Add Data Methods

First methods for adding data to distance approach class

PairsTrading/DistanceApproach.py

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+import pandas as pd
+from utilities import isSequenceOf
+from pandas.api.types import is_numeric_dtype
+
+'''
+This class implements the distance approach to a pairs trading signal in 3 steps:
+- Orders and ranks pairs according to some distance metric
+- Generates a signal according to a threshold
+- Outputs a backtest according to a brokerage fee template
+'''
+class DistanceApproach():
+    def __init__(self) -> None:
+        self.pairsData = None
+        self.tradeData = None
+
+    '''
+    This Function sets the data set for generating possible pairs.
+
+    Make sure your data frame is formated according to the following structure
+    DateTime | Price Series A | Price Series B | Price Series C |...
+    Raises Exception if:
+    - Data doesn't have more than two columns
+    - Left-Most column is not of type datetime64
+    - If there are non-numerical data types 
+    Returns true if we can successfully set the pairs data
+    '''
+    def setPairsData(self, data: pd.DataFrame) -> bool: 
+        if self.isDataWellFormed(data):
+            self.data = data
+            return True
+
+    def setTradeData(self, data: pd.DataFrame) -> bool:
+        if self.isDataWellFormed(data):
+            self.tradeData = data
+            return True
+    '''
+    Checks whether a dataframe conforms to requirements to store in DistanceApproach class
+    '''
+    @staticmethod
+    def isDataWellFormed(data: pd.DataFrame) -> bool:
+        t = lambda x: is_numeric_dtype(x) 
+        if len(data.columns) <= 1:
+            raise Exception('Dataframe is missing columns. Check that you have both securities and date columns')
+        elif data.dtypes[0] != 'datetime64':
+           raise Exception('Left-Most Column is not of type datetime64')
+        #Check if there is a non-numerical column to the right of date column
+        elif False in list(data.apply(t)[1:]):
+            raise Exception('Detected non-numerical data-types to the right of date column')
+        else:
+            return True
+
+

PairsTrading/DistanceApproachExample.ipynb

@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "cb4eb849",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from pandas.api.types import is_numeric_dtype"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "30502d1a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'B'],\n",
+    "                   'points': [11, 7, 8, 10, 13, 13],\n",
+    "                   'assists': [5, 7, 7, 9, 12, 9],\n",
+    "                   'rebounds': [11, 8, 10, 6, 6, 5]})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "31629c65",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "is_numeric_dtype(df.iloc[0:,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "10024d10",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f = lambda x: is_numeric_dtype(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "f3acf638",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>points</th>\n",
+       "      <th>assists</th>\n",
+       "      <th>rebounds</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>11</td>\n",
+       "      <td>5</td>\n",
+       "      <td>11</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>7</td>\n",
+       "      <td>7</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>8</td>\n",
+       "      <td>7</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>10</td>\n",
+       "      <td>9</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>13</td>\n",
+       "      <td>12</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>13</td>\n",
+       "      <td>9</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   points  assists  rebounds\n",
+       "0      11        5        11\n",
+       "1       7        7         8\n",
+       "2       8        7        10\n",
+       "3      10        9         6\n",
+       "4      13       12         6\n",
+       "5      13        9         5"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.iloc[0:,1:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0542b1b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

utilities.py

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+from sympy import false, true
+
+'''
+Checks if a sequence is restricted to the domain of elements
+'''
+def isSequenceOf(sequence: list, elements: list) -> bool:
+    for i in sequence:
+        if not i in elements:
+            return False
+    return True