Moving_Avg_Convergence_Div_Crossover.ipynb

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      "name": "Moving-Avg-Convergence-Div-Crossover.ipynb",
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      "authorship_tag": "ABX9TyPbisYzoSmRK6M5cmlXiQP0",
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      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/ktiwari9/algotradingbot/blob/master/Moving_Avg_Convergence_Div_Crossover.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
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      "metadata": {
        "id": "MZkBztFEVAnx",
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      "source": [
        "# Description: This is an Algorithmic Trading Bot that utilizes the Moving Average Convergence Divergence Crossover aka MACD crossover\n",
        "# strategy. This strategy is a technical indicator which utilizes the differences in the STMA and LTMA (exponential) moving averages to determine the\n",
        "# momentum and direction of the market.\n",
        "# BUY: MACD line cross above the signal line\n",
        "# SELL: MACD line crosses below the signal line\n",
        "\n",
        "# Inspired by: https://www.youtube.com/watch?v=kz_NJERCgm8"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "id": "uf2DN-o4WAjL",
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          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "0e767896-fa66-4e09-f66e-3cac61ae4d24"
      },
      "source": [
        "# All necessary imports\n",
        "import numpy as np\n",
        "# Get latest version of pandas for the code to work\n",
        "# !sudo pip install pandas==1.0\n",
        "import pandas as pd\n",
        "print(pd.__version__)\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('fivethirtyeight')"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.0.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oTui8SXCWEuA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "b900c09e-c006-4ea3-81a1-784ee94bb5a2"
      },
      "source": [
        "# introductory prints\n",
        "print(\"This is a MACD Trading Bot\")\n",
        "print(\"The Trading signal is identified when a MACD line crosses the signal line\")\n",
        "print(\"MACD line is computed as a different between short-term and long-term exp. moving averages.\")"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "This is a MACD Trading Bot\n",
            "The Trading signal is identified when a MACD line crosses the signal line\n",
            "MACD line is computed as a different between short-term and long-term exp. moving averages.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "98ZhJvmqXFKC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Import Historic Stock charts - Upload a CSV if not already done\n",
        "# from google.colab import files\n",
        "# files.upload()\n",
        "\n",
        "# dataset obtained from Yahoo Finance: https://finance.yahoo.com/quote/AAPL/history?period1=1159747200&period2=1596326400&interval=1d&filter=history&frequency=1d"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lb-WBt3pXlBn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "179191d2-ef93-4229-dac0-774531a9e6c1"
      },
      "source": [
        "# Store the data as a panda dataframe\n",
        "AAPL = pd.read_csv('AAPL.csv')\n",
        "# Set the date as the index\n",
        "AAPL = AAPL.set_index(pd.DatetimeIndex(AAPL['Date'].values)) \n",
        "\n",
        "# Show the data\n",
        "AAPL \n",
        "\n",
        "# Truncate the data until 26th Dec 2006\n",
        "AAPL = AAPL[0:60] # 60 rows mark until 26th Dec 2006\n",
        "max_close = AAPL['Close'].max()\n",
        "min_close = AAPL['Close'].min()\n",
        "\n",
        "print(AAPL)\n",
        "print(\"Max Close Price = \", max_close)\n",
        "print(\"Min Close Price = \", min_close)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                  Date       Open       High  ...      Close  Adj Close     Volume\n",
            "2006-10-02  2006-10-02  10.728572  10.838572  ...  10.694285   9.258014  178159800\n",
            "2006-10-03  2006-10-03  10.635715  10.707143  ...  10.582857   9.161551  197677200\n",
            "2006-10-04  2006-10-04  10.585714  10.780000  ...  10.768572   9.322326  207270700\n",
            "2006-10-05  2006-10-05  10.647142  10.880000  ...  10.690000   9.254304  170970800\n",
            "2006-10-06  2006-10-06  10.631429  10.720000  ...  10.602858   9.178867  116739700\n",
            "2006-10-09  2006-10-09  10.542857  10.725715  ...  10.661428   9.229569  109555600\n",
            "2006-10-10  2006-10-10  10.648571  10.654285  ...  10.544286   9.128160  132897100\n",
            "2006-10-11  2006-10-11  10.488571  10.568571  ...  10.461429   9.056430  142963800\n",
            "2006-10-12  2006-10-12  10.515715  10.770000  ...  10.751429   9.307484  148213800\n",
            "2006-10-13  2006-10-13  10.804286  10.982857  ...  10.717143   9.277802  171049200\n",
            "2006-10-16  2006-10-16  10.741428  10.840000  ...  10.771428   9.324798  127173200\n",
            "2006-10-17  2006-10-17  10.720000  10.752857  ...  10.612857   9.187523  120231300\n",
            "2006-10-18  2006-10-18  10.678572  10.767143  ...  10.647142   9.217201  283476900\n",
            "2006-10-19  2006-10-19  11.322857  11.421429  ...  11.284286   9.768776  378244300\n",
            "2006-10-20  2006-10-20  11.281428  11.427143  ...  11.421429   9.887502  159853400\n",
            "2006-10-23  2006-10-23  11.427143  11.700000  ...  11.637143  10.074244  208126800\n",
            "2006-10-24  2006-10-24  11.601429  11.668571  ...  11.578571  10.023538  115803100\n",
            "2006-10-25  2006-10-25  11.621428  11.714286  ...  11.668571  10.101451  121303700\n",
            "2006-10-26  2006-10-26  11.700000  11.800000  ...  11.741428  10.164527  108189200\n",
            "2006-10-27  2006-10-27  11.678572  11.778571  ...  11.487143   9.944393  148741600\n",
            "2006-10-30  2006-10-30  11.427143  11.557143  ...  11.488571   9.945626  124979400\n",
            "2006-10-31  2006-10-31  11.635715  11.668571  ...  11.582857  10.027248  125368600\n",
            "2006-11-01  2006-11-01  11.585714  11.625714  ...  11.308572   9.789802  152798100\n",
            "2006-11-02  2006-11-02  11.274285  11.331429  ...  11.282857   9.767539  116370800\n",
            "2006-11-03  2006-11-03  11.337143  11.361428  ...  11.184286   9.682207  107972200\n",
            "2006-11-06  2006-11-06  11.278571  11.437143  ...  11.387143   9.857821  108644200\n",
            "2006-11-07  2006-11-07  11.492857  11.571428  ...  11.501429   9.956757  131483100\n",
            "2006-11-08  2006-11-08  11.431429  11.812857  ...  11.778571  10.196676  172729200\n",
            "2006-11-09  2006-11-09  11.842857  12.098572  ...  11.905714  10.306746  230763400\n",
            "2006-11-10  2006-11-10  11.935715  11.942857  ...  11.874286  10.279537   93466100\n",
            "2006-11-13  2006-11-13  11.888572  12.064285  ...  12.050000  10.431654  112668500\n",
            "2006-11-14  2006-11-14  12.114285  12.142858  ...  12.142858  10.512039  147238700\n",
            "2006-11-15  2006-11-15  12.150000  12.271428  ...  12.007143  10.394552  163830800\n",
            "2006-11-16  2006-11-16  12.124286  12.328571  ...  12.230000  10.587480  173485200\n",
            "2006-11-17  2006-11-17  12.162857  12.277143  ...  12.264286  10.617161  116606000\n",
            "2006-11-20  2006-11-20  12.200000  12.428572  ...  12.352858  10.693839  142698500\n",
            "2006-11-21  2006-11-21  12.488571  12.657143  ...  12.657143  10.957254  155666700\n",
            "2006-11-22  2006-11-22  12.712857  12.964286  ...  12.901428  11.168736  167985300\n",
            "2006-11-24  2006-11-24  12.790000  13.297143  ...  13.090000  11.331979  129669400\n",
            "2006-11-27  2006-11-27  13.215714  13.308572  ...  12.791429  11.073504  268709000\n",
            "2006-11-28  2006-11-28  12.908571  13.138572  ...  13.115714  11.354239  259043400\n",
            "2006-11-29  2006-11-29  13.285714  13.307143  ...  13.114285  11.353003  289270800\n",
            "2006-11-30  2006-11-30  13.172857  13.240000  ...  13.094286  11.335690  217621600\n",
            "2006-12-01  2006-12-01  13.114285  13.190000  ...  13.045714  11.293642  198769900\n",
            "2006-12-04  2006-12-04  13.125714  13.150000  ...  13.017143  11.268908  177384200\n",
            "2006-12-05  2006-12-05  13.092857  13.190000  ...  13.038571  11.287459  165709600\n",
            "2006-12-06  2006-12-06  12.948571  13.055715  ...  12.832857  11.109372  159546100\n",
            "2006-12-07  2006-12-07  12.861428  12.928572  ...  12.434286  10.764329  251206900\n",
            "2006-12-08  2006-12-08  12.461429  12.770000  ...  12.608571  10.915209  196069300\n",
            "2006-12-11  2006-12-11  12.700000  12.757143  ...  12.678572  10.975807  124945100\n",
            "2006-12-12  2006-12-12  12.658571  12.691428  ...  12.305715  10.653026  256655000\n",
            "2006-12-13  2006-12-13  12.564285  12.724286  ...  12.721429  11.012909  214263000\n",
            "2006-12-14  2006-12-14  12.721429  12.857142  ...  12.650000  10.951073  208082700\n",
            "2006-12-15  2006-12-15  12.717143  12.745714  ...  12.531428  10.848425  184984800\n",
            "2006-12-18  2006-12-18  12.518572  12.571428  ...  12.210000  10.570165  180394200\n",
            "2006-12-19  2006-12-19  12.104285  12.382857  ...  12.330000  10.674047  227851400\n",
            "2006-12-20  2006-12-20  12.352858  12.381429  ...  12.108571  10.482360  141922900\n",
            "2006-12-21  2006-12-21  12.100000  12.211429  ...  11.842857  10.252333  225899800\n",
            "2006-12-22  2006-12-22  11.922857  12.005714  ...  11.742857  10.165761  153325900\n",
            "2006-12-26  2006-12-26  11.735714  11.795714  ...  11.644286  10.080429  122672200\n",
            "\n",
            "[60 rows x 7 columns]\n",
            "Max Close Price =  13.115714\n",
            "Min Close Price =  10.461428999999999\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2XvYH8SWY1sO",
        "colab_type": "code",
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          "base_uri": "https://localhost:8080/",
          "height": 873
        },
        "outputId": "f6c1b51e-baab-42a3-e450-241fa3ef363a"
      },
      "source": [
        "# Plot the data\n",
        "\n",
        "plt.figure(figsize=(20.5,12.5)) # sizes are in inches\n",
        "plt.plot(AAPL['Close'], label = 'AAPL') # adjusted price on the x axis\n",
        "plt.title('Apple Close Price History')\n",
        "plt.xlabel('02 Oct 2006 - 26th Dec 2006')\n",
        "plt.xticks(rotation=45)\n",
        "plt.ylabel('Adj. Close Price USD ($)')\n",
        "plt.legend(loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sY3xh5SWZ_2h",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Calculate the MACD and signal line indicators\n",
        "\n",
        "# Calculate the short term exponential moving average (SEMA)\n",
        "shortPeriod = 12\n",
        "Short_EMA = AAPL.Close.ewm(span=shortPeriod, adjust= False).mean()\n",
        "\n",
        "# Calculate the long term exponential moving average (SEMA)\n",
        "longPeriod = 26\n",
        "Long_EMA = AAPL.Close.ewm(span=longPeriod, adjust= False).mean()\n",
        "\n",
        "# MACD Signal\n",
        "MACD = Short_EMA - Long_EMA\n",
        "\n",
        "# Signal line\n",
        "signalPeriod = 9\n",
        "signal = MACD.ewm(span=signalPeriod,adjust=False).mean()"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MCQd-s2ibRfb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 873
        },
        "outputId": "7941d9ab-2a2b-4130-ef73-612683c23574"
      },
      "source": [
        "# Plot the data\n",
        "\n",
        "plt.figure(figsize=(20.5,12.5)) # sizes are in inches\n",
        "plt.plot(AAPL.index, MACD, label = 'AAPL MACD') # MACD line\n",
        "plt.plot(AAPL.index, signal, label = 'Signal') # Signal line\n",
        "\n",
        "plt.title('Apple Adj. Close Price History')\n",
        "plt.xlabel('02 Oct 2006 - 26th Dec 2006')\n",
        "plt.xticks(rotation=45)\n",
        "plt.ylabel('Adj. Close Price USD ($)')\n",
        "plt.legend(loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gmZ3lxTYbp9e",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Store MACD and Signal in dataframe\n",
        "AAPL['MACD']= MACD\n",
        "AAPL['Signal']= signal"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UonUfzbxb2cZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Create Buy vs Sell signals\n",
        "\n",
        "def investment_signal(data):\n",
        "  sigPriceToBuy = []\n",
        "  sigPriceToSell = []\n",
        "  isCross = -1 # flag to check when STMA crosses over LTMA\n",
        "\n",
        "  for i in range(len(data)):\n",
        "    if data['MACD'][i]> data['Signal'][i]:\n",
        "      if isCross !=1:\n",
        "        sigPriceToBuy.append(data['Close'][i]) # good time to buy\n",
        "        sigPriceToSell.append(np.nan)\n",
        "        isCross = 1\n",
        "      else:\n",
        "        sigPriceToBuy.append(np.nan)\n",
        "        sigPriceToSell.append(np.nan)\n",
        "    elif data['MACD'][i]< data['Signal'][i]:\n",
        "        if isCross!= 0:\n",
        "          sigPriceToBuy.append(np.nan) \n",
        "          sigPriceToSell.append(data['Close'][i]) # good time to sell\n",
        "          isCross = 0\n",
        "        else:\n",
        "          sigPriceToBuy.append(np.nan)\n",
        "          sigPriceToSell.append(np.nan)\n",
        "    else:\n",
        "        sigPriceToBuy.append(np.nan)\n",
        "        sigPriceToSell.append(np.nan)\n",
        "\n",
        "  return (sigPriceToBuy,sigPriceToSell)"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0T0oZJKnckp9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "ce44d92d-abd6-4994-8b9b-73d92ab657ee"
      },
      "source": [
        "# Store the Buy and Sell data\n",
        "buy_sell = investment_signal(AAPL)\n",
        "AAPL['Buy_Signal_Price'] = buy_sell[0]\n",
        "AAPL['Sell_Signal_Price'] = buy_sell[1]\n",
        "AAPL"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>MACD</th>\n",
              "      <th>Signal</th>\n",
              "      <th>Buy_Signal_Price</th>\n",
              "      <th>Sell_Signal_Price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2006-10-02</th>\n",
              "      <td>2006-10-02</td>\n",
              "      <td>10.728572</td>\n",
              "      <td>10.838572</td>\n",
              "      <td>10.614285</td>\n",
              "      <td>10.694285</td>\n",
              "      <td>9.258014</td>\n",
              "      <td>178159800</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-03</th>\n",
              "      <td>2006-10-03</td>\n",
              "      <td>10.635715</td>\n",
              "      <td>10.707143</td>\n",
              "      <td>10.455714</td>\n",
              "      <td>10.582857</td>\n",
              "      <td>9.161551</td>\n",
              "      <td>197677200</td>\n",
              "      <td>-0.008889</td>\n",
              "      <td>-0.001778</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.582857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-04</th>\n",
              "      <td>2006-10-04</td>\n",
              "      <td>10.585714</td>\n",
              "      <td>10.780000</td>\n",
              "      <td>10.451428</td>\n",
              "      <td>10.768572</td>\n",
              "      <td>9.322326</td>\n",
              "      <td>207270700</td>\n",
              "      <td>-0.000937</td>\n",
              "      <td>-0.001610</td>\n",
              "      <td>10.768572</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-05</th>\n",
              "      <td>2006-10-05</td>\n",
              "      <td>10.647142</td>\n",
              "      <td>10.880000</td>\n",
              "      <td>10.590000</td>\n",
              "      <td>10.690000</td>\n",
              "      <td>9.254304</td>\n",
              "      <td>170970800</td>\n",
              "      <td>-0.000964</td>\n",
              "      <td>-0.001480</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-06</th>\n",
              "      <td>2006-10-06</td>\n",
              "      <td>10.631429</td>\n",
              "      <td>10.720000</td>\n",
              "      <td>10.544286</td>\n",
              "      <td>10.602858</td>\n",
              "      <td>9.178867</td>\n",
              "      <td>116739700</td>\n",
              "      <td>-0.007926</td>\n",
              "      <td>-0.002769</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.602858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-09</th>\n",
              "      <td>2006-10-09</td>\n",
              "      <td>10.542857</td>\n",
              "      <td>10.725715</td>\n",
              "      <td>10.504286</td>\n",
              "      <td>10.661428</td>\n",
              "      <td>9.229569</td>\n",
              "      <td>109555600</td>\n",
              "      <td>-0.008617</td>\n",
              "      <td>-0.003939</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-10</th>\n",
              "      <td>2006-10-10</td>\n",
              "      <td>10.648571</td>\n",
              "      <td>10.654285</td>\n",
              "      <td>10.440000</td>\n",
              "      <td>10.544286</td>\n",
              "      <td>9.128160</td>\n",
              "      <td>132897100</td>\n",
              "      <td>-0.018406</td>\n",
              "      <td>-0.006832</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-11</th>\n",
              "      <td>2006-10-11</td>\n",
              "      <td>10.488571</td>\n",
              "      <td>10.568571</td>\n",
              "      <td>10.371428</td>\n",
              "      <td>10.461429</td>\n",
              "      <td>9.056430</td>\n",
              "      <td>142963800</td>\n",
              "      <td>-0.032475</td>\n",
              "      <td>-0.011961</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-12</th>\n",
              "      <td>2006-10-12</td>\n",
              "      <td>10.515715</td>\n",
              "      <td>10.770000</td>\n",
              "      <td>10.514286</td>\n",
              "      <td>10.751429</td>\n",
              "      <td>9.307484</td>\n",
              "      <td>148213800</td>\n",
              "      <td>-0.019993</td>\n",
              "      <td>-0.013567</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-13</th>\n",
              "      <td>2006-10-13</td>\n",
              "      <td>10.804286</td>\n",
              "      <td>10.982857</td>\n",
              "      <td>10.677143</td>\n",
              "      <td>10.717143</td>\n",
              "      <td>9.277802</td>\n",
              "      <td>171049200</td>\n",
              "      <td>-0.012722</td>\n",
              "      <td>-0.013398</td>\n",
              "      <td>10.717143</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-16</th>\n",
              "      <td>2006-10-16</td>\n",
              "      <td>10.741428</td>\n",
              "      <td>10.840000</td>\n",
              "      <td>10.684286</td>\n",
              "      <td>10.771428</td>\n",
              "      <td>9.324798</td>\n",
              "      <td>127173200</td>\n",
              "      <td>-0.002549</td>\n",
              "      <td>-0.011228</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-17</th>\n",
              "      <td>2006-10-17</td>\n",
              "      <td>10.720000</td>\n",
              "      <td>10.752857</td>\n",
              "      <td>10.577143</td>\n",
              "      <td>10.612857</td>\n",
              "      <td>9.187523</td>\n",
              "      <td>120231300</td>\n",
              "      <td>-0.007200</td>\n",
              "      <td>-0.010423</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-18</th>\n",
              "      <td>2006-10-18</td>\n",
              "      <td>10.678572</td>\n",
              "      <td>10.767143</td>\n",
              "      <td>10.558572</td>\n",
              "      <td>10.647142</td>\n",
              "      <td>9.217201</td>\n",
              "      <td>283476900</td>\n",
              "      <td>-0.008026</td>\n",
              "      <td>-0.009943</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-19</th>\n",
              "      <td>2006-10-19</td>\n",
              "      <td>11.322857</td>\n",
              "      <td>11.421429</td>\n",
              "      <td>11.165714</td>\n",
              "      <td>11.284286</td>\n",
              "      <td>9.768776</td>\n",
              "      <td>378244300</td>\n",
              "      <td>0.042244</td>\n",
              "      <td>0.000494</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-20</th>\n",
              "      <td>2006-10-20</td>\n",
              "      <td>11.281428</td>\n",
              "      <td>11.427143</td>\n",
              "      <td>11.238571</td>\n",
              "      <td>11.421429</td>\n",
              "      <td>9.887502</td>\n",
              "      <td>159853400</td>\n",
              "      <td>0.092088</td>\n",
              "      <td>0.018813</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-23</th>\n",
              "      <td>2006-10-23</td>\n",
              "      <td>11.427143</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>11.392858</td>\n",
              "      <td>11.637143</td>\n",
              "      <td>10.074244</td>\n",
              "      <td>208126800</td>\n",
              "      <td>0.147298</td>\n",
              "      <td>0.044510</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-24</th>\n",
              "      <td>2006-10-24</td>\n",
              "      <td>11.601429</td>\n",
              "      <td>11.668571</td>\n",
              "      <td>11.457143</td>\n",
              "      <td>11.578571</td>\n",
              "      <td>10.023538</td>\n",
              "      <td>115803100</td>\n",
              "      <td>0.184203</td>\n",
              "      <td>0.072449</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-25</th>\n",
              "      <td>2006-10-25</td>\n",
              "      <td>11.621428</td>\n",
              "      <td>11.714286</td>\n",
              "      <td>11.572857</td>\n",
              "      <td>11.668571</td>\n",
              "      <td>10.101451</td>\n",
              "      <td>121303700</td>\n",
              "      <td>0.218198</td>\n",
              "      <td>0.101599</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-26</th>\n",
              "      <td>2006-10-26</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>11.800000</td>\n",
              "      <td>11.590000</td>\n",
              "      <td>11.741428</td>\n",
              "      <td>10.164527</td>\n",
              "      <td>108189200</td>\n",
              "      <td>0.248157</td>\n",
              "      <td>0.130910</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-27</th>\n",
              "      <td>2006-10-27</td>\n",
              "      <td>11.678572</td>\n",
              "      <td>11.778571</td>\n",
              "      <td>11.430000</td>\n",
              "      <td>11.487143</td>\n",
              "      <td>9.944393</td>\n",
              "      <td>148741600</td>\n",
              "      <td>0.248516</td>\n",
              "      <td>0.154431</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-30</th>\n",
              "      <td>2006-10-30</td>\n",
              "      <td>11.427143</td>\n",
              "      <td>11.557143</td>\n",
              "      <td>11.357142</td>\n",
              "      <td>11.488571</td>\n",
              "      <td>9.945626</td>\n",
              "      <td>124979400</td>\n",
              "      <td>0.246080</td>\n",
              "      <td>0.172761</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-10-31</th>\n",
              "      <td>2006-10-31</td>\n",
              "      <td>11.635715</td>\n",
              "      <td>11.668571</td>\n",
              "      <td>11.461429</td>\n",
              "      <td>11.582857</td>\n",
              "      <td>10.027248</td>\n",
              "      <td>125368600</td>\n",
              "      <td>0.248888</td>\n",
              "      <td>0.187986</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-01</th>\n",
              "      <td>2006-11-01</td>\n",
              "      <td>11.585714</td>\n",
              "      <td>11.625714</td>\n",
              "      <td>11.194285</td>\n",
              "      <td>11.308572</td>\n",
              "      <td>9.789802</td>\n",
              "      <td>152798100</td>\n",
              "      <td>0.226371</td>\n",
              "      <td>0.195663</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-02</th>\n",
              "      <td>2006-11-02</td>\n",
              "      <td>11.274285</td>\n",
              "      <td>11.331429</td>\n",
              "      <td>11.214286</td>\n",
              "      <td>11.282857</td>\n",
              "      <td>9.767539</td>\n",
              "      <td>116370800</td>\n",
              "      <td>0.204099</td>\n",
              "      <td>0.197350</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-03</th>\n",
              "      <td>2006-11-03</td>\n",
              "      <td>11.337143</td>\n",
              "      <td>11.361428</td>\n",
              "      <td>11.112857</td>\n",
              "      <td>11.184286</td>\n",
              "      <td>9.682207</td>\n",
              "      <td>107972200</td>\n",
              "      <td>0.176460</td>\n",
              "      <td>0.193172</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.184286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-06</th>\n",
              "      <td>2006-11-06</td>\n",
              "      <td>11.278571</td>\n",
              "      <td>11.437143</td>\n",
              "      <td>11.204286</td>\n",
              "      <td>11.387143</td>\n",
              "      <td>9.857821</td>\n",
              "      <td>108644200</td>\n",
              "      <td>0.168977</td>\n",
              "      <td>0.188333</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-07</th>\n",
              "      <td>2006-11-07</td>\n",
              "      <td>11.492857</td>\n",
              "      <td>11.571428</td>\n",
              "      <td>11.447143</td>\n",
              "      <td>11.501429</td>\n",
              "      <td>9.956757</td>\n",
              "      <td>131483100</td>\n",
              "      <td>0.170305</td>\n",
              "      <td>0.184728</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-08</th>\n",
              "      <td>2006-11-08</td>\n",
              "      <td>11.431429</td>\n",
              "      <td>11.812857</td>\n",
              "      <td>11.412857</td>\n",
              "      <td>11.778571</td>\n",
              "      <td>10.196676</td>\n",
              "      <td>172729200</td>\n",
              "      <td>0.191514</td>\n",
              "      <td>0.186085</td>\n",
              "      <td>11.778571</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-09</th>\n",
              "      <td>2006-11-09</td>\n",
              "      <td>11.842857</td>\n",
              "      <td>12.098572</td>\n",
              "      <td>11.731428</td>\n",
              "      <td>11.905714</td>\n",
              "      <td>10.306746</td>\n",
              "      <td>230763400</td>\n",
              "      <td>0.216090</td>\n",
              "      <td>0.192086</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-10</th>\n",
              "      <td>2006-11-10</td>\n",
              "      <td>11.935715</td>\n",
              "      <td>11.942857</td>\n",
              "      <td>11.785714</td>\n",
              "      <td>11.874286</td>\n",
              "      <td>10.279537</td>\n",
              "      <td>93466100</td>\n",
              "      <td>0.230375</td>\n",
              "      <td>0.199744</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-13</th>\n",
              "      <td>2006-11-13</td>\n",
              "      <td>11.888572</td>\n",
              "      <td>12.064285</td>\n",
              "      <td>11.805715</td>\n",
              "      <td>12.050000</td>\n",
              "      <td>10.431654</td>\n",
              "      <td>112668500</td>\n",
              "      <td>0.252959</td>\n",
              "      <td>0.210387</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-14</th>\n",
              "      <td>2006-11-14</td>\n",
              "      <td>12.114285</td>\n",
              "      <td>12.142858</td>\n",
              "      <td>11.985714</td>\n",
              "      <td>12.142858</td>\n",
              "      <td>10.512039</td>\n",
              "      <td>147238700</td>\n",
              "      <td>0.275177</td>\n",
              "      <td>0.223345</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-15</th>\n",
              "      <td>2006-11-15</td>\n",
              "      <td>12.150000</td>\n",
              "      <td>12.271428</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>12.007143</td>\n",
              "      <td>10.394552</td>\n",
              "      <td>163830800</td>\n",
              "      <td>0.278623</td>\n",
              "      <td>0.234400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-16</th>\n",
              "      <td>2006-11-16</td>\n",
              "      <td>12.124286</td>\n",
              "      <td>12.328571</td>\n",
              "      <td>12.088572</td>\n",
              "      <td>12.230000</td>\n",
              "      <td>10.587480</td>\n",
              "      <td>173485200</td>\n",
              "      <td>0.295925</td>\n",
              "      <td>0.246705</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-17</th>\n",
              "      <td>2006-11-17</td>\n",
              "      <td>12.162857</td>\n",
              "      <td>12.277143</td>\n",
              "      <td>12.142858</td>\n",
              "      <td>12.264286</td>\n",
              "      <td>10.617161</td>\n",
              "      <td>116606000</td>\n",
              "      <td>0.308843</td>\n",
              "      <td>0.259133</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-20</th>\n",
              "      <td>2006-11-20</td>\n",
              "      <td>12.200000</td>\n",
              "      <td>12.428572</td>\n",
              "      <td>12.171429</td>\n",
              "      <td>12.352858</td>\n",
              "      <td>10.693839</td>\n",
              "      <td>142698500</td>\n",
              "      <td>0.322510</td>\n",
              "      <td>0.271808</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-21</th>\n",
              "      <td>2006-11-21</td>\n",
              "      <td>12.488571</td>\n",
              "      <td>12.657143</td>\n",
              "      <td>12.444285</td>\n",
              "      <td>12.657143</td>\n",
              "      <td>10.957254</td>\n",
              "      <td>155666700</td>\n",
              "      <td>0.353817</td>\n",
              "      <td>0.288210</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-22</th>\n",
              "      <td>2006-11-22</td>\n",
              "      <td>12.712857</td>\n",
              "      <td>12.964286</td>\n",
              "      <td>12.550000</td>\n",
              "      <td>12.901428</td>\n",
              "      <td>11.168736</td>\n",
              "      <td>167985300</td>\n",
              "      <td>0.393799</td>\n",
              "      <td>0.309328</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-24</th>\n",
              "      <td>2006-11-24</td>\n",
              "      <td>12.790000</td>\n",
              "      <td>13.297143</td>\n",
              "      <td>12.785714</td>\n",
              "      <td>13.090000</td>\n",
              "      <td>11.331979</td>\n",
              "      <td>129669400</td>\n",
              "      <td>0.435680</td>\n",
              "      <td>0.334598</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-27</th>\n",
              "      <td>2006-11-27</td>\n",
              "      <td>13.215714</td>\n",
              "      <td>13.308572</td>\n",
              "      <td>12.785714</td>\n",
              "      <td>12.791429</td>\n",
              "      <td>11.073504</td>\n",
              "      <td>268709000</td>\n",
              "      <td>0.439709</td>\n",
              "      <td>0.355620</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-28</th>\n",
              "      <td>2006-11-28</td>\n",
              "      <td>12.908571</td>\n",
              "      <td>13.138572</td>\n",
              "      <td>12.844286</td>\n",
              "      <td>13.115714</td>\n",
              "      <td>11.354239</td>\n",
              "      <td>259043400</td>\n",
              "      <td>0.463724</td>\n",
              "      <td>0.377241</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-29</th>\n",
              "      <td>2006-11-29</td>\n",
              "      <td>13.285714</td>\n",
              "      <td>13.307143</td>\n",
              "      <td>12.892858</td>\n",
              "      <td>13.114285</td>\n",
              "      <td>11.353003</td>\n",
              "      <td>289270800</td>\n",
              "      <td>0.477141</td>\n",
              "      <td>0.397221</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-11-30</th>\n",
              "      <td>2006-11-30</td>\n",
              "      <td>13.172857</td>\n",
              "      <td>13.240000</td>\n",
              "      <td>13.008572</td>\n",
              "      <td>13.094286</td>\n",
              "      <td>11.335690</td>\n",
              "      <td>217621600</td>\n",
              "      <td>0.480620</td>\n",
              "      <td>0.413901</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-01</th>\n",
              "      <td>2006-12-01</td>\n",
              "      <td>13.114285</td>\n",
              "      <td>13.190000</td>\n",
              "      <td>12.871428</td>\n",
              "      <td>13.045714</td>\n",
              "      <td>11.293642</td>\n",
              "      <td>198769900</td>\n",
              "      <td>0.473993</td>\n",
              "      <td>0.425919</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-04</th>\n",
              "      <td>2006-12-04</td>\n",
              "      <td>13.125714</td>\n",
              "      <td>13.150000</td>\n",
              "      <td>12.928572</td>\n",
              "      <td>13.017143</td>\n",
              "      <td>11.268908</td>\n",
              "      <td>177384200</td>\n",
              "      <td>0.461121</td>\n",
              "      <td>0.432960</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-05</th>\n",
              "      <td>2006-12-05</td>\n",
              "      <td>13.092857</td>\n",
              "      <td>13.190000</td>\n",
              "      <td>12.981428</td>\n",
              "      <td>13.038571</td>\n",
              "      <td>11.287459</td>\n",
              "      <td>165709600</td>\n",
              "      <td>0.447490</td>\n",
              "      <td>0.435866</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-06</th>\n",
              "      <td>2006-12-06</td>\n",
              "      <td>12.948571</td>\n",
              "      <td>13.055715</td>\n",
              "      <td>12.810000</td>\n",
              "      <td>12.832857</td>\n",
              "      <td>11.109372</td>\n",
              "      <td>159546100</td>\n",
              "      <td>0.415301</td>\n",
              "      <td>0.431753</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.832857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-07</th>\n",
              "      <td>2006-12-07</td>\n",
              "      <td>12.861428</td>\n",
              "      <td>12.928572</td>\n",
              "      <td>12.414286</td>\n",
              "      <td>12.434286</td>\n",
              "      <td>10.764329</td>\n",
              "      <td>251206900</td>\n",
              "      <td>0.353554</td>\n",
              "      <td>0.416113</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-08</th>\n",
              "      <td>2006-12-08</td>\n",
              "      <td>12.461429</td>\n",
              "      <td>12.770000</td>\n",
              "      <td>12.428572</td>\n",
              "      <td>12.608571</td>\n",
              "      <td>10.915209</td>\n",
              "      <td>196069300</td>\n",
              "      <td>0.315051</td>\n",
              "      <td>0.395901</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-11</th>\n",
              "      <td>2006-12-11</td>\n",
              "      <td>12.700000</td>\n",
              "      <td>12.757143</td>\n",
              "      <td>12.578571</td>\n",
              "      <td>12.678572</td>\n",
              "      <td>10.975807</td>\n",
              "      <td>124945100</td>\n",
              "      <td>0.286878</td>\n",
              "      <td>0.374096</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-12</th>\n",
              "      <td>2006-12-12</td>\n",
              "      <td>12.658571</td>\n",
              "      <td>12.691428</td>\n",
              "      <td>12.218572</td>\n",
              "      <td>12.305715</td>\n",
              "      <td>10.653026</td>\n",
              "      <td>256655000</td>\n",
              "      <td>0.231793</td>\n",
              "      <td>0.345635</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-13</th>\n",
              "      <td>2006-12-13</td>\n",
              "      <td>12.564285</td>\n",
              "      <td>12.724286</td>\n",
              "      <td>12.450000</td>\n",
              "      <td>12.721429</td>\n",
              "      <td>11.012909</td>\n",
              "      <td>214263000</td>\n",
              "      <td>0.219155</td>\n",
              "      <td>0.320339</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-14</th>\n",
              "      <td>2006-12-14</td>\n",
              "      <td>12.721429</td>\n",
              "      <td>12.857142</td>\n",
              "      <td>12.608571</td>\n",
              "      <td>12.650000</td>\n",
              "      <td>10.951073</td>\n",
              "      <td>208082700</td>\n",
              "      <td>0.201059</td>\n",
              "      <td>0.296483</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-15</th>\n",
              "      <td>2006-12-15</td>\n",
              "      <td>12.717143</td>\n",
              "      <td>12.745714</td>\n",
              "      <td>12.475715</td>\n",
              "      <td>12.531428</td>\n",
              "      <td>10.848425</td>\n",
              "      <td>184984800</td>\n",
              "      <td>0.175131</td>\n",
              "      <td>0.272213</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-18</th>\n",
              "      <td>2006-12-18</td>\n",
              "      <td>12.518572</td>\n",
              "      <td>12.571428</td>\n",
              "      <td>12.084286</td>\n",
              "      <td>12.210000</td>\n",
              "      <td>10.570165</td>\n",
              "      <td>180394200</td>\n",
              "      <td>0.127180</td>\n",
              "      <td>0.243206</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-19</th>\n",
              "      <td>2006-12-19</td>\n",
              "      <td>12.104285</td>\n",
              "      <td>12.382857</td>\n",
              "      <td>11.945714</td>\n",
              "      <td>12.330000</td>\n",
              "      <td>10.674047</td>\n",
              "      <td>227851400</td>\n",
              "      <td>0.097735</td>\n",
              "      <td>0.214112</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-20</th>\n",
              "      <td>2006-12-20</td>\n",
              "      <td>12.352858</td>\n",
              "      <td>12.381429</td>\n",
              "      <td>12.105714</td>\n",
              "      <td>12.108571</td>\n",
              "      <td>10.482360</td>\n",
              "      <td>141922900</td>\n",
              "      <td>0.055888</td>\n",
              "      <td>0.182467</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-21</th>\n",
              "      <td>2006-12-21</td>\n",
              "      <td>12.100000</td>\n",
              "      <td>12.211429</td>\n",
              "      <td>11.742857</td>\n",
              "      <td>11.842857</td>\n",
              "      <td>10.252333</td>\n",
              "      <td>225899800</td>\n",
              "      <td>0.001268</td>\n",
              "      <td>0.146227</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-22</th>\n",
              "      <td>2006-12-22</td>\n",
              "      <td>11.922857</td>\n",
              "      <td>12.005714</td>\n",
              "      <td>11.657143</td>\n",
              "      <td>11.742857</td>\n",
              "      <td>10.165761</td>\n",
              "      <td>153325900</td>\n",
              "      <td>-0.049517</td>\n",
              "      <td>0.107078</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006-12-26</th>\n",
              "      <td>2006-12-26</td>\n",
              "      <td>11.735714</td>\n",
              "      <td>11.795714</td>\n",
              "      <td>11.555715</td>\n",
              "      <td>11.644286</td>\n",
              "      <td>10.080429</td>\n",
              "      <td>122672200</td>\n",
              "      <td>-0.096605</td>\n",
              "      <td>0.066342</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  Date       Open  ...  Buy_Signal_Price  Sell_Signal_Price\n",
              "2006-10-02  2006-10-02  10.728572  ...               NaN                NaN\n",
              "2006-10-03  2006-10-03  10.635715  ...               NaN          10.582857\n",
              "2006-10-04  2006-10-04  10.585714  ...         10.768572                NaN\n",
              "2006-10-05  2006-10-05  10.647142  ...               NaN                NaN\n",
              "2006-10-06  2006-10-06  10.631429  ...               NaN          10.602858\n",
              "2006-10-09  2006-10-09  10.542857  ...               NaN                NaN\n",
              "2006-10-10  2006-10-10  10.648571  ...               NaN                NaN\n",
              "2006-10-11  2006-10-11  10.488571  ...               NaN                NaN\n",
              "2006-10-12  2006-10-12  10.515715  ...               NaN                NaN\n",
              "2006-10-13  2006-10-13  10.804286  ...         10.717143                NaN\n",
              "2006-10-16  2006-10-16  10.741428  ...               NaN                NaN\n",
              "2006-10-17  2006-10-17  10.720000  ...               NaN                NaN\n",
              "2006-10-18  2006-10-18  10.678572  ...               NaN                NaN\n",
              "2006-10-19  2006-10-19  11.322857  ...               NaN                NaN\n",
              "2006-10-20  2006-10-20  11.281428  ...               NaN                NaN\n",
              "2006-10-23  2006-10-23  11.427143  ...               NaN                NaN\n",
              "2006-10-24  2006-10-24  11.601429  ...               NaN                NaN\n",
              "2006-10-25  2006-10-25  11.621428  ...               NaN                NaN\n",
              "2006-10-26  2006-10-26  11.700000  ...               NaN                NaN\n",
              "2006-10-27  2006-10-27  11.678572  ...               NaN                NaN\n",
              "2006-10-30  2006-10-30  11.427143  ...               NaN                NaN\n",
              "2006-10-31  2006-10-31  11.635715  ...               NaN                NaN\n",
              "2006-11-01  2006-11-01  11.585714  ...               NaN                NaN\n",
              "2006-11-02  2006-11-02  11.274285  ...               NaN                NaN\n",
              "2006-11-03  2006-11-03  11.337143  ...               NaN          11.184286\n",
              "2006-11-06  2006-11-06  11.278571  ...               NaN                NaN\n",
              "2006-11-07  2006-11-07  11.492857  ...               NaN                NaN\n",
              "2006-11-08  2006-11-08  11.431429  ...         11.778571                NaN\n",
              "2006-11-09  2006-11-09  11.842857  ...               NaN                NaN\n",
              "2006-11-10  2006-11-10  11.935715  ...               NaN                NaN\n",
              "2006-11-13  2006-11-13  11.888572  ...               NaN                NaN\n",
              "2006-11-14  2006-11-14  12.114285  ...               NaN                NaN\n",
              "2006-11-15  2006-11-15  12.150000  ...               NaN                NaN\n",
              "2006-11-16  2006-11-16  12.124286  ...               NaN                NaN\n",
              "2006-11-17  2006-11-17  12.162857  ...               NaN                NaN\n",
              "2006-11-20  2006-11-20  12.200000  ...               NaN                NaN\n",
              "2006-11-21  2006-11-21  12.488571  ...               NaN                NaN\n",
              "2006-11-22  2006-11-22  12.712857  ...               NaN                NaN\n",
              "2006-11-24  2006-11-24  12.790000  ...               NaN                NaN\n",
              "2006-11-27  2006-11-27  13.215714  ...               NaN                NaN\n",
              "2006-11-28  2006-11-28  12.908571  ...               NaN                NaN\n",
              "2006-11-29  2006-11-29  13.285714  ...               NaN                NaN\n",
              "2006-11-30  2006-11-30  13.172857  ...               NaN                NaN\n",
              "2006-12-01  2006-12-01  13.114285  ...               NaN                NaN\n",
              "2006-12-04  2006-12-04  13.125714  ...               NaN                NaN\n",
              "2006-12-05  2006-12-05  13.092857  ...               NaN                NaN\n",
              "2006-12-06  2006-12-06  12.948571  ...               NaN          12.832857\n",
              "2006-12-07  2006-12-07  12.861428  ...               NaN                NaN\n",
              "2006-12-08  2006-12-08  12.461429  ...               NaN                NaN\n",
              "2006-12-11  2006-12-11  12.700000  ...               NaN                NaN\n",
              "2006-12-12  2006-12-12  12.658571  ...               NaN                NaN\n",
              "2006-12-13  2006-12-13  12.564285  ...               NaN                NaN\n",
              "2006-12-14  2006-12-14  12.721429  ...               NaN                NaN\n",
              "2006-12-15  2006-12-15  12.717143  ...               NaN                NaN\n",
              "2006-12-18  2006-12-18  12.518572  ...               NaN                NaN\n",
              "2006-12-19  2006-12-19  12.104285  ...               NaN                NaN\n",
              "2006-12-20  2006-12-20  12.352858  ...               NaN                NaN\n",
              "2006-12-21  2006-12-21  12.100000  ...               NaN                NaN\n",
              "2006-12-22  2006-12-22  11.922857  ...               NaN                NaN\n",
              "2006-12-26  2006-12-26  11.735714  ...               NaN                NaN\n",
              "\n",
              "[60 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EHUicpQkc46j",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 873
        },
        "outputId": "357ac34c-b2f8-4e1a-b2e8-5da5b03818ea"
      },
      "source": [
        "# Plot the data with buy and signal markers\n",
        "plt.figure(figsize=(20.5,12.5)) # sizes are in inches\n",
        "\n",
        "# Close Price\n",
        "plt.plot(AAPL['Close'],label='Close Price', alpha = 0.35)\n",
        "\n",
        "# Buy Signal\n",
        "plt.scatter(AAPL.index, AAPL['Buy_Signal_Price'], label = 'Buy', marker = \"^\", color=\"green\",s=100) # Decision Made to buy\n",
        "\n",
        "# Sell Signal\n",
        "plt.scatter(AAPL.index,AAPL['Sell_Signal_Price'], label = 'Sell',  marker = \"v\", color=\"red\",s=100) # long term moving avg\n",
        "\n",
        "plt.title('Apple Close Price History- Buy & Sell Signals')\n",
        "plt.xlabel('02 Oct 2006 - 26th Dec 2006')\n",
        "plt.xticks(rotation=45)\n",
        "plt.xticks(rotation = 45)\n",
        "plt.ylabel('Close Price USD ($)')\n",
        "plt.legend(loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}