Three_Moving_Avg_Crossover.ipynb

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  "metadata": {
    "colab": {
      "name": "Three-Moving-Avg-Crossover.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyPXKMdicPqaNkKGEUVM3FjL",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ktiwari9/algotradingbot/blob/master/Three_Moving_Avg_Crossover.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xFuh6kP-N3ev",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Description: Three Moving Average Crossover trading strategy which encompasses short, medium/middle, and long/slow moving average.\n",
        "# There are 2 Buy & Sell Signals in this strategy: crossover of short over middle and middle over long.\n",
        "# Inspired by: https://www.youtube.com/watch?v=rO_cqa4x60o\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6ZQQzoIUQmru",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# All necessary imports\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('fivethirtyeight')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2YPYK_wEQrIq",
        "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": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uiiXK1c3RCje",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "eb7b8a26-a151-476b-f1fe-74a8ebaea55c"
      },
      "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": null,
      "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": "fjhdDbTYRKhE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "outputId": "d2d382e1-420e-42c8-c1ce-5d5277124ef8"
      },
      "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": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GiWfW43lRRed",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Calculate the three moving averages\n",
        "\n",
        "# Calculate the short term exponential moving average (SEMA)\n",
        "shortPeriod = 5\n",
        "Short_EMA = AAPL.Close.ewm(span=shortPeriod, adjust= False).mean()\n",
        "\n",
        "# Calculate the medium exponential moving average (MEMA)\n",
        "medPeriod = 21\n",
        "Med_EMA = AAPL.Close.ewm(span=medPeriod, adjust= False).mean()\n",
        "\n",
        "# Calculate the long term exponential moving average (SEMA)\n",
        "longPeriod = 63 \n",
        "Long_EMA = AAPL.Close.ewm(span=longPeriod, adjust= False).mean()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mz_9A-0xSOpR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "outputId": "915b4d4b-1cf3-47ba-8b8c-0241029957a2"
      },
      "source": [
        "# Plot the 3 moving averages\n",
        "\n",
        "plt.figure(figsize=(20.5,12.5)) # sizes are in inches\n",
        "plt.plot(AAPL['Close'], label = 'AAPL Close') # Close Price\n",
        "\n",
        "plt.plot(Short_EMA, label = 'SEMA') # Short Average\n",
        "plt.plot(Med_EMA, label = 'MEMA') # Medium Average\n",
        "plt.plot(Long_EMA, label = 'LEMA') # Long Average\n",
        "\n",
        "\n",
        "plt.title('Apple Close Price History')\n",
        "plt.xlabel('02 Oct 2006 - 26th Dec 2006')\n",
        "plt.xticks(rotation=45)\n",
        "plt.ylabel('Close Price USD ($)')\n",
        "plt.legend(loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_kabILaTTJZz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "659650f3-6cbb-4745-c541-a50f1223b8eb"
      },
      "source": [
        "# Store EMAs in the dataset\n",
        "AAPL['SEMA'] = Short_EMA\n",
        "AAPL['MEMA'] = Med_EMA\n",
        "AAPL['LEMA'] = Long_EMA\n",
        "AAPL"
      ],
      "execution_count": null,
      "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>SEMA</th>\n",
              "      <th>MEMA</th>\n",
              "      <th>LEMA</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>10.694285</td>\n",
              "      <td>10.694285</td>\n",
              "      <td>10.694285</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>10.657142</td>\n",
              "      <td>10.684155</td>\n",
              "      <td>10.690803</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>10.694286</td>\n",
              "      <td>10.691829</td>\n",
              "      <td>10.693233</td>\n",
              "      <td>NaN</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>10.692857</td>\n",
              "      <td>10.691663</td>\n",
              "      <td>10.693132</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>10.662857</td>\n",
              "      <td>10.683590</td>\n",
              "      <td>10.690311</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>10.662381</td>\n",
              "      <td>10.681575</td>\n",
              "      <td>10.689408</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>10.623016</td>\n",
              "      <td>10.669094</td>\n",
              "      <td>10.684873</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>10.569154</td>\n",
              "      <td>10.650216</td>\n",
              "      <td>10.677891</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>10.629912</td>\n",
              "      <td>10.659417</td>\n",
              "      <td>10.680189</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>10.658989</td>\n",
              "      <td>10.664665</td>\n",
              "      <td>10.681344</td>\n",
              "      <td>NaN</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>10.696469</td>\n",
              "      <td>10.674370</td>\n",
              "      <td>10.684159</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>10.668598</td>\n",
              "      <td>10.668778</td>\n",
              "      <td>10.681931</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>10.661446</td>\n",
              "      <td>10.666811</td>\n",
              "      <td>10.680843</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>10.869059</td>\n",
              "      <td>10.722945</td>\n",
              "      <td>10.699701</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>11.053183</td>\n",
              "      <td>10.786444</td>\n",
              "      <td>10.722255</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>11.247836</td>\n",
              "      <td>10.863780</td>\n",
              "      <td>10.750845</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>11.358081</td>\n",
              "      <td>10.928761</td>\n",
              "      <td>10.776712</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>11.461578</td>\n",
              "      <td>10.996017</td>\n",
              "      <td>10.804582</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>11.554861</td>\n",
              "      <td>11.063781</td>\n",
              "      <td>10.833859</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>11.532288</td>\n",
              "      <td>11.102269</td>\n",
              "      <td>10.854274</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>11.517716</td>\n",
              "      <td>11.137387</td>\n",
              "      <td>10.874096</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>11.539430</td>\n",
              "      <td>11.177884</td>\n",
              "      <td>10.896244</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>11.462477</td>\n",
              "      <td>11.189765</td>\n",
              "      <td>10.909130</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>11.402604</td>\n",
              "      <td>11.198228</td>\n",
              "      <td>10.920809</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>11.329831</td>\n",
              "      <td>11.196961</td>\n",
              "      <td>10.929042</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>11.348935</td>\n",
              "      <td>11.214250</td>\n",
              "      <td>10.943358</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>11.399766</td>\n",
              "      <td>11.240357</td>\n",
              "      <td>10.960798</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>11.526035</td>\n",
              "      <td>11.289286</td>\n",
              "      <td>10.986353</td>\n",
              "      <td>NaN</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>11.652594</td>\n",
              "      <td>11.345325</td>\n",
              "      <td>11.015083</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>11.726492</td>\n",
              "      <td>11.393412</td>\n",
              "      <td>11.041933</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>11.834328</td>\n",
              "      <td>11.453102</td>\n",
              "      <td>11.073435</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>11.937171</td>\n",
              "      <td>11.515807</td>\n",
              "      <td>11.106855</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>11.960495</td>\n",
              "      <td>11.560474</td>\n",
              "      <td>11.134989</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>12.050330</td>\n",
              "      <td>11.621340</td>\n",
              "      <td>11.169208</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>12.121649</td>\n",
              "      <td>11.679789</td>\n",
              "      <td>11.203429</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>12.198718</td>\n",
              "      <td>11.740978</td>\n",
              "      <td>11.239349</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>12.351527</td>\n",
              "      <td>11.824265</td>\n",
              "      <td>11.283655</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>12.534827</td>\n",
              "      <td>11.922189</td>\n",
              "      <td>11.334210</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>12.719885</td>\n",
              "      <td>12.028354</td>\n",
              "      <td>11.389079</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>12.743733</td>\n",
              "      <td>12.097724</td>\n",
              "      <td>11.432902</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>12.867727</td>\n",
              "      <td>12.190269</td>\n",
              "      <td>11.485490</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>12.949913</td>\n",
              "      <td>12.274270</td>\n",
              "      <td>11.536390</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>12.998037</td>\n",
              "      <td>12.348817</td>\n",
              "      <td>11.585074</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>13.013929</td>\n",
              "      <td>12.412171</td>\n",
              "      <td>11.630719</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>13.015001</td>\n",
              "      <td>12.467169</td>\n",
              "      <td>11.674045</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>13.022857</td>\n",
              "      <td>12.519114</td>\n",
              "      <td>11.716686</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>12.959524</td>\n",
              "      <td>12.547637</td>\n",
              "      <td>11.751567</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>12.784445</td>\n",
              "      <td>12.537332</td>\n",
              "      <td>11.772902</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>12.725820</td>\n",
              "      <td>12.543808</td>\n",
              "      <td>11.799016</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>12.710071</td>\n",
              "      <td>12.556059</td>\n",
              "      <td>11.826502</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>12.575285</td>\n",
              "      <td>12.533301</td>\n",
              "      <td>11.841478</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>12.624000</td>\n",
              "      <td>12.550403</td>\n",
              "      <td>11.868976</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>12.632667</td>\n",
              "      <td>12.559458</td>\n",
              "      <td>11.893383</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>12.598920</td>\n",
              "      <td>12.556910</td>\n",
              "      <td>11.913322</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>12.469280</td>\n",
              "      <td>12.525372</td>\n",
              "      <td>11.922593</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>12.422854</td>\n",
              "      <td>12.507611</td>\n",
              "      <td>11.935325</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>12.318093</td>\n",
              "      <td>12.471335</td>\n",
              "      <td>11.940739</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>12.159681</td>\n",
              "      <td>12.414200</td>\n",
              "      <td>11.937680</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>12.020740</td>\n",
              "      <td>12.353169</td>\n",
              "      <td>11.931592</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>11.895255</td>\n",
              "      <td>12.288725</td>\n",
              "      <td>11.922613</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                NaN\n",
              "2006-10-04  2006-10-04  10.585714  ...               NaN                NaN\n",
              "2006-10-05  2006-10-05  10.647142  ...               NaN                NaN\n",
              "2006-10-06  2006-10-06  10.631429  ...               NaN                NaN\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  ...               NaN                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                NaN\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  ...               NaN                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                NaN\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 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oBCuYBs0T1F2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Investment signal\n",
        "def investment_signal(data):\n",
        "  sigPriceToBuy = []\n",
        "  sigPriceToSell = []\n",
        "  flagLong = 0 # flag to check when STMA crosses over LTMA\n",
        "  flagShort = 0 \n",
        "  for i in range(len(data)):\n",
        "    if data['MEMA'][i]< data['LEMA'][i] and data['SEMA'][i]< data['MEMA'][i] and flagLong == 0 and flagShort == 0:\n",
        "        sigPriceToBuy.append(data['Close'][i]) # good time to buy\n",
        "        sigPriceToSell.append(np.nan)\n",
        "        flagShort = 1\n",
        "    \n",
        "    elif data['SEMA'][i]> data['MEMA'][i] and flagShort == 1:\n",
        "        sigPriceToBuy.append(np.nan) \n",
        "        sigPriceToSell.append(data['Close'][i]) # good time to sell\n",
        "        flagShort = 0\n",
        "        \n",
        "    elif data['MEMA'][i]> data['LEMA'][i] and data['SEMA'][i]> data['MEMA'][i] and flagLong == 0 and flagShort == 0:\n",
        "        sigPriceToBuy.append(np.nan)\n",
        "        sigPriceToSell.append(np.nan)\n",
        "        flagLong =1\n",
        "    \n",
        "    elif data['SEMA'][i]< data['MEMA'][i] and flagLong == 1:\n",
        "        sigPriceToBuy.append(np.nan) \n",
        "        sigPriceToSell.append(data['Close'][i]) # good time to sell\n",
        "        flagLong = 0    \n",
        "\n",
        "    else:\n",
        "      sigPriceToBuy.append(np.nan)\n",
        "      sigPriceToSell.append(np.nan)\n",
        "\n",
        "  return (sigPriceToBuy,sigPriceToSell)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vr110oWSaqvU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1d84718a-35ae-4598-f794-39379cc2b5d6"
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "</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>SEMA</th>\n",
              "      <th>MEMA</th>\n",
              "      <th>LEMA</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>10.694285</td>\n",
              "      <td>10.694285</td>\n",
              "      <td>10.694285</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>10.657142</td>\n",
              "      <td>10.684155</td>\n",
              "      <td>10.690803</td>\n",
              "      <td>10.582857</td>\n",
              "      <td>NaN</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>10.694286</td>\n",
              "      <td>10.691829</td>\n",
              "      <td>10.693233</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.768572</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>10.692857</td>\n",
              "      <td>10.691663</td>\n",
              "      <td>10.693132</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>10.662857</td>\n",
              "      <td>10.683590</td>\n",
              "      <td>10.690311</td>\n",
              "      <td>10.602858</td>\n",
              "      <td>NaN</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>10.662381</td>\n",
              "      <td>10.681575</td>\n",
              "      <td>10.689408</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>10.623016</td>\n",
              "      <td>10.669094</td>\n",
              "      <td>10.684873</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>10.569154</td>\n",
              "      <td>10.650216</td>\n",
              "      <td>10.677891</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>10.629912</td>\n",
              "      <td>10.659417</td>\n",
              "      <td>10.680189</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>10.658989</td>\n",
              "      <td>10.664665</td>\n",
              "      <td>10.681344</td>\n",
              "      <td>NaN</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>10.696469</td>\n",
              "      <td>10.674370</td>\n",
              "      <td>10.684159</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10.771428</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>10.668598</td>\n",
              "      <td>10.668778</td>\n",
              "      <td>10.681931</td>\n",
              "      <td>10.612857</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>10.661446</td>\n",
              "      <td>10.666811</td>\n",
              "      <td>10.680843</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>10.869059</td>\n",
              "      <td>10.722945</td>\n",
              "      <td>10.699701</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11.284286</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>11.053183</td>\n",
              "      <td>10.786444</td>\n",
              "      <td>10.722255</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>11.247836</td>\n",
              "      <td>10.863780</td>\n",
              "      <td>10.750845</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>11.358081</td>\n",
              "      <td>10.928761</td>\n",
              "      <td>10.776712</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>11.461578</td>\n",
              "      <td>10.996017</td>\n",
              "      <td>10.804582</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>11.554861</td>\n",
              "      <td>11.063781</td>\n",
              "      <td>10.833859</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>11.532288</td>\n",
              "      <td>11.102269</td>\n",
              "      <td>10.854274</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>11.517716</td>\n",
              "      <td>11.137387</td>\n",
              "      <td>10.874096</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>11.539430</td>\n",
              "      <td>11.177884</td>\n",
              "      <td>10.896244</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>11.462477</td>\n",
              "      <td>11.189765</td>\n",
              "      <td>10.909130</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>11.402604</td>\n",
              "      <td>11.198228</td>\n",
              "      <td>10.920809</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>11.329831</td>\n",
              "      <td>11.196961</td>\n",
              "      <td>10.929042</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>11.348935</td>\n",
              "      <td>11.214250</td>\n",
              "      <td>10.943358</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>11.399766</td>\n",
              "      <td>11.240357</td>\n",
              "      <td>10.960798</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>11.526035</td>\n",
              "      <td>11.289286</td>\n",
              "      <td>10.986353</td>\n",
              "      <td>NaN</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>11.652594</td>\n",
              "      <td>11.345325</td>\n",
              "      <td>11.015083</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>11.726492</td>\n",
              "      <td>11.393412</td>\n",
              "      <td>11.041933</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>11.834328</td>\n",
              "      <td>11.453102</td>\n",
              "      <td>11.073435</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>11.937171</td>\n",
              "      <td>11.515807</td>\n",
              "      <td>11.106855</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>11.960495</td>\n",
              "      <td>11.560474</td>\n",
              "      <td>11.134989</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>12.050330</td>\n",
              "      <td>11.621340</td>\n",
              "      <td>11.169208</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>12.121649</td>\n",
              "      <td>11.679789</td>\n",
              "      <td>11.203429</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>12.198718</td>\n",
              "      <td>11.740978</td>\n",
              "      <td>11.239349</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>12.351527</td>\n",
              "      <td>11.824265</td>\n",
              "      <td>11.283655</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>12.534827</td>\n",
              "      <td>11.922189</td>\n",
              "      <td>11.334210</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>12.719885</td>\n",
              "      <td>12.028354</td>\n",
              "      <td>11.389079</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>12.743733</td>\n",
              "      <td>12.097724</td>\n",
              "      <td>11.432902</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>12.867727</td>\n",
              "      <td>12.190269</td>\n",
              "      <td>11.485490</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>12.949913</td>\n",
              "      <td>12.274270</td>\n",
              "      <td>11.536390</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>12.998037</td>\n",
              "      <td>12.348817</td>\n",
              "      <td>11.585074</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>13.013929</td>\n",
              "      <td>12.412171</td>\n",
              "      <td>11.630719</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>13.015001</td>\n",
              "      <td>12.467169</td>\n",
              "      <td>11.674045</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>13.022857</td>\n",
              "      <td>12.519114</td>\n",
              "      <td>11.716686</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>12.959524</td>\n",
              "      <td>12.547637</td>\n",
              "      <td>11.751567</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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>12.784445</td>\n",
              "      <td>12.537332</td>\n",
              "      <td>11.772902</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>12.725820</td>\n",
              "      <td>12.543808</td>\n",
              "      <td>11.799016</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>12.710071</td>\n",
              "      <td>12.556059</td>\n",
              "      <td>11.826502</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>12.575285</td>\n",
              "      <td>12.533301</td>\n",
              "      <td>11.841478</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>12.624000</td>\n",
              "      <td>12.550403</td>\n",
              "      <td>11.868976</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>12.632667</td>\n",
              "      <td>12.559458</td>\n",
              "      <td>11.893383</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>12.598920</td>\n",
              "      <td>12.556910</td>\n",
              "      <td>11.913322</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>12.469280</td>\n",
              "      <td>12.525372</td>\n",
              "      <td>11.922593</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.210000</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>12.422854</td>\n",
              "      <td>12.507611</td>\n",
              "      <td>11.935325</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>12.318093</td>\n",
              "      <td>12.471335</td>\n",
              "      <td>11.940739</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>12.159681</td>\n",
              "      <td>12.414200</td>\n",
              "      <td>11.937680</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>12.020740</td>\n",
              "      <td>12.353169</td>\n",
              "      <td>11.931592</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>11.895255</td>\n",
              "      <td>12.288725</td>\n",
              "      <td>11.922613</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  ...         10.582857                NaN\n",
              "2006-10-04  2006-10-04  10.585714  ...               NaN          10.768572\n",
              "2006-10-05  2006-10-05  10.647142  ...               NaN                NaN\n",
              "2006-10-06  2006-10-06  10.631429  ...         10.602858                NaN\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  ...               NaN                NaN\n",
              "2006-10-16  2006-10-16  10.741428  ...               NaN          10.771428\n",
              "2006-10-17  2006-10-17  10.720000  ...         10.612857                NaN\n",
              "2006-10-18  2006-10-18  10.678572  ...               NaN                NaN\n",
              "2006-10-19  2006-10-19  11.322857  ...               NaN          11.284286\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                NaN\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  ...               NaN                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                NaN\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          12.210000\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 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4SfvgdVXbG94",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 796
        },
        "outputId": "81b24631-2962-4957-97d8-2cdfec02f9f9"
      },
      "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",
        "plt.plot(Short_EMA, label = 'SEMA', alpha = 0.35) # Short Average\n",
        "plt.plot(Med_EMA, label = 'MEMA', alpha = 0.35) # Medium Average\n",
        "plt.plot(Long_EMA, label = 'LEMA', alpha = 0.35) # Long Average\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": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1476x900 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mPr5PbuFcQlr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# TODO: Display net profit/loss"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}