461200 -2009-11-27,572,582.46,570.97,579.76,1384600 -2009-11-30,580.63,583.67,577.11,583,1725100 -2009-12-01,588.13,591.22,583,589.87,2320300 -2009-12-02,591,593.01,586.22,587.51,1663200 -2009-12-03,589.04,591.45,585,585.74,1428700 -2009-12-04,593.02,594.83,579.18,585.01,2513600 -2009-12-07,584.21,588.69,581,586.25,1636200 -2009-12-08,583.5,590.66,582,587.05,1524000 -2009-12-09,587.5,589.33,583.58,589.02,1781000 -2009-12-10,590.44,594.71,590.41,591.5,1668300 -2009-12-11,594.68,594.75,587.73,590.51,1720000 -2009-12-14,595.35,597.31,592.61,595.73,1913400 -2009-12-15,593.3,596.38,590.99,593.14,2280400 -2009-12-16,598.6,600.37,596.64,597.76,2809400 -2009-12-17,596.44,597.64,593.76,593.94,2638800 -2009-12-18,596.03,598.93,595,596.42,3531500 -2009-12-21,597.61,599.84,595.67,598.68,2571200 -2009-12-22,601.34,601.5,598.85,601.12,1880800 -2009-12-23,603.5,612.87,602.85,611.68,2072700 -2009-12-24,612.93,619.52,612.27,618.48,858700 -2009-12-28,621.66,625.99,618.48,622.87,1697900 -2009-12-29,624.74,624.84,618.29,619.4,1424800 -2009-12-30,618.5,622.73,618.01,622.73,1465600 -2009-12-31,624.75,625.4,619.98,619.98,1219800 -2010-01-04,626.95,629.51,624.24,626.75,1956200 -2010-01-05,627.18,627.84,621.54,623.99,3004700 -2010-01-06,625.86,625.86,606.36,608.26,3978700 -2010-01-07,609.4,610,592.65,594.1,6414300 -2010-01-08,592,603.25,589.11,602.02,4724300 -2010-01-11,604.46,604.46,594.04,601.11,7212900 -2010-01-12,597.65,598.16,588,590.48,4853300 -2010-01-13,576.49,588.38,573.9,587.09,6496600 -2010-01-14,583.9,594.2,582.81,589.85,4240100 -2010-01-15,593.34,593.56,578.04,580,5434500 -2010-01-19,581.2,590.42,576.29,587.62,4316700 -2010-01-20,585.98,585.98,575.29,580.41,3250700 -2010-01-21,583.44,586.82,572.25,582.98,6307700 -2010-01-22,564.5,570.6,534.86,550.01,6800400 -2010-01-25,546.59,549.88,535.51,540,4419900 -2010-01-26,537.97,549.6,536.29,542.42,4355500 -2010-01-27,541.27,547.65,535.31,542.1,3964400 -2010-01-28,544.49,547,530.6,534.29,3229100 -2010-01-29,538.49,540.99,525.61,529.94,4140500 -2010-02-01,534.6,535.81,530.3,533.02,2250800 -2010-02-02,534.96,534.96,527.61,531.12,4096200 -2010-02-03,528.67,542.1,528.23,540.82,2999100 -2010-02-04,537,538,525.56,526.78,3377700 -2010-02-05,528.4,533.5,522.46,531.29,3156000 -2010-02-08,532.5,542,531.53,533.47,2694300 -2010-02-09,539.54,541.53,535.07,536.44,2819600 -2010-02-10,534.07,537.79,527.69,534.45,2674500 -2010-02-11,533.32,540.49,529.5,536.4,2410000 -2010-02-12,532.97,537.15,530.5,533.12,2279700 -2010-02-16,536.87,544.13,534.3,541.3,3654400 -2010-02-17,542,543.4,537.61,538.21,2029700 -2010-02-18,537.54,545.01,536.14,543.22,2336900 -2010-02-19,540.53,544.03,539.7,540.76,2553100 -2010-02-22,547.35,547.5,541,542.8,2144600 -2010-02-23,543,543.63,532.29,535.07,2872600 -2010-02-24,533.98,538.44,530.51,531.47,2326600 -2010-02-25,527.12,528.49,520,526.43,3309200 -2010-02-26,527.42,531.75,523.48,526.8,2049300 -2010-03-01,529.2,533.29,527.74,532.69,2237900 -2010-03-02,535.48,545.66,535.01,541.06,4356800 -2010-03-03,542.36,548.12,539.25,545.32,3089400 -2010-03-04,546.5,556.13,546.2,554.59,3183800 -2010-03-05,561.35,567.67,559.9,564.21,3912200 -2010-03-08,564.78,565.18,561.01,562.48,2386400 -2010-03-09,559.85,564.66,556.5,560.19,3176600 -2010-03-10,563.76,578.5,562.21,576.45,5654900 -2010-03-11,574.26,586.21,574.2,581.14,4233300 -2010-03-12,588.14,588.28,579.16,579.54,2753400 -2010-03-15,566.68,569.45,556,563.18,4653900 -2010-03-16,561.83,568.42,560.76,565.2,3431500 -2010-03-17,568.3,571.45,564.25,565.56,3321600 -2010-03-18,564.72,568.44,562.96,566.4,1777200 -2010-03-19,566.23,568,557.28,560,4792400 -2010-03-22,556.11,566.85,554.28,557.5,4004800 -2010-03-23,557.04,558.31,542,549,5501300 -2010-03-24,545.51,559.85,539.7,557.33,6565200 -2010-03-25,559.02,572,558.66,562.88,3930900 -2010-03-26,565.27,567.39,560.02,562.69,2696200 -2010-03-29,563,564.72,560.57,562.45,3104500 -2010-03-30,562.83,567.63,560.28,566.71,1977900 -2010-03-31,565.05,569.74,562.81,567.12,3030800 -2010-04-01,571.35,573.45,565.55,568.8,2102700 -2010-04-05,570.9,574.88,569,571.01,1901500 -2010-04-06,569.46,570.89,565.4,568.22,2060100 -2010-04-07,567.3,568.75,561.86,563.54,2581000 -2010-04-08,563.32,569.85,560.05,567.49,1947500 -2010-04-09,567.49,568.77,564,566.22,2056600 -2010-04-12,567.35,574,566.22,572.73,2352400 -2010-04-13,572.53,588.88,571.13,586.77,3912300 -2010-04-14,590.06,592.34,584.01,589,3402700 -2010-04-15,592.17,597.84,588.29,595.3,6761800 -2010-04-16,563,568.81,549.63,550.15,12235500 -2010-04-19,548.75,553.99,545,550.1,3894000 -2010-04-20,554.17,559.66,551.06,555.04,2977400 -2010-04-21,556.46,560.25,552.16,554.3,2391500 -2010-04-22,552,552.5,543.35,547.06,3280700 -2010-04-23,547.25,549.32,542.27,544.99,2089400 -2010-04-26,544.97,544.99,529.21,531.64,4368800 -2010-04-27,528.95,538.33,527.23,529.06,3844700 -2010-04-28,532.1,534.83,521.03,529.19,3406100 -2010-04-29,533.37,536.5,526.67,532,3058900 -2010-04-30,531.13,537.68,525.44,525.7,2435400 -2010-05-03,526.5,532.92,525.08,530.6,1857800 -2010-05-04,526.52,526.74,504.21,506.37,6076300 -2010-05-05,500.98,515.72,500.47,509.76,4582200 -2010-05-06,508.75,517.52,460,498.67,5000100 -2010-05-07,499.97,505.32,481.33,493.14,5089000 -2010-05-10,513.97,522.82,512.6,521.65,4128000 -2010-05-11,515.67,519.88,508.22,509.05,3322600 -2010-05-12,512.04,512.04,502,505.39,3851800 -2010-05-13,516.5,522,510.37,510.88,3325800 -2010-05-14,509.77,510.99,496.25,507.53,4116000 -2010-05-17,506.78,508.36,498.35,507.97,2793800 -2010-05-18,510,510.97,497.07,498.37,2825500 -2010-05-19,496.26,499.44,487.74,494.43,3445700 -2010-05-20,485.07,485.58,473.8,475.01,4913300 -2010-05-21,469.06,485,464.4,472.05,9690800 -2010-05-24,480.73,489.79,476.8,477.16,4345600 -2010-05-25,468.15,477.45,464.01,477.07,3017400 -2010-05-26,482.07,489.76,475,475.47,3475600 -2010-05-27,484.95,492.31,481.05,490.46,2809100 -2010-05-28,492.74,493.45,483,485.63,2894800 -2010-06-01,480.43,491.06,480.12,482.37,2666800 -2010-06-02,486.68,493.87,481.46,493.37,2540800 -2010-06-03,495.11,508,494.7,505.6,3650700 -2010-06-04,499.72,509.25,496.7,498.72,3920300 -2010-06-07,499.06,500.91,483.15,485.52,3632700 -2010-06-08,487.85,488.84,477.54,484.78,2685100 -2010-06-09,487.22,488.88,472,474.02,2729000 -2010-06-10,480.37,488.5,475.84,487.01,2577900 -2010-06-11,482.5,488.71,481.62,488.5,1781700 -2010-06-14,494.48,494.5,483.19,483.19,2040400 -2010-06-15,483.08,500.4,482.18,497.99,4259600 -2010-06-16,496.17,504,496.11,501.27,2289300 -2010-06-17,503.45,505.87,496.69,500.08,1977300 -2010-06-18,502.51,503.47,498.13,500.03,2872900 -2010-06-21,499.9,500.97,484.89,488.56,2983500 -2010-06-22,489.9,496.6,485.73,486.25,2219700 -2010-06-23,486.89,486.89,478.16,482.05,2029100 -2010-06-24,479.66,482.75,473.26,475.1,1893600 -2010-06-25,477.06,477.65,470.56,472.68,2245200 -2010-06-28,472.59,477.55,469.01,472.08,1762300 -2010-06-29,463.44,464.55,451.12,454.26,3502100 -2010-06-30,454.96,457.83,444.72,444.95,3603200 -2010-07-01,445.29,448.4,433.63,439.49,3513600 -2010-07-02,441.62,442.28,436,436.55,1936000 -2010-07-06,444,447.67,433.63,436.07,2560100 -2010-07-07,438.31,451.29,435.38,450.2,3129700 -2010-07-08,453.55,457.33,449.66,456.56,2668900 -2010-07-09,471.96,473.26,462.78,467.49,4331500 -2010-07-12,472.37,479.44,471.08,475.83,3334400 -2010-07-13,482.25,492.99,480.28,489.2,3976300 -2010-07-14,489.88,493.83,486.46,491.34,3118000 -2010-07-15,491.73,494.7,482.68,494.02,4858200 -2010-07-16,469.12,470.56,459.52,459.61,7824800 -2010-07-19,461.01,469.65,457.52,466.18,4550300 -2010-07-20,461.03,482.99,460.6,481.59,4054500 -2010-07-21,484,485.7,475.43,477.5,3279600 -2010-07-22,483.23,488.98,482.48,484.81,2147700 -2010-07-23,480.77,490.59,480.01,490.06,2264400 -2010-07-26,489.09,490.75,484.88,488.97,1995200 -2010-07-27,490.58,497.5,490.17,492.63,2451200 -2010-07-28,494.94,495.25,482.67,484.35,2496000 -2010-07-29,485.95,488.88,479.33,484.99,2675500 -2010-07-30,479.65,487.36,479.14,484.85,2144100 -2010-08-02,488.99,493.28,486.94,490.41,1858700 -2010-08-03,490.5,492.46,486.76,489.83,1802300 -2010-08-04,492.18,507,491.05,506.32,3812500 -2010-08-05,505.89,508.6,503.56,508.1,2420400 -2010-08-06,505.4,505.74,496.05,500.22,3319500 -2010-08-09,502.25,505.5,501.36,505.35,1872200 -2010-08-10,502.35,506,498.57,503.71,2074000 -2010-08-11,497.73,498,491.5,491.74,2223000 -2010-08-12,483.94,494.75,482.51,492.01,2204600 -2010-08-13,489,491.19,486.01,486.35,1934700 -2010-08-16,483.68,489.87,480.5,485.59,1305000 -2010-08-17,488.53,494.7,486.03,490.52,1890700 -2010-08-18,490.44,490.87,481.55,482.15,2686400 -2010-08-19,481.01,482.51,467.25,467.97,3925000 -2010-08-20,467.97,471.59,461.02,462.02,3917600 -2010-08-23,461.5,468.25,457.73,464.07,2986200 -2010-08-24,457.7,458.37,450.92,451.39,2762700 -2010-08-25,450,457.81,450,454.62,2592100 -2010-08-26,456.06,457.26,450.44,450.98,1777000 -2010-08-27,452.56,459.99,447.65,458.83,2312400 -2010-08-30,459.15,459.76,452.42,452.69,1231400 -2010-08-31,450.11,454.87,448,450.02,1946800 -2010-09-01,454.98,464.94,452.5,460.33,3228300 -2010-09-02,462.84,464.43,460.31,463.18,1684200 -2010-09-03,470.52,471.88,467.44,470.3,2540400 -2010-09-07,464.5,467.59,463.02,464.4,1709900 -2010-09-08,465.19,472.5,464.51,470.58,2401800 -2010-09-09,477.83,480.4,470.58,476.18,2430600 -2010-09-10,479.02,479.79,475.08,476.14,1974300 -2010-09-13,480.9,484.35,479.53,482.27,2241500 -2010-09-14,482.01,484.75,480.08,480.43,2216500 -2010-09-15,479.95,481.89,478.5,480.64,2402800 -2010-09-16,479.95,482.45,479.41,481.06,1969500 -2010-09-17,483.75,491.2,481.18,490.15,5641600 -2010-09-20,492.5,510.41,492.06,508.28,4403500 -2010-09-21,509.68,519.98,508.91,513.46,4466300 -2010-09-22,512.86,517.78,511.68,516,2537100 -2010-09-23,514.61,519.69,511.3,513.48,2317400 -2010-09-24,521.74,527.83,518.26,527.29,3356900 -2010-09-27,528.85,536.85,528.85,530.41,3107400 -2010-09-28,533.48,533.59,518.45,527.17,3654700 -2010-09-29,527.85,532.94,524.71,527.69,2172200 -2010-09-30,529.16,531.87,518.92,525.79,3244100 -2010-10-01,530,530.62,523,525.62,2225000 -2010-10-04,524.95,528.25,518.85,522.35,1940500 -2010-10-05,528.38,540,526.55,538.23,3507100 -2010-10-06,539.26,539.95,529.94,534.35,2762300 -2010-10-07,536.21,537.2,529.14,530.01,2395800 -2010-10-08,532.77,537.6,527.62,536.35,2859200 -2010-10-11,538.48,544.6,537.17,538.84,2626300 -2010-10-12,540.12,545.99,537.79,541.39,3753600 -2010-10-13,547,547.49,542.33,543.3,3055600 -2010-10-14,544.18,545.25,537.11,540.93,6634100 -2010-10-15,599.27,601.64,591.6,601.45,14824800 -2010-10-18,600.55,619.69,600.55,617.71,7098200 -2010-10-19,608.85,614.82,602.86,607.83,4587900 -2010-10-20,608.14,617.38,607.5,607.98,3525100 -2010-10-21,611.51,616,606,611.99,2920500 -2010-10-22,611.92,614.82,610.05,612.53,2256100 -2010-10-25,615.59,624.74,614.97,616.5,3158400 -2010-10-26,613.1,621.23,611.03,618.6,2512900 -2010-10-27,615.77,620,612.33,616.47,2241900 -2010-10-28,620.05,621,613.3,618.58,2184300 -2010-10-29,617.07,619,612.99,613.7,2278300 -2010-11-01,615.73,620.66,611.21,615,3087100 -2010-11-02,618.67,620,614.58,615.6,1997600 -2010-11-03,617.5,621.83,613.5,620.18,3380500 -2010-11-04,624.64,629.92,622.1,624.27,3570800 -2010-11-05,623.18,625.49,621.11,625.08,1765700 -2010-11-08,624.02,629.49,623.13,626.77,2101300 -2010-11-09,630,630.85,620.51,624.82,2237200 -2010-11-10,622.08,623,617.51,622.88,2497000 -2010-11-11,619.7,619.85,614.21,617.19,2261600 -2010-11-12,613.99,616.9,601.21,603.29,3393000 -2010-11-15,603.08,604,594.05,595.47,3478900 -2010-11-16,592.76,597.89,583.45,583.72,3307400 -2010-11-17,585,589.5,581.37,583.55,2442500 -2010-11-18,589,599.98,588.56,596.56,2590000 -2010-11-19,597,597.89,590.34,590.83,2297500 -2010-11-22,587.47,593.44,582.75,591.22,2186600 -2010-11-23,587.01,589.01,578.2,583.01,2162600 -2010-11-24,587.31,596.6,587.05,594.97,2396400 -2010-11-26,590.46,592.98,587,590,1311100 -2010-11-29,589.17,589.8,579.95,582.11,2859700 -2010-11-30,574.32,574.32,553.31,555.71,7117400 -2010-12-01,563,571.57,562.4,564.35,3754100 -2010-12-02,568.66,573.33,565.35,571.82,2547900 -2010-12-03,569.45,576.48,568,573,2631200 -2010-12-06,580.57,582,576.61,578.36,2093800 -2010-12-07,591.27,593,586,587.14,3042200 -2010-12-08,591.97,592.52,583.69,590.54,1756900 -2010-12-09,593.88,595.58,589,591.5,1868900 -2010-12-10,593.14,593.99,590.29,592.21,1704700 -2010-12-13,597.12,603,594.09,594.62,2398500 -2010-12-14,597.09,598.29,592.48,594.91,1643300 -2010-12-15,594.2,596.45,589.15,590.3,2167700 -2010-12-16,592.85,593.77,588.07,591.71,1596900 -2010-12-17,591,592.56,587.67,590.8,3087100 -2010-12-20,594.65,597.88,588.66,595.06,1973300 -2010-12-21,598.57,604.72,597.61,603.07,1879500 -2010-12-22,604,607,603.28,605.49,1207500 -2010-12-23,605.34,606,602.03,604.23,1110800 -2010-12-27,602.74,603.78,599.5,602.38,1208100 -2010-12-28,602.05,603.87,598.01,598.92,1064800 -2010-12-29,602,602.41,598.92,601,1019200 -2010-12-30,598,601.33,597.39,598.86,989500 -2010-12-31,596.74,598.42,592.03,593.97,1539300 -2011-01-03,596.48,605.59,596.48,604.35,2365200 -2011-01-04,605.62,606.18,600.12,602.12,1824500 -2011-01-05,600.07,610.33,600.05,609.07,2532300 -2011-01-06,610.68,618.43,610.05,613.5,2057800 -2011-01-07,615.91,618.25,610.13,616.44,2101200 -2011-01-10,614.8,615.39,608.56,614.21,1579200 -2011-01-11,617.71,618.8,614.5,616.01,1439300 -2011-01-12,619.35,619.35,614.77,616.87,1632700 -2011-01-13,616.97,619.67,614.16,616.69,1334000 -2011-01-14,617.4,624.27,617.08,624.18,2365600 -2011-01-18,626.06,641.99,625.27,639.63,3617000 -2011-01-19,642.12,642.96,629.66,631.75,3406100 -2011-01-20,632.21,634.08,623.29,626.77,5485800 -2011-01-21,639.58,641.73,611.36,611.83,8904400 -2011-01-24,607.57,612.49,601.23,611.08,4599200 -2011-01-25,608.2,620.69,606.52,619.91,3646800 -2011-01-26,620.33,622.49,615.28,616.5,2038100 -2011-01-27,617.89,619.7,613.25,616.79,2019200 -2011-01-28,619.07,620.36,599.76,600.99,4231100 -2011-01-31,603.6,604.47,595.55,600.36,2804900 -2011-02-01,604.49,613.35,603.11,611.04,2745300 -2011-02-02,611,614.34,607.53,612,1760700 -2011-02-03,609.48,611.45,606.13,610.15,1495100 -2011-02-04,610.15,611.44,606.61,610.98,1550800 -2011-02-07,610.16,618.39,609.21,614.29,1799600 -2011-02-08,614.93,619.63,614.51,618.38,1694900 -2011-02-09,616.87,619.45,612.34,616.5,1842500 -2011-02-10,613.9,617.5,611.56,616.44,2334400 -2011-02-11,613.79,625,613,624.5,2589900 -2011-02-14,623.34,629.64,620.04,628.15,2128000 -2011-02-15,627.32,630.09,623.1,624.15,2092000 -2011-02-16,625.63,626.5,622.1,624.22,1684000 -2011-02-17,621.25,627.25,620.28,625.26,1478800 -2011-02-18,626,631.18,624.18,630.08,3217900 -2011-02-22,620.03,624.93,607.77,610.21,3639900 -2011-02-23,610.33,614.7,604,611.32,2889600 -2011-02-24,611.39,613.09,601.35,608.82,2711700 -2011-02-25,611.86,614.72,609.5,610.04,1932400 -2011-02-28,610,616.49,608.01,613.4,2281500 -2011-03-01,617.78,619.22,599.3,600.76,3323200 -2011-03-02,599.8,606,595.19,600.79,2026700 -2011-03-03,606.38,611.49,605,609.56,1945300 -2011-03-04,608.33,608.98,600.2,600.62,3011000 -2011-03-07,600.55,603.69,587,591.66,3462700 -2011-03-08,592.93,597.98,590.2,592.31,2284900 -2011-03-09,591,594.51,585.75,591.77,2151000 -2011-03-10,585.44,586.62,579.45,580.3,3128100 -2011-03-11,578.22,580,573.33,576.71,3032000 -2011-03-14,572.8,578.29,568.02,569.99,2816100 -2011-03-15,557.5,571,555.5,569.56,4005600 -2011-03-16,568.01,569.79,551.28,557.1,3798500 -2011-03-17,564.48,569,560.54,561.36,2899300 -2011-03-18,564.64,567.99,559.74,561.06,3298600 -2011-03-21,570.22,579.8,569.02,576.5,3020900 -2011-03-22,577.27,579.23,572.51,577.32,1886900 -2011-03-23,575.19,582.45,572,582.16,1816200 -2011-03-24,585.43,588.39,578.8,586.89,2098700 -2011-03-25,586.88,586.91,579.24,579.74,2858400 -2011-03-28,582.07,584.99,574.71,575.36,2218400 -2011-03-29,576,581.89,573.01,581.73,1604800 -2011-03-30,584.38,585.5,580.58,581.84,1422300 -2011-03-31,583,588.16,581.74,586.76,2029400 -2011-04-01,588.76,595.19,588.76,591.8,2613200 -2011-04-04,593,594.74,583.1,587.68,2054500 -2011-04-05,581.08,581.49,565.68,569.09,6047500 -2011-04-06,572.18,575.16,568,574.18,2668300 -2011-04-07,575.73,580.64,574.19,580,2531500 -2011-04-08,584.89,584.89,578.06,578.16,1901800 -2011-04-11,576.2,578.1,573,577.37,1858200 -2011-04-12,575,576.91,568.05,570.61,2085600 -2011-04-13,575.51,577.6,571.75,576.28,2069400 -2011-04-14,575.19,579.45,572.1,578.51,5456300 -2011-04-15,545.29,545.75,530.06,530.7,14043700 -2011-04-18,526.42,527.66,519,526.84,5039800 -2011-04-19,529.95,530.88,520.9,521.53,2684100 -2011-04-20,525.9,526.82,521.39,525.73,3060000 -2011-04-21,527.49,528.28,522.39,525.1,2470100 -2011-04-25,525.25,527,522.01,525.05,1630800 -2011-04-26,526.52,537.44,525.21,532.82,3500000 -2011-04-27,538,538.11,534.35,537.76,2298400 -2011-04-28,538.06,539.25,534.08,537.97,2000000 -2011-04-29,540,544.1,538.51,544.1,4228500 -2011-05-02,545.7,545.73,537.12,538.56,2133700 -2011-05-03,537.13,542.01,529.63,533.89,2081500 -2011-05-04,535.17,539,533.02,535.79,2117000 -2011-05-05,533.86,539.42,531.5,534.27,1997800 -2011-05-06,538.15,541.46,535.18,535.3,2056100 -2011-05-09,535,538.49,531.1,537.68,1948700 -2011-05-10,540,544.43,537.54,542.66,2042900 -2011-05-11,540.14,543.55,533.69,535.45,2338800 -2011-05-12,535.24,536.94,530.91,535.05,1448300 -2011-05-13,534.61,535.92,529.05,529.55,2108700 -2011-05-16,526.31,527.27,516.4,518.42,2958200 -2011-05-17,515.43,531.22,515.03,530.46,3303600 -2011-05-18,529.54,530.33,525.7,529.81,1953200 -2011-05-19,532.73,536.54,529.72,531.25,2468700 -2011-05-20,531.8,531.99,523.13,524.03,2317500 -2011-05-23,516.6,520,513.4,518.39,2300000 -2011-05-24,520.37,523.96,518.15,518.26,1900000 -2011-05-25,519.67,522.77,517.25,519.67,1301600 -2011-05-26,517.7,522.12,515,518.13,2118500 -2011-05-27,518.48,521.79,516.3,520.9,1745800 -2011-05-31,525,529.05,523.5,529.02,2687300 -2011-06-01,528.04,533.2,525.31,525.6,2955900 -2011-06-02,527.57,530.3,522.48,528.06,2204500 -2011-06-03,522,527.6,521.5,523.08,1748500 -2011-06-06,523.54,526.82,519.25,521.06,1942100 -2011-06-07,522.89,524.63,518.99,519.03,1907600 -2011-06-08,516.53,521.24,515.78,519.17,1653400 -2011-06-09,520,520,515.64,516.73,1689100 -2011-06-10,514.08,516.69,509.29,509.51,2439900 -2011-06-13,510,510.2,502.17,504.73,2427300 -2011-06-14,508.15,514.08,506.99,508.37,2341500 -2011-06-15,505.03,508.35,500.61,502.95,2073300 -2011-06-16,502.81,506.57,496.67,500.37,2757000 -2011-06-17,506.18,506.69,484.8,485.02,5245400 -2011-06-20,485,486.23,479.23,484.58,3028600 -2011-06-21,487.19,493.94,484.73,493,2765400 -2011-06-22,491.45,492.35,486.73,487.01,2407100 -2011-06-23,482.13,482.86,473.73,480.22,4801700 -2011-06-24,480.68,480.75,473.02,474.88,3805600 -2011-06-27,474,488.4,473.6,482.8,3444700 -2011-06-28,484.02,496.21,484.02,493.65,2715100 -2011-06-29,496.54,500.25,492.38,497.57,2343000 -2011-06-30,501.99,506.67,501.5,506.38,2428400 -2011-07-01,506.74,521.18,506.38,521.03,3636700 -2011-07-05,525.3,535.4,525.3,532.44,3849200 -2011-07-06,533.5,538.51,533.04,535.36,2695600 -2011-07-07,541,550.68,535.88,546.6,3935500 -2011-07-08,532.95,537.65,527.27,531.99,4770200 -2011-07-11,528.18,535.98,525.5,527.28,2839300 -2011-07-12,528.16,539.42,526,534.01,2841200 -2011-07-13,537,544,536.48,538.26,2790200 -2011-07-14,539.12,542,526.73,528.94,6649500 -2011-07-15,597.5,600.25,588.16,597.62,13732100 -2011-07-18,592.49,602.05,592,594.94,4468300 -2011-07-19,596.14,604.68,595.53,602.55,2967500 -2011-07-20,602.18,602.83,595.35,595.35,2227800 -2011-07-21,594.03,608.06,594.01,606.99,3469500 -2011-07-22,605.39,619.5,604.27,618.23,3528200 -2011-07-25,613.36,625.41,613,618.98,3131600 -2011-07-26,618.05,627.5,617.22,622.52,2342900 -2011-07-27,617.18,620.95,604.75,607.22,3934400 -2011-07-28,605.19,615.98,603,610.94,3108400 -2011-07-29,604.23,614.96,603.69,603.69,4137400 -2011-08-01,611.22,615.5,599.18,606.77,3966100 -2011-08-02,606,609.67,591.57,592.4,3200600 -2011-08-03,594.27,603,583.63,601.17,3825700 -2011-08-04,594.5,598.85,577.47,577.52,4914600 -2011-08-05,582.54,590,562,579.04,5929100 -2011-08-08,562.98,569,544.35,546.02,7496600 -2011-08-09,561,574.61,541.01,573.41,6469700 -2011-08-10,561.38,564.12,547.73,549.01,5369600 -2011-08-11,553.82,568.5,548.41,562.13,4830600 -2011-08-12,569.5,570.5,560.4,563.77,3154300 -2011-08-15,553.43,564.99,546.05,557.23,7144900 -2011-08-16,552.43,552.44,530.3,539,6939400 -2011-08-17,540.03,543.69,530.77,533.15,4079100 -2011-08-18,523.47,524.89,500.49,504.88,6290700 -2011-08-19,499.34,514.87,490.86,490.92,5410000 -2011-08-22,504,507,494.53,498.17,4905900 -2011-08-23,503.5,521.41,499.06,518.82,4346800 -2011-08-24,519.33,530,517.23,523.29,3594500 -2011-08-25,530.38,537.27,518.3,520.04,3293000 -2011-08-26,519.99,530.45,513.14,526.86,3596300 -2011-08-29,534.56,539.45,533.56,539.08,2335800 -2011-08-30,538.19,542.99,530.81,540.7,2989000 -2011-08-31,544.74,546.3,536,540.96,2693300 -2011-09-01,540.75,543.83,531.22,532.5,2415500 -2011-09-02,524.47,527.92,520.73,524.84,2401200 -2011-09-06,510.8,522.76,510.5,522.18,2715800 -2011-09-07,530.45,535.94,527.4,534.03,2755800 -2011-09-08,533.8,539.1,531.9,534.96,2380500 -2011-09-09,531.4,534.65,521.19,524.85,3268800 -2011-09-12,517.96,531.99,517.5,530.12,2670400 -2011-09-13,532,533.88,523.4,529.52,2354200 -2011-09-14,532.59,536.95,525.82,532.07,2694400 -2011-09-15,535.5,544.98,534.56,542.56,2960800 -2011-09-16,544.8,546.84,543.14,546.68,3534300 -2011-09-19,540.35,549.9,535.38,546.67,2468400 -2011-09-20,549.4,558.52,542.67,546.63,2779100 -2011-09-21,547.69,555,538.86,539.2,2514300 -2011-09-22,526.25,528.78,514,520.66,4400300 -2011-09-23,516.56,526.42,514.5,525.51,2777300 -2011-09-26,527.25,532.93,513.25,531.89,2634200 -2011-09-27,538.2,547.05,536.05,539.34,3010900 -2011-09-28,541.5,544.02,527.7,528.84,2263300 -2011-09-29,536.04,537.3,519.41,527.5,2906600 -2011-09-30,520.21,524,514.38,515.04,2723600 -2011-10-03,509.85,512,495,495.52,4474400 -2011-10-04,490.03,503.44,480.6,501.9,4158800 -2011-10-05,496.35,507.8,480.77,504.7,4534100 -2011-10-06,507.5,515.23,502.6,514.71,3424300 -2011-10-07,516.83,520.5,510.3,515.12,2855900 -2011-10-10,525.18,537.47,523.2,537.17,2322200 -2011-10-11,533.46,546.8,533.46,543.18,2853400 -2011-10-12,548.13,555.23,544.63,548.5,3177800 -2011-10-13,550.03,559,548.02,558.99,5687600 -2011-10-14,599.47,599.6,587.57,591.68,8529900 -2011-10-17,583.72,591.83,578,582.41,4008200 -2011-10-18,580.19,592.56,577.4,590.51,3800800 -2011-10-19,587.34,592.06,579.22,580.7,2931500 -2011-10-20,581.9,588.89,579.51,583.67,3379000 -2011-10-21,589.51,592.75,586.7,590.49,3391000 -2011-10-24,586.72,599.97,586.5,596.42,3426900 -2011-10-25,593.1,595,582.85,583.16,2540500 -2011-10-26,589.55,590.18,572.86,586.31,2873100 -2011-10-27,598.42,602.7,593.3,598.67,3780300 -2011-10-28,594.52,602.3,594.25,600.14,2508000 -2011-10-31,595.09,599.69,591.67,592.64,2557800 -2011-11-01,580.1,585.51,576.75,578.65,3125100 -2011-11-02,584.9,587.96,580.48,584.82,2120900 -2011-11-03,587,597.5,583.72,597.5,2669800 -2011-11-04,593.5,599.74,592.43,596.14,2834800 -2011-11-07,593.32,608.78,592.23,608.33,3357400 -2011-11-08,609,614.37,603.6,612.34,3029400 -2011-11-09,604.26,609.39,598.66,600.95,3711000 -2011-11-10,605.93,605.95,591.56,595.08,2868400 -2011-11-11,601.3,612.09,598.6,608.35,3977000 -2011-11-14,608,618.08,607.78,613,3188700 -2011-11-15,612.8,618.08,610.5,616.56,2676000 -2011-11-16,612.08,618.3,610.61,611.47,2608500 -2011-11-17,610.05,612.29,596.78,600.87,3493300 -2011-11-18,602,604.5,593.75,594.88,3287700 -2011-11-21,587.76,588.5,572.09,580.94,3001300 -2011-11-22,580,584.97,575.24,580,2405300 -2011-11-23,575.35,580.25,570.11,570.11,2325800 -2011-11-25,565.19,574.27,561.33,563,1562400 -2011-11-28,579.37,588.82,576.5,588.19,2828900 -2011-11-29,587.88,590.36,581.33,582.93,1831800 -2011-11-30,597.95,599.51,592.09,599.39,3397000 -2011-12-01,600,616,599,613.77,3620600 -2011-12-02,617.05,624,616.26,620.36,4085700 -2011-12-05,627.64,631.9,622.4,625.65,3197500 -2011-12-06,622.99,628.62,620.24,623.77,2326500 -2011-12-07,621.68,625.66,618.1,623.39,2257300 -2011-12-08,621.04,627.45,615.3,616.05,2413100 -2011-12-09,618,629.13,617.01,627.42,2766200 -2011-12-12,621.88,626.18,620.29,625.39,2183900 -2011-12-13,628.76,636.56,622.85,625.63,4028200 -2011-12-14,621.85,624.32,612.49,618.07,3903700 -2011-12-15,622.52,624,618.69,619.54,2408600 -2011-12-16,624.32,629.32,621.47,625.96,4459300 -2011-12-19,628.01,628.5,620,621.83,2143500 -2011-12-20,628,631.84,627.99,630.37,2388200 -2011-12-21,630.01,631.82,618.96,625.82,2497900 -2011-12-22,627.95,631.73,627.01,629.7,1822300 -2011-12-23,632,634.68,630.56,633.14,1453700 -2011-12-27,632.05,644.49,632,640.25,1606400 -2011-12-28,642.75,645,638.1,639.7,2127200 -2011-12-29,641.49,643,635.2,642.4,1575400 -2011-12-30,642.02,646.76,642.02,645.9,1782300 -2012-01-03,652.94,668.15,652.37,665.41,3676500 -2012-01-04,665.03,670.25,660.62,668.28,2864000 -2012-01-05,662.13,663.97,656.23,659.01,3282900 -2012-01-06,659.15,660,649.79,650.02,2692900 -2012-01-09,646.5,647,621.23,622.46,5822600 -2012-01-10,629.75,633.8,616.91,623.14,4395600 -2012-01-11,623.5,629.39,621.12,625.96,2400000 -2012-01-12,631.22,632.89,626.5,629.64,1875200 -2012-01-13,626.26,626.95,621.06,624.99,2307300 -2012-01-17,631.98,631.98,625.68,628.58,1909300 -2012-01-18,626.63,634,622.12,632.91,2761700 -2012-01-19,640.99,640.99,631.46,639.57,6305300 -2012-01-20,590.53,591,581.7,585.99,10576300 -2012-01-23,586,588.66,583.16,585.52,3412900 -2012-01-24,586.32,587.68,578,580.93,3055800 -2012-01-25,577.51,578.71,566.38,569.49,4987700 -2012-01-26,571.98,574.48,564.55,568.1,3226200 -2012-01-27,570.78,580.32,569.33,579.98,3617500 -2012-01-30,578.05,580,573.4,577.69,2330500 -2012-01-31,583,584,575.15,580.11,2142400 -2012-02-01,584.94,585.5,579.14,580.83,2320700 -2012-02-02,584.87,586.41,582.08,585.11,2414700 -2012-02-03,590.66,597.07,588.05,596.33,3168500 -2012-02-06,595.01,610.83,594.01,609.09,3679600 -2012-02-07,607.15,609.39,603.76,606.77,2092100 -2012-02-08,608.64,611.35,604.74,609.85,1836400 -2012-02-09,612.02,614.5,609,611.46,2264700 -2012-02-10,607.88,608.13,604,605.91,2325200 -2012-02-13,610.5,613.84,610.02,612.2,1816300 -2012-02-14,611.54,612,604.76,609.76,1803700 -2012-02-15,612.93,612.93,602.56,605.56,2425900 -2012-02-16,602.82,608.81,597.73,606.52,2530900 -2012-02-17,604.97,607.63,602.4,604.64,2449100 -2012-02-21,603.87,617.88,602.88,614,2480800 -2012-02-22,611.96,616.78,606.71,607.94,1967000 -2012-02-23,607,607.94,600.35,606.11,2055000 -2012-02-24,607.35,611.65,605.51,609.9,1935600 -2012-02-27,606.59,612.36,605.06,609.31,1813900 -2012-02-28,610,619.77,607.68,618.39,2847600 -2012-02-29,618.6,625.6,615.5,618.25,3136900 -2012-03-01,622.26,625.7,618.15,622.4,2237700 -2012-03-02,622,624,620.32,621.25,1573300 -2012-03-05,620.43,622.49,611.38,614.25,1593300 -2012-03-06,608.05,608.81,593.84,604.96,3174400 -2012-03-07,609.05,611.19,605.86,606.8,1264500 -2012-03-08,610.04,611.5,606.35,607.14,1345500 -2012-03-09,607.95,611.9,600,600.25,2670600 -2012-03-12,600,607,599.26,605.15,1669000 -2012-03-13,608.75,617.85,605.55,617.78,2245800 -2012-03-14,615,622.78,613.46,615.99,2936900 -2012-03-15,616.6,623.5,614.83,621.13,2435100 -2012-03-16,620.89,625.91,620.05,625.04,3050500 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-2012-05-17,633.83,637.85,621.23,623.05,3353800 -2012-05-18,625.1,632.42,596.7,600.4,5973500 -2012-05-21,600.51,615.69,600,614.11,3075400 -2012-05-22,613.44,613.81,596,600.8,3051900 -2012-05-23,601.65,609.6,597.12,609.46,3178100 -2012-05-24,609.16,611.92,598.87,603.66,1891300 -2012-05-25,601,601.73,588.28,591.53,3581900 -2012-05-29,595.81,599.13,588.32,594.34,2605700 -2012-05-30,588.16,591.9,583.53,588.23,1906700 -2012-05-31,588.72,590,579,580.86,2968300 -2012-06-01,571.79,572.65,568.35,570.98,3057900 -2012-06-04,570.22,580.49,570.01,578.59,2432700 -2012-06-05,575.45,578.13,566.47,570.41,2339900 -2012-06-06,576.48,581.97,573.61,580.57,2095800 -2012-06-07,587.6,587.89,577.25,578.23,1758500 -2012-06-08,575.85,581,574.58,580.45,1410400 -2012-06-11,584.21,585.32,566.69,568.5,2661100 -2012-06-12,569.77,570.3,558.58,565.1,3224200 -2012-06-13,561.72,567,558.68,561.09,1954200 -2012-06-14,561.3,565.07,556.52,559.05,2344900 -2012-06-15,560.34,564.52,557.09,564.51,3001200 -2012-06-18,562.62,574.21,559.25,570.85,2496900 -2012-06-19,573.59,584.28,573.12,581.53,2076200 -2012-06-20,579.81,580,573.51,577.51,2346700 -2012-06-21,579.84,579.84,563.73,565.21,2011300 -2012-06-22,568,571.48,565.82,571.48,2227900 -2012-06-25,567.33,568.09,557.35,560.7,1581600 -2012-06-26,562.76,566.6,559.48,564.68,1350200 -2012-06-27,567.7,573.99,566.02,569.3,1692300 -2012-06-28,565.9,566.23,557.21,564.31,1920900 -2012-06-29,574.96,580.13,572.2,580.07,2519500 -2012-07-02,581.82,583,576.5,580.47,1655500 -2012-07-03,580.01,588.41,578,587.83,1189500 -2012-07-05,588.76,600.06,588.54,595.92,2345900 -2012-07-06,592.45,593.52,582.82,585.98,2161800 -2012-07-09,584.95,588.6,581.25,586.01,1715100 -2012-07-10,590.19,592.43,578.74,581.7,1923100 -2012-07-11,576.3,577.85,564.94,571.19,3499300 -2012-07-12,567.12,571.93,562.09,570.48,2309800 -2012-07-13,572.15,579.15,568.55,576.52,1976000 -2012-07-16,576.37,579.19,571.78,574.92,1462600 -2012-07-17,578.43,580.67,568.4,576.73,1680100 -2012-07-18,576.98,583.69,576.13,580.76,1548200 -2012-07-19,586.14,598.48,586,593.06,4674700 -2012-07-20,608.76,612.94,598.18,610.82,6463700 -2012-07-23,600.48,618.35,598.25,615.51,3561700 -2012-07-24,615,617.93,604.34,607.57,2009400 -2012-07-25,608.32,613.38,605.37,607.99,1823000 -2012-07-26,615,616.87,610.03,613.36,1685200 -2012-07-27,618.89,635,617.5,634.96,3549700 -2012-07-30,636.05,642.6,629.5,632.3,2186700 -2012-07-31,628.26,636.5,628.22,632.97,1865600 -2012-08-01,637.3,639.51,631.38,632.68,1844600 -2012-08-02,625.51,638.03,623.41,628.75,1977700 -2012-08-03,640,643.72,636.14,641.33,1897100 -2012-08-06,639.61,649.38,639.22,642.82,1782400 -2012-08-07,641.79,644.26,636.47,640.54,1981800 -2012-08-08,639.05,645.87,638.5,642.23,1322200 -2012-08-09,644.51,646.37,641.52,642.35,1070300 -2012-08-10,638.59,642.24,636.13,642,1434600 -2012-08-13,647.42,660.15,646.68,660.01,3267900 -2012-08-14,659.25,672.85,659,668.66,3661700 -2012-08-15,670.28,674.25,664.1,667.54,2410700 -2012-08-16,667.51,674.64,667.08,672.87,1717700 -2012-08-17,674.12,677.25,671.7,677.14,2177700 -2012-08-20,675.5,678.87,672.66,675.54,1758100 -2012-08-21,673.11,678,662.17,669.51,2222200 -2012-08-22,667.38,680.6,666.7,677.18,1909200 -2012-08-23,674.27,680.48,671,676.8,1784200 -2012-08-24,675.6,680.45,674.08,678.63,1426600 -2012-08-27,662.99,672,659.24,669.22,2613700 -2012-08-28,665,677.62,664.74,677.25,2058600 -2012-08-29,677.37,688.99,676.15,688.01,2990300 -2012-08-30,684.24,687.39,680.18,681.68,1626900 -2012-08-31,684,688.58,680.04,685.09,2127100 -2012-09-04,684.55,685,673.5,681.04,1889600 -2012-09-05,680,686.5,679.14,680.72,1708200 -2012-09-06,685.96,699.89,684.73,699.4,3043500 -2012-09-07,700,712.25,697.67,706.15,3233000 -2012-09-10,709.76,712.81,698.39,700.77,2560000 -2012-09-11,697.96,700.65,691,692.19,1873800 -2012-09-12,689.41,694.91,680.88,690.88,2642300 -2012-09-13,693.09,709,690.54,706.04,2659000 -2012-09-14,709.6,713,707.01,709.68,2618500 -2012-09-17,708.11,712.88,705,709.98,1508300 -2012-09-18,707.78,718.66,706.78,718.28,2066800 -2012-09-19,717.5,728.56,716.41,727.5,3098300 -2012-09-20,724.47,731.38,721.22,728.12,2907400 -2012-09-21,732.21,734.92,730.12,733.99,6359100 -2012-09-24,731,750.04,730.25,749.38,3563800 -2012-09-25,753.05,764.89,747.66,749.16,6058500 -2012-09-26,749.85,761.24,741,753.46,5672900 -2012-09-27,759.95,762.84,751.65,756.5,3931100 -2012-09-28,754.15,759.3,751.15,754.5,2783500 -2012-10-01,759.05,765,756.21,761.78,3168000 -2012-10-02,765.2,765.99,750.27,756.99,2790200 -2012-10-03,755.72,763.92,752.2,762.5,2208300 -2012-10-04,762.75,769.89,759.4,768.05,2454200 -2012-10-05,770.71,774.38,765.01,767.65,2735900 -2012-10-08,761,763.58,754.15,757.84,1958600 -2012-10-09,759.67,761.32,742.53,744.09,3003200 -2012-10-10,741.86,747.53,738.29,744.56,2039900 -2012-10-11,752.9,758.5,750.29,751.48,2383900 -2012-10-12,751.85,754.87,744.1,744.75,2404200 -2012-10-15,741.94,743.83,730.7,740.98,3019100 -2012-10-16,740.13,746.99,736.46,744.7,2058200 -2012-10-17,743.95,756.34,740.26,755.49,2292900 -2012-10-18,755.54,759.42,676,695,12442400 -2012-10-19,705.58,706.7,672,681.79,11482200 -2012-10-22,681.01,684.63,669.7,678.67,4055600 -2012-10-23,672.01,687.33,672,680.35,2916600 -2012-10-24,686.8,687,675.27,677.3,2496500 -2012-10-25,680,682,673.51,677.76,2401100 -2012-10-26,676.5,683.03,671.2,675.15,1950800 -2012-10-31,679.86,681,675,680.3,1537000 -2012-11-01,679.5,690.9,678.72,687.59,2050100 -2012-11-02,694.79,695.55,687.37,687.92,2324400 -2012-11-05,684.5,686.86,675.56,682.96,1635900 -2012-11-06,685.48,686.5,677.55,681.72,1582800 -2012-11-07,675,678.23,666.49,667.12,2232300 -2012-11-08,670.2,671.49,651.23,652.29,2597000 -2012-11-09,654.65,668.34,650.3,663.03,3114100 -2012-11-12,663.75,669.8,660.87,665.9,1405900 -2012-11-13,663,667.6,658.23,659.05,1594200 -2012-11-14,660.66,662.18,650.5,652.55,1668400 -2012-11-15,650,660,643.9,647.26,1848900 -2012-11-16,645.99,653.02,636,647.18,3438200 -2012-11-19,655.7,668.92,655.53,668.21,2368200 -2012-11-20,669.51,678,664.57,669.97,2088700 -2012-11-21,668.99,669.8,660.4,665.87,2112200 -2012-11-23,669.97,670,666.1,667.97,922500 -2012-11-26,666.44,667,659.02,661.15,2204600 -2012-11-27,660.17,675,658,670.71,2508700 -2012-11-28,668.01,684.91,663.89,683.67,3042000 -2012-11-29,687.78,693.9,682,691.89,2776500 -2012-11-30,691.31,699.22,685.69,698.37,3163600 -2012-12-03,702.24,705.89,694.11,695.25,2192500 -2012-12-04,695,695.51,685.7,691.03,1991700 -2012-12-05,692.15,694.5,682.33,687.82,1862400 -2012-12-06,687.59,695.61,684.51,691.13,1462300 -2012-12-07,695,696.88,682.42,684.21,1919300 -2012-12-10,685.39,691.65,683.79,685.42,1366700 -2012-12-11,690,701.92,687.72,696.88,2687600 -2012-12-12,699.23,703.51,693.48,697.56,2426000 -2012-12-13,715.92,716.47,699.55,702.7,3444900 -2012-12-14,699.17,707.82,698.43,701.96,2130100 -2012-12-17,705.5,721.92,704.02,720.78,3035400 -2012-12-18,716.6,729.1,715.05,721.07,3004900 -2012-12-19,720.71,723,716.68,720.11,1918600 -2012-12-20,723.26,724.65,716.97,722.36,1657000 -2012-12-21,713.97,718.82,710.52,715.63,3526000 -2012-12-24,714.51,715.18,707.47,709.5,840900 -2012-12-26,708.07,712.88,702.41,708.87,1182400 -2012-12-27,707.14,708.84,698.61,706.29,1647400 -2012-12-28,701.69,706.91,700.01,700.01,1402000 -2012-12-31,700,710.57,696,707.38,1997400 -2013-01-02,719.42,727,716.55,723.25,2541300 -2013-01-03,724.93,731.93,720.72,723.67,2318200 -2013-01-04,729.34,741.47,727.68,737.97,2763500 -2013-01-07,735.45,739.38,730.58,734.75,1655700 -2013-01-08,735.54,736.3,724.43,733.3,1676100 -2013-01-09,732.27,738.35,728.6,738.12,2024700 -2013-01-10,742.83,745,733.5,741.48,1835700 -2013-01-11,742,742.43,736.3,739.99,1285200 -2013-01-14,737,742.2,722.35,723.25,2863900 -2013-01-15,719.33,735,712.1,724.93,3927700 -2013-01-16,722.4,724.34,713.67,715.19,2023400 -2013-01-17,717.71,719.64,711.02,711.32,2211500 -2013-01-18,710.36,712.77,701.33,704.51,3226800 -2013-01-22,704.66,705.34,695.52,702.87,3792400 -2013-01-23,735.99,749,735.79,741.5,5909100 -2013-01-24,741.24,756.83,740.51,754.21,3382700 -2013-01-25,750.77,758.48,750.25,753.67,2225900 -2013-01-28,751.76,755.6,747.89,750.73,1627100 -2013-01-29,746.75,756.95,746.54,753.68,1747100 -2013-01-30,753.74,760.95,752.91,753.83,1733000 -2013-01-31,750.51,757.62,750.25,755.69,1634200 -2013-02-01,758.2,776.6,758.1,775.6,3746100 -2013-02-04,767.69,770.47,758.27,759.02,3040500 -2013-02-05,761.13,771.11,759.47,765.74,1870700 -2013-02-06,759.07,772.96,758.5,770.17,2078100 -2013-02-07,769.7,778.81,765.5,773.95,2840200 -2013-02-08,780.13,786.67,779.56,785.37,3020100 -2013-02-11,778.4,783,773.75,782.42,2167700 -2013-02-12,781.75,787.9,779.37,780.7,1859000 -2013-02-13,780.13,785.35,779.97,782.86,1198200 -2013-02-14,779.73,788.74,777.77,787.82,1735300 -2013-02-15,787.4,793.26,787.07,792.89,2729800 -2013-02-19,795.99,807,795.28,806.85,2931800 -2013-02-20,805.3,808.97,791.79,792.46,2764200 -2013-02-21,798,805.45,791.22,795.53,3506400 -2013-02-22,799.26,801.25,793.8,799.71,2053900 -2013-02-25,802.3,808.41,790.49,790.77,2303900 -2013-02-26,795,795.95,784.4,790.13,2202500 -2013-02-27,794.8,804.75,791.11,799.78,2026100 -2013-02-28,801.1,806.99,801.03,801.2,2265800 -2013-03-01,797.8,807.14,796.15,806.19,2175400 diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py index 4893ffd..e69de29 100644 --- a/tests/unit/__init__.py +++ b/tests/unit/__init__.py @@ -1,29 +0,0 @@ -"""Data and utilities for testing.""" - -import pandas as pd - - -def _read_file(filename): - from os.path import dirname, join - - # df.index = pd.to_datetime(df.index, format="%Y%m%d %H:%M:%S.%f") - - return pd.read_csv( - join(dirname(__file__), filename), - index_col=0, - parse_dates=True - ) - - -GOOG = _read_file("GOOG.csv") -"""DataFrame of daily NASDAQ:GOOG (Google/Alphabet) stock price data from 2004 to 2013.""" - -EURUSD = _read_file("EURUSD.csv") -"""DataFrame of hourly EUR/USD forex data from April 2017 to February 2018.""" - - -def SMA(arr: pd.Series, n: int) -> pd.Series: - """ - Returns `n`-period simple moving average of array `arr`. - """ - return pd.Series(arr).rolling(n).mean() diff --git a/tests/unit/__main__.py b/tests/unit/__main__.py deleted file mode 100644 index 88a4fb9..0000000 --- a/tests/unit/__main__.py +++ /dev/null @@ -1,7 +0,0 @@ -import sys -import unittest - -suite = unittest.defaultTestLoader.discover("backtesting.test", pattern="_test*.py") -if __name__ == "__main__": - result = unittest.TextTestRunner(verbosity=2).run(suite) - sys.exit(not result.wasSuccessful()) diff --git a/tests/unit/assets/EURGBP-2024-05_1Min.csv b/tests/unit/assets/EURGBP-2024-05_1Min.csv new file mode 100644 index 0000000..15948e3 --- /dev/null +++ b/tests/unit/assets/EURGBP-2024-05_1Min.csv @@ -0,0 +1,44461 @@ +Timestamp,open,high,low,close +2024-05-01 00:00:00,0.85401,0.85405,0.85397,0.85403 +2024-05-01 00:01:00,0.85402,0.85404,0.85392,0.85403 +2024-05-01 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20:00:00,1.27439,1.27443,1.274,1.27439 +2024-05-31 20:05:00,1.27439,1.27439,1.27414,1.27433 +2024-05-31 20:10:00,1.27434,1.27454,1.27423,1.27454 +2024-05-31 20:15:00,1.27453,1.27453,1.27436,1.27445 +2024-05-31 20:20:00,1.27441,1.2745,1.27432,1.27441 +2024-05-31 20:25:00,1.27441,1.27443,1.27424,1.2743 +2024-05-31 20:30:00,1.2743,1.27443,1.27418,1.27438 +2024-05-31 20:35:00,1.2743,1.2744,1.27419,1.27438 +2024-05-31 20:40:00,1.27429,1.27442,1.274,1.27428 +2024-05-31 20:45:00,1.274,1.27438,1.27393,1.27429 +2024-05-31 20:50:00,1.27399,1.27431,1.27357,1.2736 +2024-05-31 20:55:00,1.27419,1.2743,1.27352,1.27408 diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py new file mode 100644 index 0000000..640dd9d --- /dev/null +++ b/tests/unit/conftest.py @@ -0,0 +1,95 @@ +import pytest +from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData +from fx_lib.models.indicator import Indicator +from fx_lib.models.instruments import IInstrumentData +from fx_lib.events.event import Event +from fx_lib.models.instruments import Instrument, Granularity +import pandas as pd +import numpy as np + +class TestIndicator(Indicator): + + def _run(self, *args, **kwargs): + return self._data.values.flatten() + +class TestData(IInstrumentData): + + def __init__( + self, data: pd.DataFrame + ): + self._data = data + self.__update_event = Event() + + @property + def df(self): + return self._data + + @property + def on_update(self): + return self.__update_event + + @on_update.setter + def on_update(self, value: Event): + self.__update_event = value + +@pytest.fixture(scope="module") +def data(): + return np.array([1, 2, 3, 4, 5]) + +@pytest.fixture(scope="module") +def instrument_data(data): + df = pd.DataFrame(data) + return TestData(df) + +@pytest.fixture(scope="module") +def indicator(instrument_data): + return TestIndicator(instrument_data) + +@pytest.fixture(scope="module") +def test_csv_sources() -> list[CsvDataSource]: + return [ + # CsvDataSource( + # "tests/unit/assets/EURGBP-2024-05_1Min.csv", + # Instrument.EURGBP, + # Granularity.M1 + # ), + # CsvDataSource( + # "tests/unit/assets/EURJPY-2024-05_1Min.csv", + # Instrument.EURJPY, + # Granularity.M1 + # ), + CsvDataSource( + "tests/unit/assets/EURUSD-2024-05_1Min.csv", + Instrument.EURUSD, + Granularity.M1 + ), + # CsvDataSource( + # "tests/unit/assets/GBPUSD-2024-05_1Min.csv", + # Instrument.GBPUSD, + # Granularity.M1 + # ), + # CsvDataSource( + # "tests/unit/assets/EURGBP-2024-05_5Min.csv", + # Instrument.EURGBP, + # Granularity.M5 + # ), + # CsvDataSource( + # "tests/unit/assets/EURJPY-2024-05_5Min.csv", + # Instrument.EURJPY, + # Granularity.M5 + # ), + CsvDataSource( + "tests/unit/assets/EURUSD-2024-05_5Min.csv", + Instrument.EURUSD, + Granularity.M5 + ), + # CsvDataSource( + # "tests/unit/assets/GBPUSD-2024-05_5Min.csv", + # Instrument.GBPUSD, + # Granularity.M5 + # ), + ] + +@pytest.fixture(scope="module") +def test_universe(test_csv_sources): + return MarketData(CsvMarketDataLoader(test_csv_sources)) \ No newline at end of file diff --git a/tests/unit/test_backtest.py b/tests/unit/test_backtest.py index 0d34e41..8f290f2 100644 --- a/tests/unit/test_backtest.py +++ b/tests/unit/test_backtest.py @@ -1,1057 +1,55 @@ -import inspect -import os -import sys -import time -import unittest -import warnings -from concurrent.futures.process import ProcessPoolExecutor -from contextlib import contextmanager -from glob import glob -from runpy import run_path -from tempfile import NamedTemporaryFile, gettempdir -from unittest import TestCase from unittest.mock import patch -import numpy as np -import pandas as pd -from pandas.testing import assert_frame_equal - -from fx_backtest import Backtest, Strategy -from fx_backtest._stats import compute_drawdown_duration_peaks -from fx_backtest._util import _Array, _as_str, _Indicator, try_ -from fx_backtest.lib import ( - OHLCV_AGG, - SignalStrategy, - TrailingStrategy, - barssince, - compute_stats, - cross, - crossover, - plot_heatmaps, - quantile, - random_ohlc_data, - resample_apply, +import pytest +from fx_backtest.backtest import Backtest +from fx_lib.models.indicator import Indicator +from fx_lib.strategy import FxStrategy +from fx_lib.models.instruments import ( + CandleSubscription, + Instrument, + Granularity ) -from . import EURUSD, GOOG, SMA - -SHORT_DATA = GOOG.iloc[:20] # Short data for fast tests with no indicator lag - - -@contextmanager -def _tempfile(): - with NamedTemporaryFile(suffix=".html") as f: - if sys.platform.startswith("win"): - f.close() - yield f.name - - -@contextmanager -def chdir(path): - cwd = os.getcwd() - os.chdir(path) - try: - yield - finally: - os.chdir(cwd) - - -class SmaCross(Strategy): - # NOTE: These values are also used on the website! - fast = 10 - slow = 30 - - def init(self): - self.sma1 = self.I(SMA, self.data.Close, self.fast) - self.sma2 = self.I(SMA, self.data.Close, self.slow) - - def next(self): - if crossover(self.sma1, self.sma2): - self.position.close() - self.buy() - elif crossover(self.sma2, self.sma1): - self.position.close() - self.sell() - - -class TestBacktest(TestCase): - def test_run(self): - bt = Backtest(EURUSD, SmaCross) - bt.run() - - def test_run_invalid_param(self): - bt = Backtest(GOOG, SmaCross) - self.assertRaises(AttributeError, bt.run, foo=3) - - def test_run_speed(self): - bt = Backtest(GOOG, SmaCross) - start = time.process_time() - bt.run() - end = time.process_time() - self.assertLess(end - start, 0.3) - - def test_data_missing_columns(self): - df = GOOG.copy(deep=False) - del df["Open"] - with self.assertRaises(ValueError): - Backtest(df, SmaCross).run() - - def test_data_nan_columns(self): - df = GOOG.copy() - df["Open"] = np.nan - with self.assertRaises(ValueError): - Backtest(df, SmaCross).run() - - def test_data_extra_columns(self): - df = GOOG.copy(deep=False) - df["P/E"] = np.arange(len(df)) - df["MCap"] = np.arange(len(df)) - - class S(Strategy): - def init(self): - assert len(self.data.MCap) == len(self.data.Close) - assert len(self.data["P/E"]) == len(self.data.Close) - - def next(self): - assert len(self.data.MCap) == len(self.data.Close) - assert len(self.data["P/E"]) == len(self.data.Close) - - Backtest(df, S).run() - - def test_data_invalid(self): - with self.assertRaises(TypeError): - Backtest(GOOG.index, SmaCross).run() - with self.assertRaises(ValueError): - Backtest(GOOG.iloc[:0], SmaCross).run() - - def test_assertions(self): - class Assertive(Strategy): - def init(self): - self.sma = self.I(SMA, self.data.Close, 10) - self.remains_indicator = ( - np.r_[2] * np.cumsum(self.sma * 5 + 1) * np.r_[2] - ) - - self.transpose_invalid = self.I( - lambda: np.column_stack((self.data.Open, self.data.Close)) - ) - - resampled = resample_apply("W", SMA, self.data.Close, 3) - resampled_ind = resample_apply("W", SMA, self.sma, 3) - assert np.unique(resampled[-5:]).size == 1 - assert np.unique(resampled[-6:]).size == 2 - assert resampled in self._indicators, "Strategy.I not called" - assert resampled_ind in self._indicators, "Strategy.I not called" - - assert 1 == try_(lambda: self.data.X, 1, AttributeError) - assert 1 == try_(lambda: self.data["X"], 1, KeyError) - - assert self.data.pip == 0.01 - - assert float(self.data.Close) == self.data.Close[-1] - - def next(self, _FEW_DAYS=pd.Timedelta("3 days")): # noqa: N803 - assert self.equity >= 0 - - assert isinstance(self.sma, _Indicator) - assert isinstance(self.remains_indicator, _Indicator) - assert self.remains_indicator.name - assert isinstance(self.remains_indicator._opts, dict) - - assert not np.isnan(self.data.Open[-1]) - assert not np.isnan(self.data.High[-1]) - assert not np.isnan(self.data.Low[-1]) - assert not np.isnan(self.data.Close[-1]) - assert not np.isnan(self.data.Volume[-1]) - assert not np.isnan(self.sma[-1]) - assert self.data.index[-1] - - self.position - self.position.size - self.position.pl - self.position.pl_pct - self.position.is_long - - if crossover(self.sma, self.data.Close): - self.orders.cancel() # cancels only non-contingent - price = self.data.Close[-1] - sl, tp = 1.05 * price, 0.9 * price - - n_orders = len(self.orders) - self.sell(size=0.21, limit=price, stop=price, sl=sl, tp=tp) - assert len(self.orders) == n_orders + 1 - - order = self.orders[-1] - assert order.limit == price - assert order.stop == price - assert order.size == -0.21 - assert order.sl == sl - assert order.tp == tp - assert not order.is_contingent - - elif self.position: - assert not self.position.is_long - assert self.position.is_short - assert self.position.pl - assert self.position.pl_pct - assert self.position.size < 0 - - trade = self.trades[0] - if ( - self.data.index[-1] - self.data.index[trade.entry_bar] - > _FEW_DAYS - ): - assert not trade.is_long - assert trade.is_short - assert trade.size < 0 - assert trade.entry_bar > 0 - assert isinstance(trade.entry_time, pd.Timestamp) - assert trade.exit_bar is None - assert trade.exit_time is None - assert trade.entry_price > 0 - assert trade.exit_price is None - assert trade.pl / 1 - assert trade.pl_pct / 1 - assert trade.value > 0 - assert trade.sl - assert trade.tp - # Close multiple times - self.position.close(0.5) - self.position.close(0.5) - self.position.close(0.5) - self.position.close() - self.position.close() - - bt = Backtest(GOOG, Assertive) - with self.assertWarns(UserWarning): - stats = bt.run() - self.assertEqual(stats["# Trades"], 145) - - def test_broker_params(self): - bt = Backtest( - GOOG.iloc[:100], - SmaCross, - cash=1000, - commission=0.01, - margin=0.1, - trade_on_close=True, - ) - bt.run() - - def test_dont_overwrite_data(self): - df = EURUSD.copy() - bt = Backtest(df, SmaCross) - bt.run() - bt.optimize(fast=4, slow=[6, 8]) - bt.plot(plot_drawdown=True, open_browser=False) - self.assertTrue(df.equals(EURUSD)) - - def test_strategy_abstract(self): - class MyStrategy(Strategy): - pass - - self.assertRaises(TypeError, MyStrategy, None, None) - - def test_strategy_str(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - self.assertEqual(str(bt.run()._strategy), SmaCross.__name__) - self.assertEqual( - str(bt.run(fast=11)._strategy), SmaCross.__name__ + "(fast=11)" - ) - - def test_compute_drawdown(self): - dd = pd.Series([0, 1, 7, 0, 4, 0, 0]) - durations, peaks = compute_drawdown_duration_peaks(dd) - np.testing.assert_array_equal( - durations, pd.Series([3, 2], index=[3, 5]).reindex(dd.index) - ) - np.testing.assert_array_equal( - peaks, pd.Series([7, 4], index=[3, 5]).reindex(dd.index) - ) - - def test_compute_stats(self): - stats = Backtest(GOOG, SmaCross).run() - expected = pd.Series( - { - # NOTE: These values are also used on the website! - "# Trades": 66, - "Avg. Drawdown Duration": pd.Timedelta("41 days 00:00:00"), - "Avg. Drawdown [%]": -5.925851581948801, - "Avg. Trade Duration": pd.Timedelta("46 days 00:00:00"), - "Avg. Trade [%]": 2.531715975158555, - "Best Trade [%]": 53.59595229490424, - "Buy & Hold Return [%]": 703.4582419772772, - "Calmar Ratio": 0.4414380935608377, - "Duration": pd.Timedelta("3116 days 00:00:00"), - "End": pd.Timestamp("2013-03-01 00:00:00"), - "Equity Final [$]": 51422.98999999996, - "Equity Peak [$]": 75787.44, - "Expectancy [%]": 3.2748078066748834, - "Exposure Time [%]": 96.74115456238361, - "Max. Drawdown Duration": pd.Timedelta("584 days 00:00:00"), - "Max. Drawdown [%]": -47.98012705007589, - "Max. Trade Duration": pd.Timedelta("183 days 00:00:00"), - "Profit Factor": 2.167945974262033, - "Return (Ann.) [%]": 21.180255813792282, - "Return [%]": 414.2298999999996, - "Volatility (Ann.) [%]": 36.49390889140787, - "SQN": 1.0766187356697705, - "Kelly Criterion": 0.1518705127029717, - "Sharpe Ratio": 0.5803778344714113, - "Sortino Ratio": 1.0847880675854096, - "Start": pd.Timestamp("2004-08-19 00:00:00"), - "Win Rate [%]": 46.96969696969697, - "Worst Trade [%]": -18.39887353835481, - } - ) - - def almost_equal(a, b): - try: - return np.isclose(a, b, rtol=1.0e-8) - except TypeError: - return a == b - - diff = { - key: print(key) or value # noqa: T201 - for key, value in stats.filter(regex="^[^_]").items() - if not almost_equal(value, expected[key]) - } - self.assertDictEqual(diff, {}) - - self.assertSequenceEqual( - sorted(stats["_equity_curve"].columns), - sorted(["Equity", "DrawdownPct", "DrawdownDuration"]), - ) - - self.assertEqual(len(stats["_trades"]), 66) - - self.assertSequenceEqual( - sorted(stats["_trades"].columns), - sorted( - [ - "Size", - "EntryBar", - "ExitBar", - "EntryPrice", - "ExitPrice", - "PnL", - "ReturnPct", - "EntryTime", - "ExitTime", - "Duration", - "StopLoss", - "Tag", - "TakeProfit", - ] - ), - ) - - def test_compute_stats_bordercase(self): - - class SingleTrade(Strategy): - def init(self): - self._done = False - - def next(self): - if not self._done: - self.buy() - self._done = True - if self.position: - self.position.close() - - class SinglePosition(Strategy): - def init(self): - pass - - def next(self): - if not self.position: - self.buy() - - class NoTrade(Strategy): - def init(self): - pass - - def next(self): - pass - - for strategy in (SmaCross, SingleTrade, SinglePosition, NoTrade): - with self.subTest(strategy=strategy.__name__): - stats = Backtest(GOOG.iloc[:100], strategy).run() - - self.assertFalse(np.isnan(stats["Equity Final [$]"])) - self.assertFalse(stats["_equity_curve"]["Equity"].isnull().any()) - self.assertEqual(stats["_strategy"].__class__, strategy) - - def test_trade_enter_hit_sl_on_same_day(self): - the_day = pd.Timestamp("2012-10-17 00:00:00") - - class S(Strategy): - def init(self): - pass - - def next(self): - if self.data.index[-1] == the_day: - self.buy(sl=720) - - self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].ExitPrice, 720) - - class S(S): - def next(self): - if self.data.index[-1] == the_day: - self.buy(stop=758, sl=720) - - with self.assertWarns(UserWarning): - self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].ExitPrice, 705.58) - - def test_stop_price_between_sl_tp(self): - class S(Strategy): - def init(self): - pass - - def next(self): - if self.data.index[-1] == pd.Timestamp("2004-09-09 00:00:00"): - self.buy(stop=104, sl=103, tp=110) - - with self.assertWarns(UserWarning): - self.assertEqual(Backtest(GOOG, S).run()._trades.iloc[0].EntryPrice, 104) - - def test_position_close_portion(self): - class SmaCross(Strategy): - def init(self): - self.sma1 = self.I(SMA, self.data.Close, 10) - self.sma2 = self.I(SMA, self.data.Close, 20) - - def next(self): - if not self.position and crossover(self.sma1, self.sma2): - self.buy(size=10) - if self.position and crossover(self.sma2, self.sma1): - self.position.close(portion=0.5) - - bt = Backtest(GOOG, SmaCross, commission=0.002) - bt.run() - - def test_close_orders_from_last_strategy_iteration(self): - class S(Strategy): - def init(self): - pass - - def next(self): - if not self.position: - self.buy() - elif len(self.data) == len(SHORT_DATA): - self.position.close() - - self.assertFalse(Backtest(SHORT_DATA, S).run()._trades.empty) - - def test_check_adjusted_price_when_placing_order(self): - class S(Strategy): - def init(self): - pass - - def next(self): - self.buy(tp=self.data.Close * 1.01) - - self.assertRaises(ValueError, Backtest(SHORT_DATA, S, commission=0.02).run) - - -class TestStrategy(TestCase): - def _Backtest(self, strategy_coroutine, **kwargs): - class S(Strategy): - def init(self): - self.step = strategy_coroutine(self) - - def next(self): - try_(self.step.__next__, None, StopIteration) - - return Backtest(SHORT_DATA, S, **kwargs) - - def test_position(self): - def coroutine(self): - yield self.buy() - - assert self.position - assert self.position.is_long - assert not self.position.is_short - assert self.position.size > 0 - assert self.position.pl - assert self.position.pl_pct - - yield self.position.close() - - assert not self.position - assert not self.position.is_long - assert not self.position.is_short - assert not self.position.size - assert not self.position.pl - assert not self.position.pl_pct - - self._Backtest(coroutine).run() - - def test_broker_hedging(self): - def coroutine(self): - yield self.buy(size=2) - - assert len(self.trades) == 1 - yield self.sell(size=1) - - assert len(self.trades) == 2 - - self._Backtest(coroutine, hedging=True).run() - - def test_broker_exclusive_orders(self): - def coroutine(self): - yield self.buy(size=2) - - assert len(self.trades) == 1 - yield self.sell(size=3) - - assert len(self.trades) == 1 - assert self.trades[0].size == -3 - - self._Backtest(coroutine, exclusive_orders=True).run() - - def test_trade_multiple_close(self): - def coroutine(self): - yield self.buy() - - assert self.trades - self.trades[-1].close(1) - self.trades[-1].close(0.1) - yield - - self._Backtest(coroutine).run() - - def test_close_trade_leaves_needsize_0(self): - def coroutine(self): - self.buy(size=1) - self.buy(size=1) - yield - if self.position: - self.sell(size=1) - - self._Backtest(coroutine).run() - - def test_stop_limit_order_price_is_stop_price(self): - def coroutine(self): - self.buy(stop=112, limit=113, size=1) - self.sell(stop=107, limit=105, size=1) - yield - - stats = self._Backtest(coroutine).run() - self.assertListEqual( - stats._trades.filter(like="Price").stack().tolist(), [112, 107] - ) - - def test_autoclose_trades_on_finish(self): - def coroutine(self): - yield self.buy() - - stats = self._Backtest(coroutine).run() - self.assertEqual(len(stats._trades), 1) - - def test_order_tag(self): - def coroutine(self): - yield self.buy(size=2, tag=1) - yield self.sell(size=1, tag="s") - yield self.sell(size=1) - - yield self.buy(tag=2) - yield self.position.close() - - stats = self._Backtest(coroutine).run() - self.assertEqual(list(stats._trades.Tag), [1, 1, 2]) - - -class TestOptimize(TestCase): - def test_optimize(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - OPT_PARAMS = {"fast": range(2, 5, 2), "slow": [2, 5, 7, 9]} - - self.assertRaises(ValueError, bt.optimize) - self.assertRaises(ValueError, bt.optimize, maximize="missing key", **OPT_PARAMS) - self.assertRaises(ValueError, bt.optimize, maximize="missing key", **OPT_PARAMS) - self.assertRaises(TypeError, bt.optimize, maximize=15, **OPT_PARAMS) - self.assertRaises(TypeError, bt.optimize, constraint=15, **OPT_PARAMS) - self.assertRaises( - ValueError, bt.optimize, constraint=lambda d: False, **OPT_PARAMS - ) - self.assertRaises( - ValueError, bt.optimize, return_optimization=True, **OPT_PARAMS - ) - - res = bt.optimize(**OPT_PARAMS) - self.assertIsInstance(res, pd.Series) - - default_maximize = ( - inspect.signature(Backtest.optimize).parameters["maximize"].default - ) - res2 = bt.optimize(**OPT_PARAMS, maximize=lambda s: s[default_maximize]) - self.assertDictEqual( - res.filter(regex="^[^_]").fillna(-1).to_dict(), - res2.filter(regex="^[^_]").fillna(-1).to_dict(), - ) - - res3, heatmap = bt.optimize( - **OPT_PARAMS, return_heatmap=True, constraint=lambda d: d.slow > 2 * d.fast - ) - self.assertIsInstance(heatmap, pd.Series) - self.assertEqual(len(heatmap), 4) - self.assertEqual(heatmap.name, default_maximize) - - with _tempfile() as f: - bt.plot(filename=f, open_browser=False) - - def test_method_skopt(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - res, heatmap, skopt_results = bt.optimize( - fast=range(2, 20), - slow=np.arange(2, 20, dtype=object), - constraint=lambda p: p.fast < p.slow, - max_tries=30, - method="skopt", - return_optimization=True, - return_heatmap=True, - random_state=2, - ) - self.assertIsInstance(res, pd.Series) - self.assertIsInstance(heatmap, pd.Series) - self.assertGreater(heatmap.max(), 1.1) - self.assertGreater(heatmap.min(), -2) - self.assertEqual(-skopt_results.fun, heatmap.max()) - self.assertEqual( - heatmap.index.tolist(), heatmap.dropna().index.unique().tolist() - ) - - def test_max_tries(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - OPT_PARAMS = {"fast": range(2, 10, 2), "slow": [2, 5, 7, 9]} - for method, max_tries, random_state in ( - ("grid", 5, 0), - ("grid", 0.3, 0), - ("skopt", 7, 0), - ("skopt", 0.45, 0), - ): - with self.subTest( - method=method, max_tries=max_tries, random_state=random_state - ): - _, heatmap = bt.optimize( - max_tries=max_tries, - method=method, - random_state=random_state, - return_heatmap=True, - **OPT_PARAMS - ) - self.assertEqual(len(heatmap), 6) - - def test_nowrite_df(self): - # Test we don't write into passed data df by default. - # Important for copy-on-write in Backtest.optimize() - df = EURUSD.astype(float) - _df = df.copy(deep=True) - assert _df.equals(df) - - class S(SmaCross): - def init(self): - super().init() - assert _df.equals(self.data.df) - - bt = Backtest(df, S) - _ = bt.run() - assert _df.equals(bt._data) - - def test_multiprocessing_windows_spawn(self): - df = GOOG.iloc[:100] - kw = {"fast": [10]} - - stats1 = Backtest(df, SmaCross).optimize(**kw) - with patch("multiprocessing.get_start_method", lambda **_: "spawn"): - with self.assertWarns(UserWarning) as cm: - stats2 = Backtest(df, SmaCross).optimize(**kw) - - self.assertIn("multiprocessing support", cm.warning.args[0]) - assert stats1.filter(["^_"]).equals(stats2.filter(["^_"])), (stats1, stats2) - - def test_optimize_invalid_param(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - self.assertRaises(AttributeError, bt.optimize, foo=range(3)) - self.assertRaises(ValueError, bt.optimize, fast=[]) - - def test_optimize_no_trades(self): - bt = Backtest(GOOG, SmaCross) - stats = bt.optimize(fast=[3], slow=[3]) - self.assertTrue(stats.isnull().any()) - - def test_optimize_speed(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - start = time.process_time() - bt.optimize(fast=(2, 5, 7), slow=[10, 15, 20, 30]) - end = time.process_time() - self.assertLess(end - start, 0.2) - - -class TestPlot(TestCase): - def test_plot_before_run(self): - bt = Backtest(GOOG, SmaCross) - self.assertRaises(RuntimeError, bt.plot) - - def test_file_size(self): - bt = Backtest(GOOG, SmaCross) - bt.run() - with _tempfile() as f: - bt.plot(filename=f[: -len(".html")], open_browser=False) - self.assertLess(os.path.getsize(f), 500000) - - def test_params(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - bt.run() - with _tempfile() as f: - for p in dict( - plot_volume=False, # noqa: C408 - plot_equity=False, - plot_return=True, - plot_pl=False, - plot_drawdown=True, - plot_trades=False, - superimpose=False, - resample="1W", - smooth_equity=False, - relative_equity=False, - reverse_indicators=True, - show_legend=False, - ).items(): - with self.subTest(param=p[0]): - bt.plot(**dict([p]), filename=f, open_browser=False) - - def test_hide_legend(self): - bt = Backtest(GOOG.iloc[:100], SmaCross) - bt.run() - with _tempfile() as f: - bt.plot(filename=f, show_legend=False) - # Give browser time to open before tempfile is removed - time.sleep(5) - - def test_resolutions(self): - with _tempfile() as f: - for rule in "LSTHDWM": - with self.subTest(rule=rule): - df = ( - EURUSD.iloc[:2] - .resample(rule) - .agg(OHLCV_AGG) - .dropna() - .iloc[:1100] - ) - bt = Backtest(df, SmaCross) - bt.run() - bt.plot(filename=f, open_browser=False) - - def test_range_axis(self): - df = GOOG.iloc[:100].reset_index(drop=True) - - # Warm-up. CPython bug bpo-29620. - try: - with self.assertWarns(UserWarning): - Backtest(df, SmaCross) - except RuntimeError: - pass - - with self.assertWarns(UserWarning): - bt = Backtest(df, SmaCross) - bt.run() - with _tempfile() as f: - bt.plot(filename=f, open_browser=False) - - def test_preview(self): - class Strategy(SmaCross): - def init(self): - super().init() - - def ok(x): - return x - - self.a = self.I(SMA, self.data.Open, 5, overlay=False, name="ok") - self.b = self.I(ok, np.random.random(len(self.data.Open))) - - bt = Backtest(GOOG, Strategy) - bt.run() - with _tempfile() as f: - bt.plot(filename=f, plot_drawdown=True, smooth_equity=True) - # Give browser time to open before tempfile is removed - time.sleep(5) - - def test_wellknown(self): - class S(Strategy): - def init(self): - pass - - def next(self): - date = self.data.index[-1] - if date == pd.Timestamp("Thu 19 Oct 2006"): - self.buy(stop=484, limit=466, size=100) - elif date == pd.Timestamp("Thu 30 Oct 2007"): - self.position.close() - elif date == pd.Timestamp("Tue 11 Nov 2008"): - self.sell( - stop=self.data.Low, limit=324.90, size=200 # High from 14 Nov - ) - - bt = Backtest(GOOG, S, margin=0.1) - stats = bt.run() - trades = stats["_trades"] - - self.assertAlmostEqual(stats["Equity Peak [$]"], 46961) - self.assertEqual(stats["Equity Final [$]"], 0) - self.assertEqual(len(trades), 2) - assert trades[["EntryTime", "ExitTime"]].equals( - pd.DataFrame( - { - "EntryTime": pd.to_datetime(["2006-11-01", "2008-11-14"]), - "ExitTime": pd.to_datetime(["2007-10-31", "2009-09-21"]), - } - ) - ) - assert trades["PnL"].round().equals(pd.Series([23469.0, -34420.0])) - - with _tempfile() as f: - bt.plot(filename=f, plot_drawdown=True, smooth_equity=False) - # Give browser time to open before tempfile is removed - time.sleep(1) - - def test_resample(self): - bt = Backtest(GOOG, SmaCross) - bt.run() - import fx_backtest._plotting - - with _tempfile() as f, patch.object( - fx_backtest._plotting, "_MAX_CANDLES", 10 - ), self.assertWarns(UserWarning): - bt.plot(filename=f, resample=True) - # Give browser time to open before tempfile is removed - time.sleep(1) - - def test_indicator_color(self): - class S(Strategy): - def init(self): - a = self.I(SMA, self.data.Close, 5, overlay=True, color="red") - b = self.I(SMA, self.data.Close, 10, overlay=False, color="blue") - self.I(lambda: (a, b), overlay=False, color=("green", "orange")) - - def next(self): - pass - - bt = Backtest(GOOG, S) - bt.run() - with _tempfile() as f: - bt.plot( - filename=f, - plot_drawdown=False, - plot_equity=False, - plot_pl=False, - plot_volume=False, - open_browser=False, - ) - - def test_indicator_scatter(self): - class S(Strategy): - def init(self): - self.I(SMA, self.data.Close, 5, overlay=True, scatter=True) - self.I(SMA, self.data.Close, 10, overlay=False, scatter=True) - - def next(self): - pass - - bt = Backtest(GOOG, S) - bt.run() - with _tempfile() as f: - bt.plot( - filename=f, - plot_drawdown=False, - plot_equity=False, - plot_pl=False, - plot_volume=False, - open_browser=False, - ) - - -class TestLib(TestCase): - def test_barssince(self): - self.assertEqual(barssince(np.r_[1, 0, 0]), 2) - self.assertEqual(barssince(np.r_[0, 0, 0]), np.inf) - self.assertEqual(barssince(np.r_[0, 0, 0], 0), 0) - - def test_cross(self): - self.assertTrue(cross([0, 1], [1, 0])) - self.assertTrue(cross([1, 0], [0, 1])) - self.assertFalse(cross([1, 0], [1, 0])) - - def test_crossover(self): - self.assertTrue(crossover([0, 1], [1, 0])) - self.assertTrue(crossover([0, 1], 0.5)) - self.assertTrue(crossover([0, 1], pd.Series([0.5, 0.5], index=[5, 6]))) - self.assertFalse(crossover([1, 0], [1, 0])) - self.assertFalse(crossover([0], [1])) - - def test_quantile(self): - self.assertEqual(quantile(np.r_[1, 3, 2], 0.5), 2) - self.assertEqual(quantile(np.r_[1, 3, 2]), 0.5) - - def test_resample_apply(self): - res = resample_apply("D", SMA, EURUSD.Close, 10) - self.assertEqual(res.name, "C[D]") - self.assertEqual(res.count() / res.size, 0.9634) - np.testing.assert_almost_equal( - res.iloc[-48:].unique().tolist(), [1.242643, 1.242381, 1.242275], decimal=6 - ) - - def resets_index(*args): - return pd.Series(SMA(*args).values) - - res2 = resample_apply("D", resets_index, EURUSD.Close, 10) - self.assertTrue((res.dropna() == res2.dropna()).all()) - self.assertTrue((res.index == res2.index).all()) - - res3 = resample_apply("D", None, EURUSD) - self.assertIn("Volume", res3) - - res3 = resample_apply("D", lambda df: (df.Close, df.Close), EURUSD) - self.assertIsInstance(res3, pd.DataFrame) - - def test_plot_heatmaps(self): - bt = Backtest(GOOG, SmaCross) - stats, heatmap = bt.optimize( - fast=range(2, 7, 2), slow=range(7, 15, 2), return_heatmap=True - ) - with _tempfile() as f: - for agg in ("mean", lambda x: np.percentile(x, 75)): - plot_heatmaps(heatmap, agg, filename=f, open_browser=False) - - # Preview - plot_heatmaps(heatmap, filename=f) - time.sleep(5) - - def test_random_ohlc_data(self): - generator = random_ohlc_data(GOOG, frac=1) - new_data = next(generator) - self.assertEqual(list(new_data.index), list(GOOG.index)) - self.assertEqual(new_data.shape, GOOG.shape) - self.assertEqual(list(new_data.columns), list(GOOG.columns)) - - def test_compute_stats(self): - stats = Backtest(GOOG, SmaCross).run() - only_long_trades = stats._trades[stats._trades.Size > 0] - long_stats = compute_stats( - stats=stats, trades=only_long_trades, data=GOOG, risk_free_rate=0.02 - ) - self.assertNotEqual( - list(stats._equity_curve.Equity), list(long_stats._equity_curve.Equity) - ) - self.assertNotEqual(stats["Sharpe Ratio"], long_stats["Sharpe Ratio"]) - self.assertEqual(long_stats["# Trades"], len(only_long_trades)) - self.assertEqual(stats._strategy, long_stats._strategy) - assert_frame_equal(long_stats._trades, only_long_trades) - - def test_SignalStrategy(self): - class S(SignalStrategy): - def init(self): - sma = self.data.Close.s.rolling(10).mean() - self.set_signal(self.data.Close > sma, self.data.Close < sma) - - stats = Backtest(GOOG, S).run() - self.assertIn(stats["# Trades"], (1181, 1182)) # varies on different archs? - - def test_TrailingStrategy(self): - class S(TrailingStrategy): - def init(self): - super().init() - self.set_atr_periods(40) - self.set_trailing_sl(3) - self.sma = self.I(lambda: self.data.Close.s.rolling(10).mean()) - - def next(self): - super().next() - if not self.position and self.data.Close > self.sma: - self.buy() - - stats = Backtest(GOOG, S).run() - self.assertEqual(stats["# Trades"], 57) - - -class TestUtil(TestCase): - def test_as_str(self): - def func(): - pass - - class Class: - def __call__(self): - pass - - self.assertEqual(_as_str("4"), "4") - self.assertEqual(_as_str(4), "4") - self.assertEqual(_as_str(_Indicator([1, 2], name="x")), "x") - self.assertEqual(_as_str(func), "func") - self.assertEqual(_as_str(Class), "Class") - self.assertEqual(_as_str(Class()), "Class") - self.assertEqual(_as_str(pd.Series([1, 2], name="x")), "x") - self.assertEqual(_as_str(pd.DataFrame()), "df") - self.assertEqual(_as_str(lambda x: x), "λ") - for s in ("Open", "High", "Low", "Close", "Volume"): - self.assertEqual(_as_str(_Array([1], name=s)), s[0]) - - def test_pandas_accessors(self): - class S(Strategy): - def init(self): - close, index = self.data.Close, self.data.index - assert close.s.equals(pd.Series(close, index=index)) - assert self.data.df["Close"].equals(pd.Series(close, index=index)) - self.data.df["new_key"] = 2 * close - - def next(self): - close, index = self.data.Close, self.data.index - assert close.s.equals(pd.Series(close, index=index)) - assert self.data.df["Close"].equals(pd.Series(close, index=index)) - assert self.data.df["new_key"].equals( - pd.Series(self.data.new_key, index=index) - ) - - Backtest(GOOG.iloc[:20], S).run() - - def test_indicators_picklable(self): - bt = Backtest(SHORT_DATA, SmaCross) - with ProcessPoolExecutor() as executor: - stats = executor.submit(Backtest.run, bt).result() - assert stats._strategy._indicators[ - 0 - ]._opts, "._opts and .name were not unpickled" - bt.plot(results=stats, resample="2d", open_browser=False) - - -class TestDocs(TestCase): - DOCS_DIR = os.path.join(os.path.dirname(__file__), "..", "..", "doc") - - @unittest.skipUnless(os.path.isdir(DOCS_DIR), "docs dir doesn't exist") - def test_examples(self): - examples = glob(os.path.join(self.DOCS_DIR, "examples", "*.py")) - self.assertGreaterEqual(len(examples), 4) - with chdir(gettempdir()): - for file in examples: - with self.subTest(example=os.path.basename(file)): - run_path(file) - - def test_backtest_run_docstring_contains_stats_keys(self): - stats = Backtest(SHORT_DATA, SmaCross).run() - for key in stats.index: - self.assertIn(key, Backtest.run.__doc__) - - def test_readme_contains_stats_keys(self): - with open( - os.path.join(os.path.dirname(__file__), "..", "..", "README.md") - ) as f: - readme = f.read() - stats = Backtest(SHORT_DATA, SmaCross).run() - for key in stats.index: - self.assertIn(key, readme) - +BACKTEST_INSTRUMENT = Instrument.EURUSD +BACKTEST_GRANULARITY = Granularity.M5 + +class BacktestIndicator(Indicator): + + def _run(self, *args, **kwargs): + return self._data.Open > self._data.Close + +class BacktestStrategy(FxStrategy): + + @property + def subscriptions(self) -> list[CandleSubscription]: + """ + Declare the `InstrumentSubscription`s this strategy should use + for its signals + """ + return [ + CandleSubscription(BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY) + ] + + def _init(self) -> None: + """ + Create indicators to be used for signals in the `_next` method. + """ + data = self.get_data(BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY) + self.test_indicator = BacktestIndicator(data) + + def _next(self) -> None: + """ + Evaluate indicators and submit orders to the broker + """ + if self.test_indicator: + self.sell(1) + else: + self.buy(1) + + +@pytest.mark.asyncio +async def test_backtest_increments_indicator(test_universe): + + test = Backtest(test_universe, BacktestStrategy, 10000) + await test.run() -if __name__ == "__main__": - warnings.filterwarnings("error") - unittest.main() diff --git a/tests/unit/test_data.py b/tests/unit/test_data.py new file mode 100644 index 0000000..affddae --- /dev/null +++ b/tests/unit/test_data.py @@ -0,0 +1,32 @@ +from datetime import datetime +from datetime import timedelta + +from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData +from fx_lib.models.instruments import Instrument, Granularity, Candlestick + +def test_load_market_data(test_universe): + data = test_universe + assert len(data._sources) == 8 + +def test_init_timeframe(test_universe): + data = test_universe + + assert data._index == datetime(2024, 5, 1) + assert data._granularity == timedelta(minutes=1) + +def test_updates(test_universe): + data: MarketData = test_universe + + sources_count = len(data._sources) + + _candles = [] + def _handle_update(candle: Candlestick): + _candles.append(candle) + + for instrument, granularity in data._sources.keys(): + data.subscribe(instrument, granularity, _handle_update) + + for i in range(10): + data.next() + + assert len(_candles) == sources_count * (i + 1) \ No newline at end of file diff --git a/tests/unit/test_default.py b/tests/unit/test_default.py new file mode 100644 index 0000000..47d4f19 --- /dev/null +++ b/tests/unit/test_default.py @@ -0,0 +1,2 @@ +def test_default(): + assert True diff --git a/tests/unit/test_indicator.py b/tests/unit/test_indicator.py new file mode 100644 index 0000000..270e880 --- /dev/null +++ b/tests/unit/test_indicator.py @@ -0,0 +1,14 @@ +from fx_lib.models.indicator import Indicator +import numpy as np + +from fx_backtest.data import MarketData + +def test_indicator_values(data: np.ndarray, indicator: Indicator): + assert len(indicator._values) == len(data) + assert (indicator._values == data).all() + + +def test_indicator_updates(test_universe: MarketData, indicator: Indicator): + data_c + while test_universe.next(): + pass \ No newline at end of file diff --git a/tests/unit/test_strategy.py b/tests/unit/test_strategy.py new file mode 100644 index 0000000..5410af4 --- /dev/null +++ b/tests/unit/test_strategy.py @@ -0,0 +1,109 @@ +from unittest.mock import patch + +import pandas as pd +import pytest +from fx_backtest.backtest import Backtest +from fx_lib.models.indicator import Indicator +from fx_lib.strategy import FxStrategy +from fx_lib.models.instruments import ( + CandleSubscription, + Instrument, + Granularity +) + +from fx_backtest.broker import BacktestBroker +from fx_backtest.data import MarketData +from fx_backtest.strategy import BacktestStrategyWrapper + +BACKTEST_INSTRUMENT = Instrument.EURUSD +BACKTEST_GRANULARITY = Granularity.M5 + +class BacktestIndicator(Indicator): + + def _run(self, *args, **kwargs): + return self._data.Open > self._data.Close + +class BacktestStrategy(FxStrategy): + + @property + def subscriptions(self) -> list[CandleSubscription]: + """ + Declare the `InstrumentSubscription`s this strategy should use + for its signals + """ + return [ + CandleSubscription(BACKTEST_INSTRUMENT, Granularity.M1), + CandleSubscription(BACKTEST_INSTRUMENT, Granularity.M5) + ] + + def _init(self) -> None: + """ + Create indicators to be used for signals in the `_next` method. + """ + self.eurusd_m1 = BacktestIndicator(self.get_data(BACKTEST_INSTRUMENT, Granularity.M1)) + self.eurusd_m5 = BacktestIndicator(self.get_data(BACKTEST_INSTRUMENT, Granularity.M5)) + + def _next(self) -> None: + """ + Evaluate indicators and submit orders to the broker + """ + if self.eurusd_m5: + self.sell(1) + else: + self.buy(1) + + +@pytest.mark.asyncio +async def test_strategy_indicator_updates(test_universe: MarketData): + + broker = BacktestBroker(test_universe) + + strategy = BacktestStrategyWrapper(broker, test_universe, BacktestStrategy) + strategy.init() + + m1_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, Granularity.M1)) + m5_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, Granularity.M5)) + indicator_data = { + "eurusd_m1": m1_data, + "eurusd_m5": m5_data + } + expected_indicator_values = { + "eurusd_m1": m1_data.Open > m1_data.Close, + "eurusd_m5": m5_data.Open > m5_data.Close + } + + for attr, indicator in strategy._indicators: + assert len(indicator._values) == len(indicator_data[attr]) + + while test_universe.next(): + + await strategy.next() + for attr, indicator in strategy._indicators: + if test_universe.index in indicator._data.df.index: + data_i_index = indicator._data.df.index.get_loc(test_universe.index) + expected_length = data_i_index + 1 + assert len(indicator._values) == expected_length + assert indicator == expected_indicator_values[attr][data_i_index] + +@patch("fx_lib.strategy.FxStrategy.sell") +@patch("fx_lib.strategy.FxStrategy.buy") +@pytest.mark.asyncio +async def test_strategy_indicator_orders(mock_buy, mock_sell, test_universe: MarketData): + + broker = BacktestBroker(test_universe) + + strategy = BacktestStrategyWrapper(broker, test_universe, BacktestStrategy) + strategy.init() + + test_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY)) + + while test_universe.next(): + + await strategy.next() + + expected_buy_calls = test_data[test_data.Open <= test_data.Close].count().Open + expected_sell_calls = test_data[test_data.Open > test_data.Close].count().Open + assert expected_buy_calls + expected_sell_calls == test_data.count().Open + + assert mock_buy.call_count == expected_buy_calls + assert mock_sell.call_count == expected_sell_calls diff --git a/tests/unit/test_utils.py b/tests/unit/test_utils.py new file mode 100644 index 0000000..00b168d --- /dev/null +++ b/tests/unit/test_utils.py @@ -0,0 +1,18 @@ +import os +import pytest + +from fx_backtest.utils import load_csv + + +@pytest.mark.parametrize( + "path,count", + [ + ("tests/unit/assets/EURGBP-2024-05_1Min.csv", 44460), + ("tests/unit/assets/EURJPY-2024-05_1Min.csv", 44460), + ("tests/unit/assets/EURUSD-2024-05_1Min.csv", 44460), + ("tests/unit/assets/GBPUSD-2024-05_1Min.csv", 44460) + ] +) +def test_load_csvs(path, count): + df = load_csv(path, parse_dates=["Timestamp"]) + assert df.shape[0] == count \ No newline at end of file From 6b00568c3706ca6aa187b5db8dff9c7442144c00 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Tue, 7 Jan 2025 06:22:43 -0500 Subject: [PATCH 7/9] Moving fx_backtest from monorepo to individual repo --- .flake8 | 3 +- .github/workflows/build.yml | 26 + .gitmodules | 3 + .vscode/launch.json | 27 + .vscode/settings.json | 16 + Makefile | 4 +- clean | 430 ++++++++ docker/Dockerfile | 2 + fx_backtest/main.py | 17 - fx_backtest/stats.py | 186 ---- makefiles/development.mk | 12 +- poetry.lock | 967 +++++++++--------- pyproject.toml | 10 +- {fx_backtest => pytradebacktest}/__init__.py | 0 {fx_backtest => pytradebacktest}/backtest.py | 15 +- {fx_backtest => pytradebacktest}/broker.py | 14 +- {fx_backtest => pytradebacktest}/data.py | 57 +- .../exceptions.py | 0 {fx_backtest => pytradebacktest}/strategy.py | 48 +- {fx_backtest => pytradebacktest}/utils.py | 3 +- scripts/test.sh | 4 +- tests/unit/conftest.py | 95 +- tests/unit/test_backtest.py | 30 +- tests/unit/test_data.py | 36 +- tests/unit/test_default.py | 2 - tests/unit/test_indicator.py | 9 +- tests/unit/test_strategy.py | 72 +- tests/unit/test_utils.py | 19 +- 28 files changed, 1226 insertions(+), 881 deletions(-) create mode 100644 .github/workflows/build.yml create mode 100644 .gitmodules create mode 100644 .vscode/launch.json create mode 100644 .vscode/settings.json create mode 100644 clean delete mode 100644 fx_backtest/main.py delete mode 100644 fx_backtest/stats.py rename {fx_backtest => pytradebacktest}/__init__.py (100%) rename {fx_backtest => pytradebacktest}/backtest.py (75%) rename {fx_backtest => pytradebacktest}/broker.py (77%) rename {fx_backtest => pytradebacktest}/data.py (85%) rename {fx_backtest => pytradebacktest}/exceptions.py (100%) rename {fx_backtest => pytradebacktest}/strategy.py (51%) rename {fx_backtest => pytradebacktest}/utils.py (79%) delete mode 100644 tests/unit/test_default.py diff --git a/.flake8 b/.flake8 index 79a16af..51d5a5c 100644 --- a/.flake8 +++ b/.flake8 @@ -1,2 +1,3 @@ [flake8] -max-line-length = 120 \ No newline at end of file +max-line-length = 120 +extend-ignore = E203 \ No newline at end of file diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml new file mode 100644 index 0000000..f9116b0 --- /dev/null +++ b/.github/workflows/build.yml @@ -0,0 +1,26 @@ +name: Run CI make command + +on: + push: + branches: + - "*" + - "!main" + +env: + REGISTRY: ghcr.io + IMAGE_NAME: ${{ github.repository }} + +jobs: + build: + runs-on: ubuntu-latest + permissions: + contents: read + packages: write + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Build + working-directory: . + run: make ci \ No newline at end of file diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 0000000..9657d8c --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "lib/PyTrade"] + path = lib/PyTrade + url = https://github.com/kylewidmann/PyTrade.git diff --git a/.vscode/launch.json b/.vscode/launch.json new file mode 100644 index 0000000..ed6fff5 --- /dev/null +++ b/.vscode/launch.json @@ -0,0 +1,27 @@ +{ + // Use IntelliSense to learn about possible attributes. + // Hover to view descriptions of existing attributes. + // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387 + "version": "0.2.0", + "configurations": [ + + + { + "name": "Python Debugger: Current File", + "type": "debugpy", + "request": "launch", + "program": "${file}", + "console": "integratedTerminal", + "justMyCode": false + }, + { + "name": "Pytest", + "type": "debugpy", + "request": "launch", + "program": "${file}", + "console": "integratedTerminal", + "purpose": ["debug-test"], + "justMyCode": false + } + ] +} \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..bf7f41d --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,16 @@ +{ + "python.defaultInterpreterPath": "./.venv/bin/python", + "python.testing.pytestArgs": [ + "--ignore=lib" + ], + "python.testing.unittestEnabled": false, + "python.testing.pytestEnabled": true, + "python.terminal.activateEnvironment": true, + "python.terminal.activateEnvInCurrentTerminal": true, + "python.analysis.exclude": [ + "**/.venv", + "**/docker", + "**/mypy_cache", + "**/pytest_cache" + ] +} \ No newline at end of file diff --git a/Makefile b/Makefile index 0ae07ee..984d780 100644 --- a/Makefile +++ b/Makefile @@ -1,12 +1,12 @@ SHELL := /bin/bash -e -o pipefail -PROJECT ?= fx-backtest +PROJECT ?= pytradebacktest BRANCH_NAME ?= local BUILD_NUMBER ?= 0 IMAGE ?= ${PROJECT}:${BRANCH_NAME}-${BUILD_NUMBER} COMPOSE_FILE=docker/docker-compose.yaml COMPOSE_BASE_FILE=docker/docker-compose.base.yaml DC=docker compose -p ${PROJECT} -f ${COMPOSE_FILE} -f ${COMPOSE_BASE_FILE} -SERVICE := fx_backtest +SERVICE := pytradebacktest POETRY ?= "poetry" VERSION := $(shell head VERSION | grep -Eo "\d+.\d+.\d+") diff --git a/clean b/clean new file mode 100644 index 0000000..4957abf --- /dev/null +++ b/clean @@ -0,0 +1,430 @@ +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__ +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__/__init__.cpython-312.pyc +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__/finder.cpython-312.pyc +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__/pyflakes.cpython-312.pyc +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__/reporter.cpython-312.pyc +./.venv/lib/python3.12/site-packages/flake8/plugins/__pycache__/pycodestyle.cpython-312.pyc 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+./.venv/lib/python3.12/site-packages/pluggy/__pycache__/_warnings.cpython-312.pyc +./.venv/lib/python3.12/site-packages/pluggy/__pycache__/_version.cpython-312.pyc +./.venv/lib/python3.12/site-packages/pluggy/__pycache__/_hooks.cpython-312.pyc +./.venv/lib/python3.12/site-packages/pluggy/__pycache__/_tracing.cpython-312.pyc +./.venv/lib/python3.12/site-packages/pluggy/__pycache__/_manager.cpython-312.pyc diff --git a/docker/Dockerfile b/docker/Dockerfile index e0b6bc3..d7aa453 100644 --- a/docker/Dockerfile +++ b/docker/Dockerfile @@ -25,6 +25,7 @@ RUN curl -sSL https://install.python-poetry.org | python3 - \ WORKDIR /app/${PROJECT_DIR} COPY ${PROJECT_DIR}/pyproject.toml ${PROJECT_DIR}/poetry.lock ./ +COPY lib lib/ RUN poetry install --only main ################################################## @@ -74,6 +75,7 @@ RUN set -ex \ WORKDIR /app COPY --chown=${APP_USER}:${APP_GROUP} . ./ RUN poetry install +RUN chown ${APP_USER}:${APP_GROUP} . USER ${APP_USER} ENTRYPOINT ["/app/scripts/entrypoint.sh"] \ No newline at end of file diff --git a/fx_backtest/main.py b/fx_backtest/main.py deleted file mode 100644 index 46d91a0..0000000 --- a/fx_backtest/main.py +++ /dev/null @@ -1,17 +0,0 @@ -import pandas as pd -from fx_strategy.strategy import SlopeMomentum -from fx_lib.models.instruments import Instrument, Granularity - -from fx_backtest.backtest import Backtest -from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData - -test_universe = MarketData(CsvMarketDataLoader([ - CsvDataSource("/home/kyle/Tick_Data/ohlc/2024/February/EURUSD-2024-02_5Min.csv", Instrument.EURUSD, Granularity.M5) -])) -bt = Backtest( - test_universe, SlopeMomentum, 10000, margin=0.02 -) - -stats = bt.run() -bt.plot() -print(stats) diff --git a/fx_backtest/stats.py b/fx_backtest/stats.py deleted file mode 100644 index de7db21..0000000 --- a/fx_backtest/stats.py +++ /dev/null @@ -1,186 +0,0 @@ -from typing import Any -from fx_lib.models.trade import Trade -from fx_lib.strategy import FxStrategy -import numpy as np -import pandas as pd - -from fx_backtest.data import MarketData - -class Stats: - - def __init__( - self, - trades: list[Trade], - equity: np.ndarray, - market_data: MarketData, - strategy: FxStrategy - ): - self._trades = trades - self._equity = equity - self._market_data = market_data - self._strategy = strategy - self._trades_df = pd.DataFrame({ - 'Size': [t.size for t in trades], - 'EntryBar': [t.entry_bar for t in trades], - 'ExitBar': [t.exit_bar for t in trades], - 'EntryPrice': [t.entry_price for t in trades], - 'ExitPrice': [t.exit_price for t in trades], - 'PnL': [t.pl for t in trades], - 'ReturnPct': [t.pl_pct for t in trades], - 'EntryTime': [t.entry_time for t in trades], - 'ExitTime': [t.exit_time for t in trades], - 'Tag': [t.tag for t in trades], - 'TakeProfit': [t.tp for t in trades], - 'StopLoss': [t.sl for t in trades] - }) - self._trades_df['Duration'] = self._trades_df['ExitTime'] - self._trades_df['EntryTime'] - - @property - def drawdown(self) -> np.ndarray[np.floating[Any]]: - if not self._drawdown: - self._drawdown = 1 - self._equity / np.maximum.accumulate(self._equity) - return self._drawdown - - @property - def drawdown_duration(self): - iloc = np.unique(np.r_[(self.drawdown == 0).values.nonzero()[0], len(self.drawdown) - 1]) - iloc = pd.Series(iloc, index=self.drawdown.index[iloc]) - df = iloc.to_frame('iloc').assign(prev=iloc.shift()) - df = df[df['iloc'] > df['prev'] + 1].astype(int) - - # If no drawdown since no trade, avoid below for pandas sake and return nan series - if not len(df): - return (self.drawdown.replace(0, np.nan),) * 2 - - # df = df.reindex(self.drawdown.index) - return df['iloc'].map(self.drawdown.index.__getitem__) - df['prev'].map(self.drawdown.index.__getitem__) - - @property - def drawdown_peaks(self): - iloc = np.unique(np.r_[(self.drawdown == 0).values.nonzero()[0], len(self.drawdown) - 1]) - iloc = pd.Series(iloc, index=self.drawdown.index[iloc]) - df = iloc.to_frame('iloc').assign(prev=iloc.shift()) - df = df[df['iloc'] > df['prev'] + 1].astype(int) - - # If no drawdown since no trade, avoid below for pandas sake and return nan series - if not len(df): - return (self.drawdown.replace(0, np.nan),) * 2 - - # df = df.reindex(self.drawdown.index) - return df.apply(lambda row: self.drawdown.iloc[row['prev']:row['iloc'] + 1].max(), axis=1) - - @property - def profit_n_loss(self): - return self._trades_df['PnL'] - - @property - def returns(self): - return self._trades_df['ReturnPct'] - - @property - def durations(self): - return self._trades_df['Duration'] - - @property - def positions(self): - pass - - @property - def exposure_time(self): - pass - - @property - def equity_final(self): - pass - - @property - def equity_peak(self): - pass - - @property - def return_pct(self): - pass - - @property - def buy_and_hold_return(self): - pass - - @property - def annualized_return(self): - pass - - @property - def annualized_volatility(self): - pass - - @property - def sharpe_ratio(self): - pass - - @property - def sortino_ratio(self): - pass - - @property - def calmar_ratio(self): - pass - - @property - def max_drawndown(self): - pass - - @property - def avg_drawdown(self): - pass - - @property - def max_drawdown_duration(self): - pass - - @property - def avg_drawdown_duration(self): - pass - - @property - def number_of_trades(self): - pass - - @property - def win_rate(self): - pass - - @property - def best_trade_return(self): - pass - - @property - def worst_trade_return(self): - pass - - @property - def avg_trade_return(self): - pass - - @property - def max_trade_duration(self): - pass - - @property - def avg_trade_duration(self): - pass - - @property - def profit_factor(self): - pass - - @property - def expectancy(self): - pass - - @property - def SQN(self): - pass - - @property - def kelly_criterion(self): - pass \ No newline at end of file diff --git a/makefiles/development.mk b/makefiles/development.mk index 6ad5571..59c1f55 100644 --- a/makefiles/development.mk +++ b/makefiles/development.mk @@ -7,21 +7,21 @@ venv: buid: ##@development Build the docker images build: prod_image ?= ${PROJECT}:${BRANCH_NAME}-${BUILD_NUMBER} build: dev_image ?= ${PROJECT}_development:${BRANCH_NAME}-${BUILD_NUMBER} -build: args ?= -f docker/Dockerfile --build-arg PROJECT_DIR=${PROJECT} --network=host --build-arg BUILDKIT_INLINE_CACHE=1 +build: args ?= -f docker/Dockerfile --build-arg PROJECT_DIR=. --network=host --build-arg BUILDKIT_INLINE_CACHE=1 build: - DOCKER_BUILDKIT=1 docker build --progress=plain --target production -t ${prod_image} ${args} .. - DOCKER_BUILDKIT=1 docker build --progress=plain --target development -t ${dev_image} --cache-from ${prod_image} ${args} .. + DOCKER_BUILDKIT=1 docker build --progress=plain --target production -t ${prod_image} ${args} . + DOCKER_BUILDKIT=1 docker build --progress=plain --target development -t ${dev_image} --cache-from ${prod_image} ${args} . .PHONY: infrastructure infrastructure: ##@development Set up infrastructure for tests infrastructure: echo "Skipping..." -.PHONY: client +.PHONY: clean clean: ##@development Clean up any dependencies clean: - echo "Skipping..." + find . | grep -E "(/__pycache__$$|\.pyc$$|\.pyo$$)" > $@ || true | xargs rm -rf -.PHONY: config +.PHONY: ci ci: ##@development Run CI pipeline ci: clean build infrastructure lint test clean \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index 4552113..06cc413 100644 --- a/poetry.lock +++ b/poetry.lock @@ -22,13 +22,13 @@ test = ["matplotlib", "scikit-learn", "scikit-optimize", "seaborn"] [[package]] name = "bandit" -version = "1.7.9" +version = "1.8.0" description = "Security oriented static analyser for python code." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "bandit-1.7.9-py3-none-any.whl", hash = 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python-versions = ">=2" files = [ - {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"}, - {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"}, + {file = "tzdata-2024.2-py2.py3-none-any.whl", hash = "sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd"}, + {file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"}, ] [[package]] @@ -1199,4 +1208,4 @@ files = [ [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "5364ddbedcb5426d47ee9167e9354bafdd764006e605457fda1e936d7b832e9f" +content-hash = "c28e465d2f7d12b2b6d71c9f702d542d60285ce7067c5433f25b4a4e711b1448" diff --git a/pyproject.toml b/pyproject.toml index b04a7a5..16eb616 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,19 +1,15 @@ [tool.poetry] -name = "fx-backtest" +name = "pytradebacktest" version = "0.1.0" description = "" authors = ["Kyle Widmann "] readme = "README.md" -packages = [ - {include = "fx_backtest"} -] [tool.poetry.dependencies] python = "^3.10" -fx-lib = {path = "../fx-lib", develop = true} -fx-strategy = {path = "../fx-strategy", develop = true} +pytrade = {path = "lib/PyTrade", develop = true} pandas = "^2.2.2" -pytest-asyncio = "^0.24.0" +pytest-asyncio = "^0.25.1" [tool.poetry.group.dev.dependencies] diff --git a/fx_backtest/__init__.py b/pytradebacktest/__init__.py similarity index 100% rename from fx_backtest/__init__.py rename to pytradebacktest/__init__.py diff --git a/fx_backtest/backtest.py b/pytradebacktest/backtest.py similarity index 75% rename from fx_backtest/backtest.py rename to pytradebacktest/backtest.py index f660f68..dd9de9b 100644 --- a/fx_backtest/backtest.py +++ b/pytradebacktest/backtest.py @@ -1,10 +1,10 @@ from typing import Type -from fx_lib.strategy import FxStrategy -from fx_backtest.broker import BacktestBroker -from fx_backtest.data import MarketData +from pytrade.strategy import FxStrategy -from fx_backtest.strategy import BacktestStrategyWrapper +from pytradebacktest.broker import BacktestBroker +from pytradebacktest.data import MarketData +from pytradebacktest.strategy import BacktestStrategyWrapper class Backtest: @@ -29,16 +29,15 @@ async def run(self): strategy = BacktestStrategyWrapper(broker, self.data, self.kstrategy) strategy.init() - + while self.data.next(): broker.next() await strategy.next() - # Increment data points - # Update indicators - # Update trades + # Update indicators + # Update trades # Claculate results/stats pass diff --git a/fx_backtest/broker.py b/pytradebacktest/broker.py similarity index 77% rename from fx_backtest/broker.py rename to pytradebacktest/broker.py index 32e6105..e31a5da 100644 --- a/fx_backtest/broker.py +++ b/pytradebacktest/broker.py @@ -1,9 +1,11 @@ from typing import Callable -from fx_lib.interfaces.broker import IBroker -from fx_lib.models.order import OrderRequest -from fx_lib.models.instruments import Instrument, Granularity, Candlestick -from fx_backtest.data import MarketData +from pytrade.interfaces.broker import IBroker +from pytrade.models.instruments import Candlestick, Granularity, Instrument +from pytrade.models.order import OrderRequest + +from pytradebacktest.data import MarketData + class BacktestBroker(IBroker): @@ -32,6 +34,6 @@ def subscribe( callback: Callable[[Candlestick], None], ): pass - + def next(self): - pass \ No newline at end of file + pass diff --git a/fx_backtest/data.py b/pytradebacktest/data.py similarity index 85% rename from fx_backtest/data.py rename to pytradebacktest/data.py index 89aadb4..8be6c5c 100644 --- a/fx_backtest/data.py +++ b/pytradebacktest/data.py @@ -1,14 +1,18 @@ from abc import abstractmethod -from typing import Optional, Tuple +from typing import Tuple import numpy as np import pandas as pd -from fx_lib.events.event import Event -from pandas import Timestamp -from pandas import Timedelta -from fx_backtest.utils import load_csv -from fx_lib.models.instruments import CandleData, Instrument, InstrumentCandles, INDEX, COLUMNS -from fx_lib.models.instruments import Granularity +from pandas import Timedelta, Timestamp +from pytrade.models.instruments import ( + CandleData, + Granularity, + Instrument, + InstrumentCandles, +) + +from pytradebacktest.utils import load_csv + class DataSource: @@ -16,18 +20,21 @@ def __init__(self, instrument: Instrument, granularity: Granularity): self.instrument = instrument self.granularity = granularity + class CsvDataSource(DataSource): def __init__(self, path: str, instrument: Instrument, granularity: Granularity): super().__init__(instrument, granularity) self.path = path + class MarketDataLoader: @abstractmethod def load(self) -> dict[Tuple[Instrument, Granularity], pd.DataFrame]: raise NotImplementedError + class CsvMarketDataLoader(MarketDataLoader): def __init__(self, sources: list[CsvDataSource]): @@ -39,12 +46,13 @@ def load(self) -> dict[Tuple[Instrument, Granularity], pd.DataFrame]: for source in self.sources: df = load_csv(source.path, parse_dates=["Timestamp"]) df = df.set_index("Timestamp") - df.replace('', np.nan, inplace=True) + df.replace("", np.nan, inplace=True) df.dropna(inplace=True) _sources[(source.instrument, source.granularity)] = df return _sources + class MarketData: def __init__(self, loader: MarketDataLoader): @@ -55,11 +63,11 @@ def __init__(self, loader: MarketDataLoader): @property def universe(self): return self._sources - + @property def index(self): return self._index - + def _init_timeframe(self): _start = None _granularity = None @@ -89,22 +97,25 @@ def _init_timeframe(self): if not _start: raise RuntimeError("Unable to determine start time for market data.") - + if not _granularity: - raise RuntimeError("Unable to determine smallest granularity for market data.") - + raise RuntimeError( + "Unable to determine smallest granularity for market data." + ) + if not _end: raise RuntimeError("Unable to determine end time for market data.") - + self._index: Timestamp = _start - _granularity - self._granularity: Timedelta = _granularity + self._granularity: Timedelta = _granularity self._end_index: Timestamp = _end def next(self): - + self._index = self._index + self._granularity return self._index <= self._end_index + class BacktestInstrumentCandles(InstrumentCandles): def __init__( @@ -117,7 +128,7 @@ def __init__( @property def index(self): return self._index - + @index.setter def index(self, value: pd.Timestamp): if value in self._data.index: @@ -126,7 +137,7 @@ def index(self, value: pd.Timestamp): @property def i_index(self): return self._data.index.get_loc(self._index) - + # def next(self): # while self._i_index < len(self._data.index): # yield self._data[self._i_index] @@ -139,7 +150,7 @@ def __init__(self): self._max_size = -1 self._data: dict[tuple[Instrument, Granularity], BacktestInstrumentCandles] = {} self._index = None - + def __new__(cls, *args, **kwargs): if not hasattr(cls, "instance"): cls.instance = super().__new__(cls) @@ -149,17 +160,19 @@ def __new__(cls, *args, **kwargs): @property def index(self): return self._index - + @index.setter def index(self, value: pd.Timestamp): self._index = value for candles in self._data.values(): candles.index = self._index - def populate(self, df: pd.DataFrame, instrument: Instrument, granularity: Granularity): + def populate( + self, df: pd.DataFrame, instrument: Instrument, granularity: Granularity + ): key = (instrument, granularity) instrument_candles: BacktestInstrumentCandles = self._data.get( key, BacktestInstrumentCandles(df, instrument, granularity), ) - self._data[key] = instrument_candles \ No newline at end of file + self._data[key] = instrument_candles diff --git a/fx_backtest/exceptions.py b/pytradebacktest/exceptions.py similarity index 100% rename from fx_backtest/exceptions.py rename to pytradebacktest/exceptions.py diff --git a/fx_backtest/strategy.py b/pytradebacktest/strategy.py similarity index 51% rename from fx_backtest/strategy.py rename to pytradebacktest/strategy.py index a87f7a1..e83929c 100644 --- a/fx_backtest/strategy.py +++ b/pytradebacktest/strategy.py @@ -1,10 +1,15 @@ -import asyncio from typing import Type -from fx_lib.interfaces.broker import IBroker -from fx_lib.strategy import FxStrategy -from fx_lib.models.indicator import Indicator -from fx_backtest.data import BacktestCandleData, BacktestInstrumentCandles, MarketData +from pytrade.interfaces.broker import IBroker +from pytrade.models.indicator import Indicator +from pytrade.strategy import FxStrategy + +from pytradebacktest.data import ( + BacktestCandleData, + BacktestInstrumentCandles, + MarketData, +) + class BacktestStrategyWrapper: @@ -20,28 +25,43 @@ def init(self): self._strategy.init() - self._indicators = {attr: indicator - for attr, indicator in self._strategy.__dict__.items() - if isinstance(indicator, Indicator)}.items() - - self._indicator_values = {attr: indicator._values for attr, indicator in self._indicators } + self._indicators = { + attr: indicator + for attr, indicator in self._strategy.__dict__.items() + if isinstance(indicator, Indicator) + }.items() + + self._indicator_values = { + attr: indicator._values for attr, indicator in self._indicators + } self._indicator_i_index = {attr: None for attr, indicator in self._indicators} async def next(self) -> None: self._data_context.index = self._data.index - indicator_updated = False + updates = [] # Incrememnt indicators for attr, indicator in self._indicators: + indicator_updated = False if isinstance(indicator._data, BacktestInstrumentCandles): previous_i_index = self._indicator_i_index.get(attr) if previous_i_index != indicator._data.i_index: - indicator._values = self._indicator_values[attr][:indicator._data.i_index+1] + indicator._values = self._indicator_values[attr][ + : indicator._data.i_index + 1 + ] self._indicator_i_index[attr] = indicator._data.i_index indicator_updated = True - if indicator_updated: + updates.append(indicator_updated) + + all_updates_received = all(updates) + + # Currently making sure all indicators have been updated before calling next + # This aligns with the pending update logic when the strategy is event + # driven in live trading. If that behavior changes this will also need to + # change. + if all_updates_received: # Call _next directly so we don't wait for pending updates - self._strategy._next() \ No newline at end of file + self._strategy._next() diff --git a/fx_backtest/utils.py b/pytradebacktest/utils.py similarity index 79% rename from fx_backtest/utils.py rename to pytradebacktest/utils.py index 2413fe9..c8fa1f7 100644 --- a/fx_backtest/utils.py +++ b/pytradebacktest/utils.py @@ -1,4 +1,3 @@ -from typing import Optional import pandas as pd @@ -6,4 +5,4 @@ def load_csv(path, parse_dates: list[str] = []) -> pd.DataFrame: with open(path) as fh: data = pd.read_csv(fh, parse_dates=parse_dates) - return data \ No newline at end of file + return data diff --git a/scripts/test.sh b/scripts/test.sh index c7d290d..1d4ce33 100755 --- a/scripts/test.sh +++ b/scripts/test.sh @@ -1,3 +1,3 @@ #!/bin/bash -poetry run pytest -s --tb=native --durations=5 --cov=fx_backtest --cov-report=html tests -poetry run coverage report --fail-under=0 \ No newline at end of file +poetry run pytest -s --tb=native --durations=5 --cov=pytradebacktest --cov-report=html tests +poetry run coverage report --fail-under=90 \ No newline at end of file diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py index 640dd9d..b5a3439 100644 --- a/tests/unit/conftest.py +++ b/tests/unit/conftest.py @@ -1,22 +1,22 @@ -import pytest -from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData -from fx_lib.models.indicator import Indicator -from fx_lib.models.instruments import IInstrumentData -from fx_lib.events.event import Event -from fx_lib.models.instruments import Instrument, Granularity -import pandas as pd import numpy as np +import pandas as pd +import pytest +from pytrade.events.event import Event +from pytrade.models.indicator import Indicator +from pytrade.models.instruments import Granularity, IInstrumentData, Instrument + +from pytradebacktest.data import CsvDataSource, CsvMarketDataLoader, MarketData + class TestIndicator(Indicator): def _run(self, *args, **kwargs): - return self._data.values.flatten() + return self._data.df.values.flatten() + class TestData(IInstrumentData): - def __init__( - self, data: pd.DataFrame - ): + def __init__(self, data: pd.DataFrame): self._data = data self.__update_event = Event() @@ -32,64 +32,69 @@ def on_update(self): def on_update(self, value: Event): self.__update_event = value + @pytest.fixture(scope="module") def data(): return np.array([1, 2, 3, 4, 5]) + @pytest.fixture(scope="module") def instrument_data(data): df = pd.DataFrame(data) return TestData(df) + @pytest.fixture(scope="module") def indicator(instrument_data): return TestIndicator(instrument_data) + @pytest.fixture(scope="module") def test_csv_sources() -> list[CsvDataSource]: return [ - # CsvDataSource( - # "tests/unit/assets/EURGBP-2024-05_1Min.csv", - # Instrument.EURGBP, - # Granularity.M1 - # ), - # CsvDataSource( - # "tests/unit/assets/EURJPY-2024-05_1Min.csv", - # Instrument.EURJPY, - # Granularity.M1 - # ), + CsvDataSource( + "tests/unit/assets/EURGBP-2024-05_1Min.csv", + Instrument.EURGBP, + Granularity.M1, + ), + CsvDataSource( + "tests/unit/assets/EURJPY-2024-05_1Min.csv", + Instrument.EURJPY, + Granularity.M1, + ), CsvDataSource( "tests/unit/assets/EURUSD-2024-05_1Min.csv", Instrument.EURUSD, - Granularity.M1 + Granularity.M1, + ), + CsvDataSource( + "tests/unit/assets/GBPUSD-2024-05_1Min.csv", + Instrument.GBPUSD, + Granularity.M1, + ), + CsvDataSource( + "tests/unit/assets/EURGBP-2024-05_5Min.csv", + Instrument.EURGBP, + Granularity.M5, + ), + CsvDataSource( + "tests/unit/assets/EURJPY-2024-05_5Min.csv", + Instrument.EURJPY, + Granularity.M5, ), - # CsvDataSource( - # "tests/unit/assets/GBPUSD-2024-05_1Min.csv", - # Instrument.GBPUSD, - # Granularity.M1 - # ), - # CsvDataSource( - # "tests/unit/assets/EURGBP-2024-05_5Min.csv", - # Instrument.EURGBP, - # Granularity.M5 - # ), - # CsvDataSource( - # "tests/unit/assets/EURJPY-2024-05_5Min.csv", - # Instrument.EURJPY, - # Granularity.M5 - # ), CsvDataSource( "tests/unit/assets/EURUSD-2024-05_5Min.csv", Instrument.EURUSD, - Granularity.M5 + Granularity.M5, + ), + CsvDataSource( + "tests/unit/assets/GBPUSD-2024-05_5Min.csv", + Instrument.GBPUSD, + Granularity.M5, ), - # CsvDataSource( - # "tests/unit/assets/GBPUSD-2024-05_5Min.csv", - # Instrument.GBPUSD, - # Granularity.M5 - # ), ] -@pytest.fixture(scope="module") + +@pytest.fixture(scope="function") def test_universe(test_csv_sources): - return MarketData(CsvMarketDataLoader(test_csv_sources)) \ No newline at end of file + return MarketData(CsvMarketDataLoader(test_csv_sources)) diff --git a/tests/unit/test_backtest.py b/tests/unit/test_backtest.py index 8f290f2..66cac0a 100644 --- a/tests/unit/test_backtest.py +++ b/tests/unit/test_backtest.py @@ -1,35 +1,30 @@ -from unittest.mock import patch - import pytest -from fx_backtest.backtest import Backtest -from fx_lib.models.indicator import Indicator -from fx_lib.strategy import FxStrategy -from fx_lib.models.instruments import ( - CandleSubscription, - Instrument, - Granularity -) +from pytrade.models.indicator import Indicator +from pytrade.models.instruments import CandleSubscription, Granularity, Instrument +from pytrade.strategy import FxStrategy + +from pytradebacktest.backtest import Backtest BACKTEST_INSTRUMENT = Instrument.EURUSD BACKTEST_GRANULARITY = Granularity.M5 + class BacktestIndicator(Indicator): def _run(self, *args, **kwargs): return self._data.Open > self._data.Close - + + class BacktestStrategy(FxStrategy): - + @property def subscriptions(self) -> list[CandleSubscription]: """ Declare the `InstrumentSubscription`s this strategy should use for its signals """ - return [ - CandleSubscription(BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY) - ] - + return [CandleSubscription(BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY)] + def _init(self) -> None: """ Create indicators to be used for signals in the `_next` method. @@ -43,7 +38,7 @@ def _next(self) -> None: """ if self.test_indicator: self.sell(1) - else: + else: self.buy(1) @@ -52,4 +47,3 @@ async def test_backtest_increments_indicator(test_universe): test = Backtest(test_universe, BacktestStrategy, 10000) await test.run() - diff --git a/tests/unit/test_data.py b/tests/unit/test_data.py index affddae..ecb659f 100644 --- a/tests/unit/test_data.py +++ b/tests/unit/test_data.py @@ -1,32 +1,34 @@ -from datetime import datetime -from datetime import timedelta +from datetime import datetime, timedelta + +from pytradebacktest.data import MarketData -from fx_backtest.data import CsvDataSource, CsvMarketDataLoader, MarketData -from fx_lib.models.instruments import Instrument, Granularity, Candlestick def test_load_market_data(test_universe): data = test_universe assert len(data._sources) == 8 + def test_init_timeframe(test_universe): - data = test_universe + data: MarketData = test_universe - assert data._index == datetime(2024, 5, 1) + assert data._index == datetime(2024, 4, 30, 23, 59) assert data._granularity == timedelta(minutes=1) -def test_updates(test_universe): - data: MarketData = test_universe - sources_count = len(data._sources) +# def test_updates(test_universe): +# data: MarketData = test_universe + +# sources_count = len(data._sources) + +# _candles = [] - _candles = [] - def _handle_update(candle: Candlestick): - _candles.append(candle) +# def _handle_update(candle: Candlestick): +# _candles.append(candle) - for instrument, granularity in data._sources.keys(): - data.subscribe(instrument, granularity, _handle_update) +# for instrument, granularity in data._sources.keys(): +# data.subscribe(instrument, granularity, _handle_update) - for i in range(10): - data.next() +# for i in range(10): +# data.next() - assert len(_candles) == sources_count * (i + 1) \ No newline at end of file +# assert len(_candles) == sources_count * (i + 1) diff --git a/tests/unit/test_default.py b/tests/unit/test_default.py deleted file mode 100644 index 47d4f19..0000000 --- a/tests/unit/test_default.py +++ /dev/null @@ -1,2 +0,0 @@ -def test_default(): - assert True diff --git a/tests/unit/test_indicator.py b/tests/unit/test_indicator.py index 270e880..6db9492 100644 --- a/tests/unit/test_indicator.py +++ b/tests/unit/test_indicator.py @@ -1,7 +1,8 @@ -from fx_lib.models.indicator import Indicator import numpy as np +from pytrade.models.indicator import Indicator + +from pytradebacktest.data import MarketData -from fx_backtest.data import MarketData def test_indicator_values(data: np.ndarray, indicator: Indicator): assert len(indicator._values) == len(data) @@ -9,6 +10,6 @@ def test_indicator_values(data: np.ndarray, indicator: Indicator): def test_indicator_updates(test_universe: MarketData, indicator: Indicator): - data_c + while test_universe.next(): - pass \ No newline at end of file + pass diff --git a/tests/unit/test_strategy.py b/tests/unit/test_strategy.py index 5410af4..45e1db8 100644 --- a/tests/unit/test_strategy.py +++ b/tests/unit/test_strategy.py @@ -2,29 +2,26 @@ import pandas as pd import pytest -from fx_backtest.backtest import Backtest -from fx_lib.models.indicator import Indicator -from fx_lib.strategy import FxStrategy -from fx_lib.models.instruments import ( - CandleSubscription, - Instrument, - Granularity -) - -from fx_backtest.broker import BacktestBroker -from fx_backtest.data import MarketData -from fx_backtest.strategy import BacktestStrategyWrapper +from pytrade.models.indicator import Indicator +from pytrade.models.instruments import CandleSubscription, Granularity, Instrument +from pytrade.strategy import FxStrategy + +from pytradebacktest.broker import BacktestBroker +from pytradebacktest.data import MarketData +from pytradebacktest.strategy import BacktestStrategyWrapper BACKTEST_INSTRUMENT = Instrument.EURUSD BACKTEST_GRANULARITY = Granularity.M5 + class BacktestIndicator(Indicator): def _run(self, *args, **kwargs): return self._data.Open > self._data.Close - + + class BacktestStrategy(FxStrategy): - + @property def subscriptions(self) -> list[CandleSubscription]: """ @@ -33,15 +30,19 @@ def subscriptions(self) -> list[CandleSubscription]: """ return [ CandleSubscription(BACKTEST_INSTRUMENT, Granularity.M1), - CandleSubscription(BACKTEST_INSTRUMENT, Granularity.M5) + CandleSubscription(BACKTEST_INSTRUMENT, Granularity.M5), ] - + def _init(self) -> None: """ Create indicators to be used for signals in the `_next` method. """ - self.eurusd_m1 = BacktestIndicator(self.get_data(BACKTEST_INSTRUMENT, Granularity.M1)) - self.eurusd_m5 = BacktestIndicator(self.get_data(BACKTEST_INSTRUMENT, Granularity.M5)) + self.eurusd_m1 = BacktestIndicator( + self.get_data(BACKTEST_INSTRUMENT, Granularity.M1) + ) + self.eurusd_m5 = BacktestIndicator( + self.get_data(BACKTEST_INSTRUMENT, Granularity.M5) + ) def _next(self) -> None: """ @@ -49,7 +50,7 @@ def _next(self) -> None: """ if self.eurusd_m5: self.sell(1) - else: + else: self.buy(1) @@ -60,16 +61,17 @@ async def test_strategy_indicator_updates(test_universe: MarketData): strategy = BacktestStrategyWrapper(broker, test_universe, BacktestStrategy) strategy.init() - - m1_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, Granularity.M1)) - m5_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, Granularity.M5)) - indicator_data = { - "eurusd_m1": m1_data, - "eurusd_m5": m5_data - } + + m1_data: pd.DataFrame = test_universe._sources.get( + (BACKTEST_INSTRUMENT, Granularity.M1) + ) + m5_data: pd.DataFrame = test_universe._sources.get( + (BACKTEST_INSTRUMENT, Granularity.M5) + ) + indicator_data = {"eurusd_m1": m1_data, "eurusd_m5": m5_data} expected_indicator_values = { "eurusd_m1": m1_data.Open > m1_data.Close, - "eurusd_m5": m5_data.Open > m5_data.Close + "eurusd_m5": m5_data.Open > m5_data.Close, } for attr, indicator in strategy._indicators: @@ -85,20 +87,24 @@ async def test_strategy_indicator_updates(test_universe: MarketData): assert len(indicator._values) == expected_length assert indicator == expected_indicator_values[attr][data_i_index] -@patch("fx_lib.strategy.FxStrategy.sell") -@patch("fx_lib.strategy.FxStrategy.buy") + +@patch("pytrade.strategy.FxStrategy.sell") +@patch("pytrade.strategy.FxStrategy.buy") @pytest.mark.asyncio -async def test_strategy_indicator_orders(mock_buy, mock_sell, test_universe: MarketData): +async def test_strategy_indicator_orders( + mock_buy, mock_sell, test_universe: MarketData +): broker = BacktestBroker(test_universe) strategy = BacktestStrategyWrapper(broker, test_universe, BacktestStrategy) strategy.init() - - test_data: pd.DataFrame = test_universe._sources.get((BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY)) - while test_universe.next(): + test_data: pd.DataFrame = test_universe._sources.get( + (BACKTEST_INSTRUMENT, BACKTEST_GRANULARITY) + ) + while test_universe.next(): await strategy.next() expected_buy_calls = test_data[test_data.Open <= test_data.Close].count().Open diff --git a/tests/unit/test_utils.py b/tests/unit/test_utils.py index 00b168d..b62ff86 100644 --- a/tests/unit/test_utils.py +++ b/tests/unit/test_utils.py @@ -1,18 +1,17 @@ -import os import pytest -from fx_backtest.utils import load_csv +from pytradebacktest.utils import load_csv @pytest.mark.parametrize( - "path,count", - [ - ("tests/unit/assets/EURGBP-2024-05_1Min.csv", 44460), - ("tests/unit/assets/EURJPY-2024-05_1Min.csv", 44460), - ("tests/unit/assets/EURUSD-2024-05_1Min.csv", 44460), - ("tests/unit/assets/GBPUSD-2024-05_1Min.csv", 44460) - ] + "path,count", + [ + ("tests/unit/assets/EURGBP-2024-05_1Min.csv", 44460), + ("tests/unit/assets/EURJPY-2024-05_1Min.csv", 44460), + ("tests/unit/assets/EURUSD-2024-05_1Min.csv", 44460), + ("tests/unit/assets/GBPUSD-2024-05_1Min.csv", 44460), + ], ) def test_load_csvs(path, count): df = load_csv(path, parse_dates=["Timestamp"]) - assert df.shape[0] == count \ No newline at end of file + assert df.shape[0] == count From c175aac50c48216fc0ecaddeb09b4b838c9539d1 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Tue, 7 Jan 2025 06:29:03 -0500 Subject: [PATCH 8/9] Update build to pull submodules --- .github/workflows/build.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index f9116b0..8236a68 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -20,6 +20,8 @@ jobs: steps: - name: Checkout repository uses: actions/checkout@v4 + with: + submodules: 'true' - name: Build working-directory: . From b81219351c9d16553aa3b096e969802248fa82b7 Mon Sep 17 00:00:00 2001 From: Kyle Widmann Date: Wed, 8 Jan 2025 06:11:31 -0500 Subject: [PATCH 9/9] Fixing pytrade submodule --- .github/workflows/build.yml | 2 +- lib/PyTrade | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) create mode 160000 lib/PyTrade diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 8236a68..7066efa 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -21,7 +21,7 @@ jobs: - name: Checkout repository uses: actions/checkout@v4 with: - submodules: 'true' + submodules: 'recursive' - name: Build working-directory: . diff --git a/lib/PyTrade b/lib/PyTrade new file mode 160000 index 0000000..b3b4a28 --- /dev/null +++ b/lib/PyTrade @@ -0,0 +1 @@ +Subproject commit b3b4a28c12a86114a754ac7c9e8f00ec8a02b914