Data_Construction.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ObUaDCL7MDyu"
      },
      "source": [
        "# **This notebook showcases the construction of the additional features (technical indicators) and the feature selection methods that has been implemented**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DwAcW1H-6MqI"
      },
      "source": [
        "# **Installing packages**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SddSd9yvdt9u",
        "outputId": "5c66c0ca-7d62-415e-9c82-75a5f7144b85"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting ta\n",
            "  Downloading ta-0.9.0.tar.gz (25 kB)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from ta) (1.19.5)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from ta) (1.1.5)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->ta) (1.15.0)\n",
            "Building wheels for collected packages: ta\n",
            "  Building wheel for ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ta: filename=ta-0.9.0-py3-none-any.whl size=28908 sha256=86a571a6f68b33b622a45256a7c8321d5c398bf84885e401fcdef259e09933fb\n",
            "  Stored in directory: /root/.cache/pip/wheels/72/78/64/cc1c01506a1010a9845e9bd7c69333730f7174661228ea4f98\n",
            "Successfully built ta\n",
            "Installing collected packages: ta\n",
            "Successfully installed ta-0.9.0\n"
          ]
        }
      ],
      "source": [
        "!pip install ta"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1B2PqxSg6Qz8"
      },
      "source": [
        "# **Importing packages**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q1hMynQ1d-p7",
        "outputId": "370d6e1f-25f4-4b02-c6e1-f7f32921b2d2"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd \n",
        "import numpy as np\n",
        "\n",
        "from ta import momentum, trend, volatility, volume, others\n",
        "import statsmodels.api as sm"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6h49D40q6U1n"
      },
      "source": [
        "# **Loading data**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 710
        },
        "id": "S9vk3PF6eG-K",
        "outputId": "8e31cff1-e360-4b90-af4f-3db7b9b71ee7"
      },
      "outputs": [
        {
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></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>current_ratio</th>\n",
              "      <th>long-term_debt_to_capital</th>\n",
              "      <th>debt_to_equity_ratio</th>\n",
              "      <th>gross_margin</th>\n",
              "      <th>operating_margin</th>\n",
              "      <th>ebit_margin</th>\n",
              "      <th>ebitda_margin</th>\n",
              "      <th>pre-tax_profit_margin</th>\n",
              "      <th>net_profit_margin</th>\n",
              "      <th>asset_turnover</th>\n",
              "      <th>inventory_turnover_ratio</th>\n",
              "      <th>receiveable_turnover</th>\n",
              "      <th>days_sales_in_receivables</th>\n",
              "      <th>roe_-_return_on_equity</th>\n",
              "      <th>return_on_tangible_equity</th>\n",
              "      <th>roa_-_return_on_assets</th>\n",
              "      <th>roi_-_return_on_investment</th>\n",
              "      <th>book_value_per_share</th>\n",
              "      <th>operating_cash_flow_per_share</th>\n",
              "      <th>free_cash_flow_per_share</th>\n",
              "      <th>is_day_start_market</th>\n",
              "      <th>is_day_end_market</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>SMA_5</th>\n",
              "      <th>SMA_10</th>\n",
              "      <th>SMA_20</th>\n",
              "      <th>SMA_50</th>\n",
              "      <th>EMA_5</th>\n",
              "      <th>EMA_10</th>\n",
              "      <th>EMA_20</th>\n",
              "      <th>EMA_50</th>\n",
              "      <th>ATR_14</th>\n",
              "      <th>ADX_14</th>\n",
              "      <th>CCI_14</th>\n",
              "      <th>ROC_10</th>\n",
              "      <th>RSI_14</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>27.847500</td>\n",
              "      <td>27.860001</td>\n",
              "      <td>26.837500</td>\n",
              "      <td>27.332500</td>\n",
              "      <td>24.819241</td>\n",
              "      <td>212818400</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.237</td>\n",
              "      <td>0.3401</td>\n",
              "      <td>40.7792</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.0014</td>\n",
              "      <td>23.3908</td>\n",
              "      <td>0.2221</td>\n",
              "      <td>14.3381</td>\n",
              "      <td>3.1937</td>\n",
              "      <td>28.1807</td>\n",
              "      <td>10.5181</td>\n",
              "      <td>11.2855</td>\n",
              "      <td>5.1950</td>\n",
              "      <td>8.0253</td>\n",
              "      <td>5.5970</td>\n",
              "      <td>0.8291</td>\n",
              "      <td>0.7265</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>27.072500</td>\n",
              "      <td>27.162500</td>\n",
              "      <td>26.352501</td>\n",
              "      <td>26.562500</td>\n",
              "      <td>24.120045</td>\n",
              "      <td>257142000</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.237</td>\n",
              "      <td>0.3401</td>\n",
              "      <td>40.7792</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.0014</td>\n",
              "      <td>23.3908</td>\n",
              "      <td>0.2221</td>\n",
              "      <td>14.3381</td>\n",
              "      <td>3.1937</td>\n",
              "      <td>28.1807</td>\n",
              "      <td>10.5181</td>\n",
              "      <td>11.2855</td>\n",
              "      <td>5.1950</td>\n",
              "      <td>8.0253</td>\n",
              "      <td>5.5970</td>\n",
              "      <td>0.8291</td>\n",
              "      <td>0.7265</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2015-01-06</th>\n",
              "      <td>26.635000</td>\n",
              "      <td>26.857500</td>\n",
              "      <td>26.157499</td>\n",
              "      <td>26.565001</td>\n",
              "      <td>24.122320</td>\n",
              "      <td>263188400</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.237</td>\n",
              "      <td>0.3401</td>\n",
              "      <td>40.7792</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.0014</td>\n",
              "      <td>23.3908</td>\n",
              "      <td>0.2221</td>\n",
              "      <td>14.3381</td>\n",
              "      <td>3.1937</td>\n",
              "      <td>28.1807</td>\n",
              "      <td>10.5181</td>\n",
              "      <td>11.2855</td>\n",
              "      <td>5.1950</td>\n",
              "      <td>8.0253</td>\n",
              "      <td>5.5970</td>\n",
              "      <td>0.8291</td>\n",
              "      <td>0.7265</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2015-01-07</th>\n",
              "      <td>26.799999</td>\n",
              "      <td>27.049999</td>\n",
              "      <td>26.674999</td>\n",
              "      <td>26.937500</td>\n",
              "      <td>24.460564</td>\n",
              "      <td>160423600</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.237</td>\n",
              "      <td>0.3401</td>\n",
              "      <td>40.7792</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.0014</td>\n",
              "      <td>23.3908</td>\n",
              "      <td>0.2221</td>\n",
              "      <td>14.3381</td>\n",
              "      <td>3.1937</td>\n",
              "      <td>28.1807</td>\n",
              "      <td>10.5181</td>\n",
              "      <td>11.2855</td>\n",
              "      <td>5.1950</td>\n",
              "      <td>8.0253</td>\n",
              "      <td>5.5970</td>\n",
              "      <td>0.8291</td>\n",
              "      <td>0.7265</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-08</th>\n",
              "      <td>27.307501</td>\n",
              "      <td>28.037500</td>\n",
              "      <td>27.174999</td>\n",
              "      <td>27.972500</td>\n",
              "      <td>25.400398</td>\n",
              "      <td>237458000</td>\n",
              "      <td>1.1560</td>\n",
              "      <td>0.237</td>\n",
              "      <td>0.3401</td>\n",
              "      <td>40.7792</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>31.5084</td>\n",
              "      <td>0.0</td>\n",
              "      <td>32.0014</td>\n",
              "      <td>23.3908</td>\n",
              "      <td>0.2221</td>\n",
              "      <td>14.3381</td>\n",
              "      <td>3.1937</td>\n",
              "      <td>28.1807</td>\n",
              "      <td>10.5181</td>\n",
              "      <td>11.2855</td>\n",
              "      <td>5.1950</td>\n",
              "      <td>8.0253</td>\n",
              "      <td>5.5970</td>\n",
              "      <td>0.8291</td>\n",
              "      <td>0.7265</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>27.074000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>27.074000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-25</th>\n",
              "      <td>119.540001</td>\n",
              "      <td>121.660004</td>\n",
              "      <td>119.000000</td>\n",
              "      <td>120.589996</td>\n",
              "      <td>120.385513</td>\n",
              "      <td>98844700</td>\n",
              "      <td>1.1417</td>\n",
              "      <td>0.611</td>\n",
              "      <td>1.7584</td>\n",
              "      <td>42.5065</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.2679</td>\n",
              "      <td>26.3775</td>\n",
              "      <td>0.2657</td>\n",
              "      <td>9.8687</td>\n",
              "      <td>2.7117</td>\n",
              "      <td>33.1894</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>7.0086</td>\n",
              "      <td>13.2887</td>\n",
              "      <td>4.1458</td>\n",
              "      <td>1.4413</td>\n",
              "      <td>1.3050</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>121.319998</td>\n",
              "      <td>122.247999</td>\n",
              "      <td>121.982499</td>\n",
              "      <td>128.7484</td>\n",
              "      <td>121.275008</td>\n",
              "      <td>121.754923</td>\n",
              "      <td>122.991014</td>\n",
              "      <td>125.567708</td>\n",
              "      <td>3.539975</td>\n",
              "      <td>28.160311</td>\n",
              "      <td>-54.510961</td>\n",
              "      <td>-1.123322</td>\n",
              "      <td>43.713712</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-26</th>\n",
              "      <td>120.349998</td>\n",
              "      <td>121.480003</td>\n",
              "      <td>118.919998</td>\n",
              "      <td>121.209999</td>\n",
              "      <td>121.004463</td>\n",
              "      <td>94071200</td>\n",
              "      <td>1.1417</td>\n",
              "      <td>0.611</td>\n",
              "      <td>1.7584</td>\n",
              "      <td>42.5065</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.2679</td>\n",
              "      <td>26.3775</td>\n",
              "      <td>0.2657</td>\n",
              "      <td>9.8687</td>\n",
              "      <td>2.7117</td>\n",
              "      <td>33.1894</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>7.0086</td>\n",
              "      <td>13.2887</td>\n",
              "      <td>4.1458</td>\n",
              "      <td>1.4413</td>\n",
              "      <td>1.3050</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>121.563998</td>\n",
              "      <td>122.265999</td>\n",
              "      <td>121.979999</td>\n",
              "      <td>128.5548</td>\n",
              "      <td>121.253338</td>\n",
              "      <td>121.655846</td>\n",
              "      <td>122.821394</td>\n",
              "      <td>125.396817</td>\n",
              "      <td>3.469977</td>\n",
              "      <td>27.926685</td>\n",
              "      <td>-64.627979</td>\n",
              "      <td>0.148723</td>\n",
              "      <td>44.995052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-29</th>\n",
              "      <td>121.650002</td>\n",
              "      <td>122.580002</td>\n",
              "      <td>120.730003</td>\n",
              "      <td>121.389999</td>\n",
              "      <td>121.184158</td>\n",
              "      <td>80819200</td>\n",
              "      <td>1.1417</td>\n",
              "      <td>0.611</td>\n",
              "      <td>1.7584</td>\n",
              "      <td>42.5065</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.2679</td>\n",
              "      <td>26.3775</td>\n",
              "      <td>0.2657</td>\n",
              "      <td>9.8687</td>\n",
              "      <td>2.7117</td>\n",
              "      <td>33.1894</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>7.0086</td>\n",
              "      <td>13.2887</td>\n",
              "      <td>4.1458</td>\n",
              "      <td>1.4413</td>\n",
              "      <td>1.3050</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>121.163998</td>\n",
              "      <td>122.005999</td>\n",
              "      <td>121.659999</td>\n",
              "      <td>128.4044</td>\n",
              "      <td>121.298892</td>\n",
              "      <td>121.607510</td>\n",
              "      <td>122.685070</td>\n",
              "      <td>125.239687</td>\n",
              "      <td>3.354264</td>\n",
              "      <td>27.265441</td>\n",
              "      <td>-17.921375</td>\n",
              "      <td>-2.096943</td>\n",
              "      <td>45.383781</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-30</th>\n",
              "      <td>120.110001</td>\n",
              "      <td>120.400002</td>\n",
              "      <td>118.860001</td>\n",
              "      <td>119.900002</td>\n",
              "      <td>119.696686</td>\n",
              "      <td>85671900</td>\n",
              "      <td>1.1417</td>\n",
              "      <td>0.611</td>\n",
              "      <td>1.7584</td>\n",
              "      <td>42.5065</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.2679</td>\n",
              "      <td>26.3775</td>\n",
              "      <td>0.2657</td>\n",
              "      <td>9.8687</td>\n",
              "      <td>2.7117</td>\n",
              "      <td>33.1894</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>7.0086</td>\n",
              "      <td>13.2887</td>\n",
              "      <td>4.1458</td>\n",
              "      <td>1.4413</td>\n",
              "      <td>1.3050</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>120.635998</td>\n",
              "      <td>121.438999</td>\n",
              "      <td>121.398999</td>\n",
              "      <td>128.2596</td>\n",
              "      <td>120.832595</td>\n",
              "      <td>121.297054</td>\n",
              "      <td>122.419826</td>\n",
              "      <td>125.030288</td>\n",
              "      <td>3.295388</td>\n",
              "      <td>27.136881</td>\n",
              "      <td>-105.699850</td>\n",
              "      <td>-4.515408</td>\n",
              "      <td>42.694043</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-31</th>\n",
              "      <td>121.650002</td>\n",
              "      <td>123.519997</td>\n",
              "      <td>121.150002</td>\n",
              "      <td>122.150002</td>\n",
              "      <td>121.942871</td>\n",
              "      <td>118323800</td>\n",
              "      <td>1.1417</td>\n",
              "      <td>0.611</td>\n",
              "      <td>1.7584</td>\n",
              "      <td>42.5065</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>30.7008</td>\n",
              "      <td>0.0</td>\n",
              "      <td>31.2679</td>\n",
              "      <td>26.3775</td>\n",
              "      <td>0.2657</td>\n",
              "      <td>9.8687</td>\n",
              "      <td>2.7117</td>\n",
              "      <td>33.1894</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>34.1583</td>\n",
              "      <td>7.0086</td>\n",
              "      <td>13.2887</td>\n",
              "      <td>4.1458</td>\n",
              "      <td>1.4413</td>\n",
              "      <td>1.3050</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>121.048000</td>\n",
              "      <td>121.177999</td>\n",
              "      <td>121.403499</td>\n",
              "      <td>128.1460</td>\n",
              "      <td>121.271731</td>\n",
              "      <td>121.452135</td>\n",
              "      <td>122.394128</td>\n",
              "      <td>124.917335</td>\n",
              "      <td>3.318574</td>\n",
              "      <td>25.847576</td>\n",
              "      <td>19.939937</td>\n",
              "      <td>-2.092017</td>\n",
              "      <td>47.731710</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1572 rows × 42 columns</p>\n",
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            ],
            "text/plain": [
              "                  open        high         low  ...      CCI_14    ROC_10     RSI_14\n",
              "date                                            ...                                 \n",
              "2015-01-02   27.847500   27.860001   26.837500  ...         NaN       NaN        NaN\n",
              "2015-01-05   27.072500   27.162500   26.352501  ...         NaN       NaN        NaN\n",
              "2015-01-06   26.635000   26.857500   26.157499  ...         NaN       NaN        NaN\n",
              "2015-01-07   26.799999   27.049999   26.674999  ...         NaN       NaN        NaN\n",
              "2015-01-08   27.307501   28.037500   27.174999  ...         NaN       NaN        NaN\n",
              "...                ...         ...         ...  ...         ...       ...        ...\n",
              "2021-03-25  119.540001  121.660004  119.000000  ...  -54.510961 -1.123322  43.713712\n",
              "2021-03-26  120.349998  121.480003  118.919998  ...  -64.627979  0.148723  44.995052\n",
              "2021-03-29  121.650002  122.580002  120.730003  ...  -17.921375 -2.096943  45.383781\n",
              "2021-03-30  120.110001  120.400002  118.860001  ... -105.699850 -4.515408  42.694043\n",
              "2021-03-31  121.650002  123.519997  121.150002  ...   19.939937 -2.092017  47.731710\n",
              "\n",
              "[1572 rows x 42 columns]"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = pd.read_csv('apple.csv', header=0, parse_dates=[0], index_col=0, squeeze=True)\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QStoAOFS6Y1w"
      },
      "source": [
        "# **Drop old features**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lc4EWOqMN8K_",
        "outputId": "369b2f46-4214-4ed2-f264-8eb9000bfaf5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Index(['open', 'high', 'low', 'close', 'adj_close', 'volume', 'current_ratio',\n",
              "       'long-term_debt_to_capital', 'debt_to_equity_ratio', 'gross_margin',\n",
              "       'operating_margin', 'ebit_margin', 'ebitda_margin',\n",
              "       'pre-tax_profit_margin', 'net_profit_margin', 'asset_turnover',\n",
              "       'inventory_turnover_ratio', 'receiveable_turnover',\n",
              "       'days_sales_in_receivables', 'roe_-_return_on_equity',\n",
              "       'return_on_tangible_equity', 'roa_-_return_on_assets',\n",
              "       'roi_-_return_on_investment', 'book_value_per_share',\n",
              "       'operating_cash_flow_per_share', 'free_cash_flow_per_share',\n",
              "       'is_day_start_market', 'is_day_end_market', 'day_of_week', 'SMA_5',\n",
              "       'SMA_10', 'SMA_20', 'SMA_50', 'EMA_5', 'EMA_10', 'EMA_20', 'EMA_50',\n",
              "       'ATR_14', 'ADX_14', 'CCI_14', 'ROC_10', 'RSI_14'],\n",
              "      dtype='object')"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "sUPi17tqnz1X"
      },
      "outputs": [],
      "source": [
        "# We keep only the OHLCV data \n",
        "df = df[['open', 'high', 'low', 'close', 'adj_close', 'volume']]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ktQX6Ted6cJK"
      },
      "source": [
        "# **Computing technical indicators**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W0Uvq36nF0cY"
      },
      "source": [
        "We are creating features as technical indicators that are set for different time-ranges from 5 to 50 days, with 5 days of difference. They are the following:\n",
        "\n",
        "- SMA: Simple Moving Average.\n",
        "- EMA: Exponential Moving Average.\n",
        "- ATR: Average True Range.\n",
        "- ADX: Average Directional Index.\n",
        "- CCI: Commodity Channel Index.\n",
        "- ROC: Rate of Change.\n",
        "- RSI: Relative Strength Index.\n",
        "- Force Index.\n",
        "- MFI: Money Flow Index.\n",
        "- OBV: On Balance Volume.\n",
        "- UI: ULCER Index."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f-zSwX2ueNti",
        "outputId": "0bb9c83e-077c-44d4-c5f2-36f730f63cf8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "sma_indicator5\n",
            "ema_indicator5\n",
            "average_true_range5\n",
            "adx5\n",
            "cci5\n",
            "roc5\n",
            "rsi5\n",
            "force_index5\n",
            "money_flow_index5\n",
            "on_balance_volume5\n",
            "ulcer_index5\n",
            "sma_indicator10\n",
            "ema_indicator10\n",
            "average_true_range10\n",
            "adx10\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:17: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:22: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:27: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:32: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:37: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:42: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:47: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:52: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:57: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:17: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:22: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:27: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:32: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:37: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:42: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:47: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:52: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:57: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:17: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:22: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "cci10\n",
            "roc10\n",
            "rsi10\n",
            "force_index10\n",
            "money_flow_index10\n",
            "on_balance_volume10\n",
            "ulcer_index10\n",
            "sma_indicator15\n",
            "ema_indicator15\n",
            "average_true_range15\n",
            "adx15\n",
            "cci15\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:27: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:32: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:37: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:42: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:47: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:52: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:57: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "roc15\n",
            "rsi15\n",
            "force_index15\n",
            "money_flow_index15\n",
            "on_balance_volume15\n",
            "ulcer_index15\n",
            "sma_indicator20\n",
            "ema_indicator20\n",
            "average_true_range20\n",
            "adx20\n",
            "cci20\n",
            "roc20\n",
            "rsi20\n",
            "force_index20\n",
            "money_flow_index20\n",
            "on_balance_volume20\n",
            "ulcer_index20\n",
            "sma_indicator25\n",
            "ema_indicator25\n",
            "average_true_range25\n",
            "adx25\n",
            "cci25\n",
            "roc25\n",
            "rsi25\n",
            "force_index25\n",
            "money_flow_index25\n",
            "on_balance_volume25\n",
            "ulcer_index25\n",
            "sma_indicator30\n",
            "ema_indicator30\n",
            "average_true_range30\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "adx30\n",
            "cci30\n",
            "roc30\n",
            "rsi30\n",
            "force_index30\n",
            "money_flow_index30\n",
            "on_balance_volume30\n",
            "ulcer_index30\n",
            "sma_indicator35\n",
            "ema_indicator35\n",
            "average_true_range35\n",
            "adx35\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "cci35\n",
            "roc35\n",
            "rsi35\n",
            "force_index35\n",
            "money_flow_index35\n",
            "on_balance_volume35\n",
            "ulcer_index35\n",
            "sma_indicator40\n",
            "ema_indicator40\n",
            "average_true_range40\n",
            "adx40\n",
            "cci40\n",
            "roc40\n",
            "rsi40\n",
            "force_index40\n",
            "money_flow_index40\n",
            "on_balance_volume40\n",
            "ulcer_index40\n",
            "sma_indicator45\n",
            "ema_indicator45\n",
            "average_true_range45\n",
            "adx45\n",
            "cci45\n",
            "roc45\n",
            "rsi45\n",
            "force_index45\n",
            "money_flow_index45\n",
            "on_balance_volume45\n",
            "ulcer_index45\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:769: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  dip[idx] = 100 * (self._dip[idx] / value)\n",
            "/usr/local/lib/python3.7/dist-packages/ta/trend.py:774: RuntimeWarning: invalid value encountered in double_scalars\n",
            "  din[idx] = 100 * (self._din[idx] / value)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "sma_indicator50\n",
            "ema_indicator50\n",
            "average_true_range50\n",
            "adx50\n",
            "cci50\n",
            "roc50\n",
            "rsi50\n",
            "force_index50\n",
            "money_flow_index50\n",
            "on_balance_volume50\n",
            "ulcer_index50\n"
          ]
        }
      ],
      "source": [
        "f_names = []\n",
        "for i in range(5, 51, 5):\n",
        "    # SMA\n",
        "    n = trend.sma_indicator.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = trend.sma_indicator(df.close, i, fillna=False)\n",
        "    # EMA\n",
        "    n = trend.ema_indicator.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = trend.ema_indicator(df.close, i, fillna=False)\n",
        "    # ATR\n",
        "    n = volatility.average_true_range.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = volatility.average_true_range(df.high, df.low, df.close, i, fillna=False)\n",
        "    # ADX\n",
        "    n = trend.adx.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = trend.adx(df.high, df.low, df.close, i, fillna=False)\n",
        "    # CCI\n",
        "    n = trend.cci.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = trend.cci(df.high, df.low, df.close, i, fillna=False)\n",
        "    # ROC\n",
        "    n = momentum.roc.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = momentum.roc(df.close, i, fillna=False)\n",
        "    # RSI\n",
        "    n = momentum.rsi.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = momentum.rsi(df.close, i, fillna=False)\n",
        "    # Force index\n",
        "    n = volume.force_index.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = volume.force_index(df.close, df.volume, i, fillna=False)\n",
        "    # MFI\n",
        "    n = volume.money_flow_index.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = volume.money_flow_index(df.high, df.low, df.close, df.volume, i, fillna=False)\n",
        "    # OBV\n",
        "    n = volume.on_balance_volume.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] = volume.on_balance_volume(df.close, df.volume, i)\n",
        "    # UI\n",
        "    n =  volatility.ulcer_index.__name__ + str(i)\n",
        "    print(n)\n",
        "    f_names.append(n)\n",
        "    df[n] =  volatility.ulcer_index(df.close, i, fillna=False)\n",
        "\n",
        "# Add features to the dataset\n",
        "f_names.extend([volume.acc_dist_index.__name__, others.cumulative_return.__name__, others.daily_log_return.__name__, others.daily_return.__name__])\n",
        "\n",
        "df[volume.acc_dist_index.__name__] = volume.acc_dist_index(df.high, df.low, df.close, df.volume, fillna=False)\n",
        "\n",
        "df[others.cumulative_return.__name__] =  others.cumulative_return(df.close, fillna=False)\n",
        "  \n",
        "df[others.daily_log_return.__name__] =  others.daily_log_return(df.close, fillna=False)\n",
        "  \n",
        "df[others.daily_return.__name__] =  others.daily_return(df.close, fillna=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sE6El041-8MR",
        "outputId": "d9aaf31a-db16-4206-a174-d5f621abf644"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Index(['open', 'high', 'low', 'close', 'adj_close', 'volume', 'sma_indicator5',\n",
              "       'ema_indicator5', 'average_true_range5', 'adx5',\n",
              "       ...\n",
              "       'roc50', 'rsi50', 'force_index50', 'money_flow_index50',\n",
              "       'on_balance_volume50', 'ulcer_index50', 'acc_dist_index',\n",
              "       'cumulative_return', 'daily_log_return', 'daily_return'],\n",
              "      dtype='object', length=120)"
            ]
          },
          "execution_count": 175,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Check the new dataset's columns\n",
        "df.columns"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WMvYKas2JuLW"
      },
      "source": [
        "# **Data preparation**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DSsScW_V6_L4"
      },
      "source": [
        "## **Data shifting**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "72RQbOl8JKxP"
      },
      "source": [
        "**A necessary step when dealing with Time series is to make the dataset suitable to supervised learning models, or simply \"data shifting\".**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y3t9z4s5eMuo",
        "outputId": "49a45b72-1643-4e7b-f0b9-dfaef237cc03"
      },
      "outputs": [
        {
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              "      <th>acc_dist_index</th>\n",
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              "      <th>daily_return</th>\n",
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              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
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              "      <th>2015-01-06</th>\n",
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              "      <th>2015-01-08</th>\n",
              "      <td>27.307501</td>\n",
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              "      <td>27.074000</td>\n",
              "      <td>27.268303</td>\n",
              "      <td>0.857500</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>115.405916</td>\n",
              "      <td>NaN</td>\n",
              "      <td>77.196268</td>\n",
              "      <td>NaN</td>\n",
              "      <td>44.043623</td>\n",
              "      <td>616746400</td>\n",
              "      <td>1.892607</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>616746400</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.785025e+08</td>\n",
              "      <td>2.341535</td>\n",
              "      <td>3.770252</td>\n",
              "      <td>3.842227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-25</th>\n",
              "      <td>119.540001</td>\n",
              "      <td>121.660004</td>\n",
              "      <td>119.000000</td>\n",
              "      <td>121.209999</td>\n",
              "      <td>120.385513</td>\n",
              "      <td>98844700</td>\n",
              "      <td>121.319998</td>\n",
              "      <td>121.275008</td>\n",
              "      <td>3.050337</td>\n",
              "      <td>21.091700</td>\n",
              "      <td>-67.532434</td>\n",
              "      <td>0.049778</td>\n",
              "      <td>42.454670</td>\n",
              "      <td>-3.080332e+07</td>\n",
              "      <td>36.150238</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>2.765111</td>\n",
              "      <td>122.247999</td>\n",
              "      <td>121.754923</td>\n",
              "      <td>3.413519</td>\n",
              "      <td>27.882780</td>\n",
              "      <td>-80.293488</td>\n",
              "      <td>-1.123322</td>\n",
              "      <td>43.735864</td>\n",
              "      <td>-2.959334e+07</td>\n",
              "      <td>37.861638</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>3.296697</td>\n",
              "      <td>121.552666</td>\n",
              "      <td>122.303136</td>\n",
              "      <td>3.559847</td>\n",
              "      <td>27.494146</td>\n",
              "      <td>-51.560524</td>\n",
              "      <td>0.382918</td>\n",
              "      <td>43.762508</td>\n",
              "      <td>-3.214809e+07</td>\n",
              "      <td>37.173504</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>6.191894</td>\n",
              "      <td>121.982499</td>\n",
              "      <td>...</td>\n",
              "      <td>34.433018</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.944658</td>\n",
              "      <td>127.163500</td>\n",
              "      <td>125.146465</td>\n",
              "      <td>3.668391</td>\n",
              "      <td>13.441953</td>\n",
              "      <td>-80.042404</td>\n",
              "      <td>-15.113334</td>\n",
              "      <td>47.179008</td>\n",
              "      <td>-3.557365e+07</td>\n",
              "      <td>34.002513</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.897897</td>\n",
              "      <td>128.680444</td>\n",
              "      <td>125.406049</td>\n",
              "      <td>3.665046</td>\n",
              "      <td>12.573743</td>\n",
              "      <td>-83.610511</td>\n",
              "      <td>-8.664700</td>\n",
              "      <td>47.783740</td>\n",
              "      <td>-3.397053e+07</td>\n",
              "      <td>39.940568</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.335815</td>\n",
              "      <td>128.7484</td>\n",
              "      <td>125.567708</td>\n",
              "      <td>3.658196</td>\n",
              "      <td>12.028678</td>\n",
              "      <td>-91.683548</td>\n",
              "      <td>-6.374229</td>\n",
              "      <td>48.325260</td>\n",
              "      <td>-3.215676e+07</td>\n",
              "      <td>39.959075</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>10.895303</td>\n",
              "      <td>8.214703e+09</td>\n",
              "      <td>341.196363</td>\n",
              "      <td>0.415490</td>\n",
              "      <td>0.416354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-26</th>\n",
              "      <td>120.349998</td>\n",
              "      <td>121.480003</td>\n",
              "      <td>118.919998</td>\n",
              "      <td>121.389999</td>\n",
              "      <td>121.004463</td>\n",
              "      <td>94071200</td>\n",
              "      <td>121.563998</td>\n",
              "      <td>121.253338</td>\n",
              "      <td>2.952271</td>\n",
              "      <td>22.336771</td>\n",
              "      <td>-63.633921</td>\n",
              "      <td>1.016752</td>\n",
              "      <td>47.051731</td>\n",
              "      <td>-1.094070e+06</td>\n",
              "      <td>61.928560</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>2.078645</td>\n",
              "      <td>122.265999</td>\n",
              "      <td>121.655846</td>\n",
              "      <td>3.328168</td>\n",
              "      <td>27.481583</td>\n",
              "      <td>-75.702115</td>\n",
              "      <td>0.148723</td>\n",
              "      <td>45.605967</td>\n",
              "      <td>-1.360830e+07</td>\n",
              "      <td>45.984209</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>3.045566</td>\n",
              "      <td>121.538666</td>\n",
              "      <td>122.166494</td>\n",
              "      <td>3.493191</td>\n",
              "      <td>27.322841</td>\n",
              "      <td>-47.249446</td>\n",
              "      <td>-0.172953</td>\n",
              "      <td>44.950328</td>\n",
              "      <td>-2.083903e+07</td>\n",
              "      <td>43.946270</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>5.662475</td>\n",
              "      <td>121.979999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.412630</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>12.081717</td>\n",
              "      <td>126.766500</td>\n",
              "      <td>124.954442</td>\n",
              "      <td>3.640681</td>\n",
              "      <td>13.514197</td>\n",
              "      <td>-76.206742</td>\n",
              "      <td>-11.583629</td>\n",
              "      <td>47.582940</td>\n",
              "      <td>-3.099325e+07</td>\n",
              "      <td>36.582681</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>12.024050</td>\n",
              "      <td>128.332444</td>\n",
              "      <td>125.223612</td>\n",
              "      <td>3.640490</td>\n",
              "      <td>12.618661</td>\n",
              "      <td>-79.209514</td>\n",
              "      <td>-11.441511</td>\n",
              "      <td>48.138369</td>\n",
              "      <td>-2.995771e+07</td>\n",
              "      <td>39.465059</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>11.563945</td>\n",
              "      <td>128.5548</td>\n",
              "      <td>125.396817</td>\n",
              "      <td>3.636233</td>\n",
              "      <td>12.048508</td>\n",
              "      <td>-86.533716</td>\n",
              "      <td>-7.395523</td>\n",
              "      <td>48.641115</td>\n",
              "      <td>-2.860848e+07</td>\n",
              "      <td>39.941466</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>11.092756</td>\n",
              "      <td>8.288931e+09</td>\n",
              "      <td>343.464736</td>\n",
              "      <td>0.512824</td>\n",
              "      <td>0.514141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-29</th>\n",
              "      <td>121.650002</td>\n",
              "      <td>122.580002</td>\n",
              "      <td>120.730003</td>\n",
              "      <td>119.900002</td>\n",
              "      <td>121.184158</td>\n",
              "      <td>80819200</td>\n",
              "      <td>121.163998</td>\n",
              "      <td>121.298892</td>\n",
              "      <td>2.731816</td>\n",
              "      <td>18.832909</td>\n",
              "      <td>22.743043</td>\n",
              "      <td>-1.620877</td>\n",
              "      <td>48.543492</td>\n",
              "      <td>4.119772e+06</td>\n",
              "      <td>59.264480</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>1.973351</td>\n",
              "      <td>122.005999</td>\n",
              "      <td>121.607510</td>\n",
              "      <td>3.180351</td>\n",
              "      <td>26.207793</td>\n",
              "      <td>-23.894474</td>\n",
              "      <td>-2.096943</td>\n",
              "      <td>46.182985</td>\n",
              "      <td>-8.489068e+06</td>\n",
              "      <td>45.373600</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>3.209675</td>\n",
              "      <td>121.873999</td>\n",
              "      <td>122.069432</td>\n",
              "      <td>3.383645</td>\n",
              "      <td>26.779343</td>\n",
              "      <td>-13.777852</td>\n",
              "      <td>4.322790</td>\n",
              "      <td>45.309645</td>\n",
              "      <td>-1.641572e+07</td>\n",
              "      <td>50.753777</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>4.707191</td>\n",
              "      <td>121.659999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.341062</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>12.209356</td>\n",
              "      <td>126.502249</td>\n",
              "      <td>124.780567</td>\n",
              "      <td>3.595914</td>\n",
              "      <td>13.537878</td>\n",
              "      <td>-61.271789</td>\n",
              "      <td>-8.010009</td>\n",
              "      <td>47.702026</td>\n",
              "      <td>-2.877176e+07</td>\n",
              "      <td>39.352361</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>12.101164</td>\n",
              "      <td>127.939555</td>\n",
              "      <td>125.056933</td>\n",
              "      <td>3.600701</td>\n",
              "      <td>12.626289</td>\n",
              "      <td>-66.271030</td>\n",
              "      <td>-12.713027</td>\n",
              "      <td>48.242739</td>\n",
              "      <td>-2.802270e+07</td>\n",
              "      <td>38.897470</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>11.784041</td>\n",
              "      <td>128.4044</td>\n",
              "      <td>125.239687</td>\n",
              "      <td>3.600508</td>\n",
              "      <td>12.038982</td>\n",
              "      <td>-72.536373</td>\n",
              "      <td>-5.833531</td>\n",
              "      <td>48.733946</td>\n",
              "      <td>-2.691609e+07</td>\n",
              "      <td>41.433666</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>11.270592</td>\n",
              "      <td>8.265777e+09</td>\n",
              "      <td>344.123293</td>\n",
              "      <td>0.148392</td>\n",
              "      <td>0.148503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-30</th>\n",
              "      <td>120.110001</td>\n",
              "      <td>120.400002</td>\n",
              "      <td>118.860001</td>\n",
              "      <td>122.150002</td>\n",
              "      <td>119.696686</td>\n",
              "      <td>85671900</td>\n",
              "      <td>120.635998</td>\n",
              "      <td>120.832595</td>\n",
              "      <td>2.691453</td>\n",
              "      <td>21.226957</td>\n",
              "      <td>-121.101740</td>\n",
              "      <td>-2.154398</td>\n",
              "      <td>37.586286</td>\n",
              "      <td>-3.980378e+07</td>\n",
              "      <td>39.165591</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>1.887372</td>\n",
              "      <td>121.438999</td>\n",
              "      <td>121.297054</td>\n",
              "      <td>3.115316</td>\n",
              "      <td>26.102997</td>\n",
              "      <td>-107.291047</td>\n",
              "      <td>-4.515408</td>\n",
              "      <td>42.077550</td>\n",
              "      <td>-3.015485e+07</td>\n",
              "      <td>35.733984</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>3.437948</td>\n",
              "      <td>121.794666</td>\n",
              "      <td>121.798253</td>\n",
              "      <td>3.326735</td>\n",
              "      <td>26.689178</td>\n",
              "      <td>-102.802413</td>\n",
              "      <td>-0.982735</td>\n",
              "      <td>42.830229</td>\n",
              "      <td>-3.032011e+07</td>\n",
              "      <td>44.068617</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>4.451394</td>\n",
              "      <td>121.398999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.302157</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.350397</td>\n",
              "      <td>126.146250</td>\n",
              "      <td>124.542491</td>\n",
              "      <td>3.569266</td>\n",
              "      <td>13.619278</td>\n",
              "      <td>-81.403218</td>\n",
              "      <td>-10.615772</td>\n",
              "      <td>46.799342</td>\n",
              "      <td>-3.359513e+07</td>\n",
              "      <td>36.980684</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.226903</td>\n",
              "      <td>127.428000</td>\n",
              "      <td>124.832719</td>\n",
              "      <td>3.576908</td>\n",
              "      <td>12.680515</td>\n",
              "      <td>-83.111576</td>\n",
              "      <td>-16.106910</td>\n",
              "      <td>47.434576</td>\n",
              "      <td>-3.235436e+07</td>\n",
              "      <td>36.076173</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.030375</td>\n",
              "      <td>128.2596</td>\n",
              "      <td>125.030288</td>\n",
              "      <td>3.579098</td>\n",
              "      <td>12.068096</td>\n",
              "      <td>-88.246503</td>\n",
              "      <td>-5.694508</td>\n",
              "      <td>48.001097</td>\n",
              "      <td>-3.086647e+07</td>\n",
              "      <td>41.671428</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>11.459915</td>\n",
              "      <td>8.295818e+09</td>\n",
              "      <td>338.671918</td>\n",
              "      <td>-1.235042</td>\n",
              "      <td>-1.227446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-31</th>\n",
              "      <td>121.650002</td>\n",
              "      <td>123.519997</td>\n",
              "      <td>121.150002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>121.942871</td>\n",
              "      <td>118323800</td>\n",
              "      <td>121.048000</td>\n",
              "      <td>121.271731</td>\n",
              "      <td>2.877161</td>\n",
              "      <td>20.312113</td>\n",
              "      <td>112.276057</td>\n",
              "      <td>1.715385</td>\n",
              "      <td>56.233615</td>\n",
              "      <td>6.220700e+07</td>\n",
              "      <td>61.656322</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>1.460013</td>\n",
              "      <td>121.177999</td>\n",
              "      <td>121.452135</td>\n",
              "      <td>3.165783</td>\n",
              "      <td>23.697411</td>\n",
              "      <td>77.566827</td>\n",
              "      <td>-2.092017</td>\n",
              "      <td>49.595526</td>\n",
              "      <td>2.373304e+07</td>\n",
              "      <td>46.627524</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>3.446574</td>\n",
              "      <td>121.939333</td>\n",
              "      <td>121.842222</td>\n",
              "      <td>3.346286</td>\n",
              "      <td>25.588653</td>\n",
              "      <td>20.084215</td>\n",
              "      <td>1.808634</td>\n",
              "      <td>47.480121</td>\n",
              "      <td>6.748471e+06</td>\n",
              "      <td>51.306346</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>4.055027</td>\n",
              "      <td>121.403499</td>\n",
              "      <td>...</td>\n",
              "      <td>34.845029</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>12.431893</td>\n",
              "      <td>125.825249</td>\n",
              "      <td>124.425784</td>\n",
              "      <td>3.570534</td>\n",
              "      <td>13.568474</td>\n",
              "      <td>-46.980882</td>\n",
              "      <td>-9.511818</td>\n",
              "      <td>48.314168</td>\n",
              "      <td>-1.896958e+07</td>\n",
              "      <td>37.356476</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>12.319052</td>\n",
              "      <td>126.961111</td>\n",
              "      <td>124.716079</td>\n",
              "      <td>3.577865</td>\n",
              "      <td>12.632216</td>\n",
              "      <td>-53.806072</td>\n",
              "      <td>-14.675888</td>\n",
              "      <td>48.760233</td>\n",
              "      <td>-1.937250e+07</td>\n",
              "      <td>36.117457</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>12.210444</td>\n",
              "      <td>128.1460</td>\n",
              "      <td>124.917335</td>\n",
              "      <td>3.579916</td>\n",
              "      <td>12.015613</td>\n",
              "      <td>-59.761707</td>\n",
              "      <td>-4.443401</td>\n",
              "      <td>49.178702</td>\n",
              "      <td>-1.921569e+07</td>\n",
              "      <td>43.548477</td>\n",
              "      <td>4000824000</td>\n",
              "      <td>11.610211</td>\n",
              "      <td>8.277346e+09</td>\n",
              "      <td>346.903876</td>\n",
              "      <td>1.859174</td>\n",
              "      <td>1.876564</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1572 rows × 120 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  open        high  ...  daily_log_return  daily_return\n",
              "date                                ...                                \n",
              "2015-01-02   27.847500   27.860001  ...               NaN    -46.648777\n",
              "2015-01-05   27.072500   27.162500  ...         -2.857602     -2.817159\n",
              "2015-01-06   26.635000   26.857500  ...          0.009415      0.009416\n",
              "2015-01-07   26.799999   27.049999  ...          1.392477      1.402217\n",
              "2015-01-08   27.307501   28.037500  ...          3.770252      3.842227\n",
              "...                ...         ...  ...               ...           ...\n",
              "2021-03-25  119.540001  121.660004  ...          0.415490      0.416354\n",
              "2021-03-26  120.349998  121.480003  ...          0.512824      0.514141\n",
              "2021-03-29  121.650002  122.580002  ...          0.148392      0.148503\n",
              "2021-03-30  120.110001  120.400002  ...         -1.235042     -1.227446\n",
              "2021-03-31  121.650002  123.519997  ...          1.859174      1.876564\n",
              "\n",
              "[1572 rows x 120 columns]"
            ]
          },
          "execution_count": 176,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Shift the close price upwards\n",
        "df['close'] = df['close'].shift(-1)\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "33o_Agbl7FxT"
      },
      "source": [
        "## **Dropping rows with Nan values**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VR5hgMkPJ-dq"
      },
      "source": [
        "**While the Nan values are available only on the first 50 days, which caused by the computation of technical indicators for the 50 day range, the close price isn't affected by these days, especially with the lack of fluctuations and volatility during the first 50 days in the dataset. Therefore, dropping these values won't cause any harm.**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ozLYy9pleRgv",
        "outputId": "7462bf8f-983b-46c5-aadc-2062c5a38775"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>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>sma_indicator5</th>\n",
              "      <th>ema_indicator5</th>\n",
              "      <th>average_true_range5</th>\n",
              "      <th>adx5</th>\n",
              "      <th>cci5</th>\n",
              "      <th>roc5</th>\n",
              "      <th>rsi5</th>\n",
              "      <th>force_index5</th>\n",
              "      <th>money_flow_index5</th>\n",
              "      <th>on_balance_volume5</th>\n",
              "      <th>ulcer_index5</th>\n",
              "      <th>sma_indicator10</th>\n",
              "      <th>ema_indicator10</th>\n",
              "      <th>average_true_range10</th>\n",
              "      <th>adx10</th>\n",
              "      <th>cci10</th>\n",
              "      <th>roc10</th>\n",
              "      <th>rsi10</th>\n",
              "      <th>force_index10</th>\n",
              "      <th>money_flow_index10</th>\n",
              "      <th>on_balance_volume10</th>\n",
              "      <th>ulcer_index10</th>\n",
              "      <th>sma_indicator15</th>\n",
              "      <th>ema_indicator15</th>\n",
              "      <th>average_true_range15</th>\n",
              "      <th>adx15</th>\n",
              "      <th>cci15</th>\n",
              "      <th>roc15</th>\n",
              "      <th>rsi15</th>\n",
              "      <th>force_index15</th>\n",
              "      <th>money_flow_index15</th>\n",
              "      <th>on_balance_volume15</th>\n",
              "      <th>ulcer_index15</th>\n",
              "      <th>sma_indicator20</th>\n",
              "      <th>...</th>\n",
              "      <th>money_flow_index35</th>\n",
              "      <th>on_balance_volume35</th>\n",
              "      <th>ulcer_index35</th>\n",
              "      <th>sma_indicator40</th>\n",
              "      <th>ema_indicator40</th>\n",
              "      <th>average_true_range40</th>\n",
              "      <th>adx40</th>\n",
              "      <th>cci40</th>\n",
              "      <th>roc40</th>\n",
              "      <th>rsi40</th>\n",
              "      <th>force_index40</th>\n",
              "      <th>money_flow_index40</th>\n",
              "      <th>on_balance_volume40</th>\n",
              "      <th>ulcer_index40</th>\n",
              "      <th>sma_indicator45</th>\n",
              "      <th>ema_indicator45</th>\n",
              "      <th>average_true_range45</th>\n",
              "      <th>adx45</th>\n",
              "      <th>cci45</th>\n",
              "      <th>roc45</th>\n",
              "      <th>rsi45</th>\n",
              "      <th>force_index45</th>\n",
              "      <th>money_flow_index45</th>\n",
              "      <th>on_balance_volume45</th>\n",
              "      <th>ulcer_index45</th>\n",
              "      <th>sma_indicator50</th>\n",
              "      <th>ema_indicator50</th>\n",
              "      <th>average_true_range50</th>\n",
              "      <th>adx50</th>\n",
              "      <th>cci50</th>\n",
              "      <th>roc50</th>\n",
              "      <th>rsi50</th>\n",
              "      <th>force_index50</th>\n",
              "      <th>money_flow_index50</th>\n",
              "      <th>on_balance_volume50</th>\n",
              "      <th>ulcer_index50</th>\n",
              "      <th>acc_dist_index</th>\n",
              "      <th>cumulative_return</th>\n",
              "      <th>daily_log_return</th>\n",
              "      <th>daily_return</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-03-17</th>\n",
              "      <td>31.475000</td>\n",
              "      <td>31.830000</td>\n",
              "      <td>31.412500</td>\n",
              "      <td>32.117500</td>\n",
              "      <td>28.953447</td>\n",
              "      <td>204092400</td>\n",
              "      <td>31.113499</td>\n",
              "      <td>31.355336</td>\n",
              "      <td>0.674854</td>\n",
              "      <td>45.282571</td>\n",
              "      <td>166.666667</td>\n",
              "      <td>2.031962</td>\n",
              "      <td>60.835341</td>\n",
              "      <td>3.192186e+07</td>\n",
              "      <td>73.328474</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>2.329223</td>\n",
              "      <td>31.386750</td>\n",
              "      <td>31.432506</td>\n",
              "      <td>0.671668</td>\n",
              "      <td>26.702521</td>\n",
              "      <td>37.342668</td>\n",
              "      <td>-1.793445</td>\n",
              "      <td>55.054594</td>\n",
              "      <td>6.293812e+06</td>\n",
              "      <td>45.139318</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>4.249636</td>\n",
              "      <td>31.693166</td>\n",
              "      <td>31.465652</td>\n",
              "      <td>0.672812</td>\n",
              "      <td>23.397505</td>\n",
              "      <td>-7.230524</td>\n",
              "      <td>-3.881365</td>\n",
              "      <td>56.190986</td>\n",
              "      <td>2.537203e+06</td>\n",
              "      <td>34.411178</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>4.858499</td>\n",
              "      <td>31.917875</td>\n",
              "      <td>...</td>\n",
              "      <td>64.482921</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>3.337691</td>\n",
              "      <td>30.714937</td>\n",
              "      <td>30.724633</td>\n",
              "      <td>0.699112</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>46.361314</td>\n",
              "      <td>19.860369</td>\n",
              "      <td>59.404395</td>\n",
              "      <td>-2.209559e+06</td>\n",
              "      <td>67.809882</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>3.175521</td>\n",
              "      <td>30.313722</td>\n",
              "      <td>30.555396</td>\n",
              "      <td>0.698566</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>54.667965</td>\n",
              "      <td>13.418441</td>\n",
              "      <td>59.610829</td>\n",
              "      <td>-6.406228e+06</td>\n",
              "      <td>63.328036</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>3.218801</td>\n",
              "      <td>30.00315</td>\n",
              "      <td>30.396444</td>\n",
              "      <td>0.699026</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>61.780071</td>\n",
              "      <td>16.198665</td>\n",
              "      <td>59.769765</td>\n",
              "      <td>-1.108759e+07</td>\n",
              "      <td>62.625162</td>\n",
              "      <td>4044080000</td>\n",
              "      <td>3.111721</td>\n",
              "      <td>4.093498e+07</td>\n",
              "      <td>16.198665</td>\n",
              "      <td>1.658837</td>\n",
              "      <td>1.672672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-18</th>\n",
              "      <td>31.750000</td>\n",
              "      <td>32.290001</td>\n",
              "      <td>31.592501</td>\n",
              "      <td>31.875000</td>\n",
              "      <td>29.279362</td>\n",
              "      <td>261083600</td>\n",
              "      <td>31.424999</td>\n",
              "      <td>31.609391</td>\n",
              "      <td>0.679383</td>\n",
              "      <td>44.026622</td>\n",
              "      <td>110.414321</td>\n",
              "      <td>5.096535</td>\n",
              "      <td>67.985976</td>\n",
              "      <td>5.239370e+07</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>1.566711</td>\n",
              "      <td>31.385000</td>\n",
              "      <td>31.557051</td>\n",
              "      <td>0.674251</td>\n",
              "      <td>25.613248</td>\n",
              "      <td>96.813758</td>\n",
              "      <td>-0.054452</td>\n",
              "      <td>59.295187</td>\n",
              "      <td>2.211992e+07</td>\n",
              "      <td>53.537539</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>4.115201</td>\n",
              "      <td>31.687833</td>\n",
              "      <td>31.547133</td>\n",
              "      <td>0.674458</td>\n",
              "      <td>22.850964</td>\n",
              "      <td>43.473153</td>\n",
              "      <td>-0.248460</td>\n",
              "      <td>59.010261</td>\n",
              "      <td>1.388723e+07</td>\n",
              "      <td>42.313392</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>4.804795</td>\n",
              "      <td>31.914750</td>\n",
              "      <td>...</td>\n",
              "      <td>68.080302</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>3.334872</td>\n",
              "      <td>30.838375</td>\n",
              "      <td>30.792578</td>\n",
              "      <td>0.699072</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>60.096490</td>\n",
              "      <td>18.165931</td>\n",
              "      <td>60.675177</td>\n",
              "      <td>2.451267e+06</td>\n",
              "      <td>68.122838</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>3.187204</td>\n",
              "      <td>30.420500</td>\n",
              "      <td>30.623313</td>\n",
              "      <td>0.698542</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>65.572244</td>\n",
              "      <td>17.592677</td>\n",
              "      <td>60.801501</td>\n",
              "      <td>-2.069549e+06</td>\n",
              "      <td>65.261631</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>3.237832</td>\n",
              "      <td>30.11425</td>\n",
              "      <td>30.463936</td>\n",
              "      <td>0.698996</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.358719</td>\n",
              "      <td>20.912941</td>\n",
              "      <td>60.898858</td>\n",
              "      <td>-6.992495e+06</td>\n",
              "      <td>64.646940</td>\n",
              "      <td>4305163600</td>\n",
              "      <td>3.123476</td>\n",
              "      <td>1.728797e+08</td>\n",
              "      <td>17.506631</td>\n",
              "      <td>1.119342</td>\n",
              "      <td>1.125630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-19</th>\n",
              "      <td>32.187500</td>\n",
              "      <td>32.312500</td>\n",
              "      <td>31.850000</td>\n",
              "      <td>31.475000</td>\n",
              "      <td>29.058285</td>\n",
              "      <td>183238000</td>\n",
              "      <td>31.577500</td>\n",
              "      <td>31.697927</td>\n",
              "      <td>0.636006</td>\n",
              "      <td>43.241338</td>\n",
              "      <td>74.381206</td>\n",
              "      <td>2.450787</td>\n",
              "      <td>58.872057</td>\n",
              "      <td>2.011740e+07</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>1.293559</td>\n",
              "      <td>31.412250</td>\n",
              "      <td>31.614860</td>\n",
              "      <td>0.653076</td>\n",
              "      <td>24.705134</td>\n",
              "      <td>88.612080</td>\n",
              "      <td>0.862270</td>\n",
              "      <td>55.358603</td>\n",
              "      <td>1.001898e+07</td>\n",
              "      <td>62.272027</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>3.812716</td>\n",
              "      <td>31.639166</td>\n",
              "      <td>31.588116</td>\n",
              "      <td>0.660327</td>\n",
              "      <td>22.371603</td>\n",
              "      <td>50.009813</td>\n",
              "      <td>-2.238920</td>\n",
              "      <td>56.373633</td>\n",
              "      <td>6.596921e+06</td>\n",
              "      <td>50.251684</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>4.793018</td>\n",
              "      <td>31.902875</td>\n",
              "      <td>...</td>\n",
              "      <td>66.710717</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>3.407341</td>\n",
              "      <td>30.950562</td>\n",
              "      <td>30.845379</td>\n",
              "      <td>0.693158</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>58.592179</td>\n",
              "      <td>16.385208</td>\n",
              "      <td>59.381942</td>\n",
              "      <td>1.641219e+05</td>\n",
              "      <td>68.179305</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>3.234998</td>\n",
              "      <td>30.516500</td>\n",
              "      <td>30.677735</td>\n",
              "      <td>0.693297</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>63.697890</td>\n",
              "      <td>15.677735</td>\n",
              "      <td>59.582947</td>\n",
              "      <td>-3.911534e+06</td>\n",
              "      <td>65.100685</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>3.287374</td>\n",
              "      <td>30.22045</td>\n",
              "      <td>30.519272</td>\n",
              "      <td>0.694266</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>69.350393</td>\n",
              "      <td>19.988702</td>\n",
              "      <td>59.738371</td>\n",
              "      <td>-8.460837e+06</td>\n",
              "      <td>66.447007</td>\n",
              "      <td>4121925600</td>\n",
              "      <td>3.152843</td>\n",
              "      <td>9.451222e+06</td>\n",
              "      <td>16.619409</td>\n",
              "      <td>-0.757905</td>\n",
              "      <td>-0.755040</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-20</th>\n",
              "      <td>32.062500</td>\n",
              "      <td>32.099998</td>\n",
              "      <td>31.290001</td>\n",
              "      <td>31.802500</td>\n",
              "      <td>28.693634</td>\n",
              "      <td>274780400</td>\n",
              "      <td>31.693000</td>\n",
              "      <td>31.623618</td>\n",
              "      <td>0.670805</td>\n",
              "      <td>36.628439</td>\n",
              "      <td>-12.884734</td>\n",
              "      <td>1.869087</td>\n",
              "      <td>46.123378</td>\n",
              "      <td>-2.322579e+07</td>\n",
              "      <td>74.315892</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>0.956238</td>\n",
              "      <td>31.394750</td>\n",
              "      <td>31.589431</td>\n",
              "      <td>0.668768</td>\n",
              "      <td>22.816168</td>\n",
              "      <td>34.048234</td>\n",
              "      <td>-0.552923</td>\n",
              "      <td>49.353459</td>\n",
              "      <td>-1.178668e+07</td>\n",
              "      <td>50.324835</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>3.552664</td>\n",
              "      <td>31.596500</td>\n",
              "      <td>31.573977</td>\n",
              "      <td>0.670305</td>\n",
              "      <td>20.947581</td>\n",
              "      <td>-1.465038</td>\n",
              "      <td>-1.992844</td>\n",
              "      <td>52.247896</td>\n",
              "      <td>-7.966714e+06</td>\n",
              "      <td>49.928334</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>4.761633</td>\n",
              "      <td>31.857875</td>\n",
              "      <td>...</td>\n",
              "      <td>63.191552</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>3.524798</td>\n",
              "      <td>31.034937</td>\n",
              "      <td>30.876092</td>\n",
              "      <td>0.696079</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>34.374320</td>\n",
              "      <td>12.010676</td>\n",
              "      <td>57.315230</td>\n",
              "      <td>-5.205453e+06</td>\n",
              "      <td>65.635435</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>3.343300</td>\n",
              "      <td>30.605944</td>\n",
              "      <td>30.712398</td>\n",
              "      <td>0.695890</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>44.966106</td>\n",
              "      <td>14.663020</td>\n",
              "      <td>57.634359</td>\n",
              "      <td>-8.520257e+06</td>\n",
              "      <td>64.463310</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>3.369511</td>\n",
              "      <td>30.31120</td>\n",
              "      <td>30.556752</td>\n",
              "      <td>0.696580</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>52.127614</td>\n",
              "      <td>16.844548</td>\n",
              "      <td>57.881868</td>\n",
              "      <td>-1.243932e+07</td>\n",
              "      <td>64.497071</td>\n",
              "      <td>3847145200</td>\n",
              "      <td>3.235523</td>\n",
              "      <td>-1.398124e+08</td>\n",
              "      <td>15.155950</td>\n",
              "      <td>-1.262842</td>\n",
              "      <td>-1.254902</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-03-23</th>\n",
              "      <td>31.780001</td>\n",
              "      <td>31.962500</td>\n",
              "      <td>31.629999</td>\n",
              "      <td>31.672501</td>\n",
              "      <td>28.992193</td>\n",
              "      <td>150838800</td>\n",
              "      <td>31.806000</td>\n",
              "      <td>31.683245</td>\n",
              "      <td>0.634144</td>\n",
              "      <td>31.338119</td>\n",
              "      <td>-9.694390</td>\n",
              "      <td>1.808727</td>\n",
              "      <td>55.897551</td>\n",
              "      <td>9.827099e+05</td>\n",
              "      <td>74.570561</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>1.052033</td>\n",
              "      <td>31.396500</td>\n",
              "      <td>31.628170</td>\n",
              "      <td>0.650642</td>\n",
              "      <td>21.116099</td>\n",
              "      <td>63.145725</td>\n",
              "      <td>0.055057</td>\n",
              "      <td>53.902544</td>\n",
              "      <td>-6.618813e+05</td>\n",
              "      <td>62.143994</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>3.356974</td>\n",
              "      <td>31.565166</td>\n",
              "      <td>31.602542</td>\n",
              "      <td>0.658118</td>\n",
              "      <td>19.618493</td>\n",
              "      <td>33.671037</td>\n",
              "      <td>-1.456345</td>\n",
              "      <td>55.128669</td>\n",
              "      <td>-7.959116e+05</td>\n",
              "      <td>49.250507</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>4.720288</td>\n",
              "      <td>31.785500</td>\n",
              "      <td>...</td>\n",
              "      <td>62.453906</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>3.592283</td>\n",
              "      <td>31.123875</td>\n",
              "      <td>30.921283</td>\n",
              "      <td>0.690864</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>41.876992</td>\n",
              "      <td>12.595146</td>\n",
              "      <td>58.527318</td>\n",
              "      <td>-2.541786e+06</td>\n",
              "      <td>65.585966</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>3.413423</td>\n",
              "      <td>30.719222</td>\n",
              "      <td>30.759794</td>\n",
              "      <td>0.691259</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>50.728876</td>\n",
              "      <td>19.088186</td>\n",
              "      <td>58.763608</td>\n",
              "      <td>-6.001998e+06</td>\n",
              "      <td>66.203097</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>3.361199</td>\n",
              "      <td>30.38780</td>\n",
              "      <td>30.605605</td>\n",
              "      <td>0.692399</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>57.054179</td>\n",
              "      <td>13.692019</td>\n",
              "      <td>58.947739</td>\n",
              "      <td>-1.001426e+07</td>\n",
              "      <td>64.324829</td>\n",
              "      <td>3997984000</td>\n",
              "      <td>3.293577</td>\n",
              "      <td>-1.341414e+08</td>\n",
              "      <td>16.354157</td>\n",
              "      <td>1.035132</td>\n",
              "      <td>1.040508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-24</th>\n",
              "      <td>122.820000</td>\n",
              "      <td>122.900002</td>\n",
              "      <td>120.070000</td>\n",
              "      <td>120.589996</td>\n",
              "      <td>119.886360</td>\n",
              "      <td>88530500</td>\n",
              "      <td>121.307999</td>\n",
              "      <td>121.617514</td>\n",
              "      <td>3.147921</td>\n",
              "      <td>19.765173</td>\n",
              "      <td>-47.207056</td>\n",
              "      <td>-3.743192</td>\n",
              "      <td>39.040075</td>\n",
              "      <td>-7.091615e+07</td>\n",
              "      <td>34.763713</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>3.136545</td>\n",
              "      <td>122.384999</td>\n",
              "      <td>122.013795</td>\n",
              "      <td>3.497243</td>\n",
              "      <td>28.372827</td>\n",
              "      <td>-68.971381</td>\n",
              "      <td>0.091676</td>\n",
              "      <td>42.295941</td>\n",
              "      <td>-4.715239e+07</td>\n",
              "      <td>46.913707</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>3.372937</td>\n",
              "      <td>121.521999</td>\n",
              "      <td>122.547871</td>\n",
              "      <td>3.624122</td>\n",
              "      <td>27.695322</td>\n",
              "      <td>-25.992232</td>\n",
              "      <td>-1.613962</td>\n",
              "      <td>42.834084</td>\n",
              "      <td>-4.380101e+07</td>\n",
              "      <td>35.574191</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>6.763175</td>\n",
              "      <td>122.002499</td>\n",
              "      <td>...</td>\n",
              "      <td>34.419983</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>11.814730</td>\n",
              "      <td>127.700250</td>\n",
              "      <td>125.380130</td>\n",
              "      <td>3.694247</td>\n",
              "      <td>13.370345</td>\n",
              "      <td>-75.576842</td>\n",
              "      <td>-16.114842</td>\n",
              "      <td>46.857003</td>\n",
              "      <td>-3.993242e+07</td>\n",
              "      <td>33.514834</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>11.740385</td>\n",
              "      <td>128.934666</td>\n",
              "      <td>125.624960</td>\n",
              "      <td>3.687888</td>\n",
              "      <td>12.529801</td>\n",
              "      <td>-81.470951</td>\n",
              "      <td>-6.054921</td>\n",
              "      <td>47.500668</td>\n",
              "      <td>-3.776112e+07</td>\n",
              "      <td>41.936897</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>11.101152</td>\n",
              "      <td>128.91260</td>\n",
              "      <td>125.770880</td>\n",
              "      <td>3.678568</td>\n",
              "      <td>12.010088</td>\n",
              "      <td>-89.086698</td>\n",
              "      <td>-6.892542</td>\n",
              "      <td>48.072872</td>\n",
              "      <td>-3.548652e+07</td>\n",
              "      <td>39.964218</td>\n",
              "      <td>3694437000</td>\n",
              "      <td>10.695930</td>\n",
              "      <td>8.195381e+09</td>\n",
              "      <td>339.367039</td>\n",
              "      <td>-2.019609</td>\n",
              "      <td>-1.999351</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-25</th>\n",
              "      <td>119.540001</td>\n",
              "      <td>121.660004</td>\n",
              "      <td>119.000000</td>\n",
              "      <td>121.209999</td>\n",
              "      <td>120.385513</td>\n",
              "      <td>98844700</td>\n",
              "      <td>121.319998</td>\n",
              "      <td>121.275008</td>\n",
              "      <td>3.050337</td>\n",
              "      <td>21.091700</td>\n",
              "      <td>-67.532434</td>\n",
              "      <td>0.049778</td>\n",
              "      <td>42.454670</td>\n",
              "      <td>-3.080332e+07</td>\n",
              "      <td>36.150238</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>2.765111</td>\n",
              "      <td>122.247999</td>\n",
              "      <td>121.754923</td>\n",
              "      <td>3.413519</td>\n",
              "      <td>27.882780</td>\n",
              "      <td>-80.293488</td>\n",
              "      <td>-1.123322</td>\n",
              "      <td>43.735864</td>\n",
              "      <td>-2.959334e+07</td>\n",
              "      <td>37.861638</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>3.296697</td>\n",
              "      <td>121.552666</td>\n",
              "      <td>122.303136</td>\n",
              "      <td>3.559847</td>\n",
              "      <td>27.494146</td>\n",
              "      <td>-51.560524</td>\n",
              "      <td>0.382918</td>\n",
              "      <td>43.762508</td>\n",
              "      <td>-3.214809e+07</td>\n",
              "      <td>37.173504</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>6.191894</td>\n",
              "      <td>121.982499</td>\n",
              "      <td>...</td>\n",
              "      <td>34.433018</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.944658</td>\n",
              "      <td>127.163500</td>\n",
              "      <td>125.146465</td>\n",
              "      <td>3.668391</td>\n",
              "      <td>13.441953</td>\n",
              "      <td>-80.042404</td>\n",
              "      <td>-15.113334</td>\n",
              "      <td>47.179008</td>\n",
              "      <td>-3.557365e+07</td>\n",
              "      <td>34.002513</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.897897</td>\n",
              "      <td>128.680444</td>\n",
              "      <td>125.406049</td>\n",
              "      <td>3.665046</td>\n",
              "      <td>12.573743</td>\n",
              "      <td>-83.610511</td>\n",
              "      <td>-8.664700</td>\n",
              "      <td>47.783740</td>\n",
              "      <td>-3.397053e+07</td>\n",
              "      <td>39.940568</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>11.335815</td>\n",
              "      <td>128.74840</td>\n",
              "      <td>125.567708</td>\n",
              "      <td>3.658196</td>\n",
              "      <td>12.028678</td>\n",
              "      <td>-91.683548</td>\n",
              "      <td>-6.374229</td>\n",
              "      <td>48.325260</td>\n",
              "      <td>-3.215676e+07</td>\n",
              "      <td>39.959075</td>\n",
              "      <td>3793281700</td>\n",
              "      <td>10.895303</td>\n",
              "      <td>8.214703e+09</td>\n",
              "      <td>341.196363</td>\n",
              "      <td>0.415490</td>\n",
              "      <td>0.416354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-26</th>\n",
              "      <td>120.349998</td>\n",
              "      <td>121.480003</td>\n",
              "      <td>118.919998</td>\n",
              "      <td>121.389999</td>\n",
              "      <td>121.004463</td>\n",
              "      <td>94071200</td>\n",
              "      <td>121.563998</td>\n",
              "      <td>121.253338</td>\n",
              "      <td>2.952271</td>\n",
              "      <td>22.336771</td>\n",
              "      <td>-63.633921</td>\n",
              "      <td>1.016752</td>\n",
              "      <td>47.051731</td>\n",
              "      <td>-1.094070e+06</td>\n",
              "      <td>61.928560</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>2.078645</td>\n",
              "      <td>122.265999</td>\n",
              "      <td>121.655846</td>\n",
              "      <td>3.328168</td>\n",
              "      <td>27.481583</td>\n",
              "      <td>-75.702115</td>\n",
              "      <td>0.148723</td>\n",
              "      <td>45.605967</td>\n",
              "      <td>-1.360830e+07</td>\n",
              "      <td>45.984209</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>3.045566</td>\n",
              "      <td>121.538666</td>\n",
              "      <td>122.166494</td>\n",
              "      <td>3.493191</td>\n",
              "      <td>27.322841</td>\n",
              "      <td>-47.249446</td>\n",
              "      <td>-0.172953</td>\n",
              "      <td>44.950328</td>\n",
              "      <td>-2.083903e+07</td>\n",
              "      <td>43.946270</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>5.662475</td>\n",
              "      <td>121.979999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.412630</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>12.081717</td>\n",
              "      <td>126.766500</td>\n",
              "      <td>124.954442</td>\n",
              "      <td>3.640681</td>\n",
              "      <td>13.514197</td>\n",
              "      <td>-76.206742</td>\n",
              "      <td>-11.583629</td>\n",
              "      <td>47.582940</td>\n",
              "      <td>-3.099325e+07</td>\n",
              "      <td>36.582681</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>12.024050</td>\n",
              "      <td>128.332444</td>\n",
              "      <td>125.223612</td>\n",
              "      <td>3.640490</td>\n",
              "      <td>12.618661</td>\n",
              "      <td>-79.209514</td>\n",
              "      <td>-11.441511</td>\n",
              "      <td>48.138369</td>\n",
              "      <td>-2.995771e+07</td>\n",
              "      <td>39.465059</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>11.563945</td>\n",
              "      <td>128.55480</td>\n",
              "      <td>125.396817</td>\n",
              "      <td>3.636233</td>\n",
              "      <td>12.048508</td>\n",
              "      <td>-86.533716</td>\n",
              "      <td>-7.395523</td>\n",
              "      <td>48.641115</td>\n",
              "      <td>-2.860848e+07</td>\n",
              "      <td>39.941466</td>\n",
              "      <td>3887352900</td>\n",
              "      <td>11.092756</td>\n",
              "      <td>8.288931e+09</td>\n",
              "      <td>343.464736</td>\n",
              "      <td>0.512824</td>\n",
              "      <td>0.514141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-29</th>\n",
              "      <td>121.650002</td>\n",
              "      <td>122.580002</td>\n",
              "      <td>120.730003</td>\n",
              "      <td>119.900002</td>\n",
              "      <td>121.184158</td>\n",
              "      <td>80819200</td>\n",
              "      <td>121.163998</td>\n",
              "      <td>121.298892</td>\n",
              "      <td>2.731816</td>\n",
              "      <td>18.832909</td>\n",
              "      <td>22.743043</td>\n",
              "      <td>-1.620877</td>\n",
              "      <td>48.543492</td>\n",
              "      <td>4.119772e+06</td>\n",
              "      <td>59.264480</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>1.973351</td>\n",
              "      <td>122.005999</td>\n",
              "      <td>121.607510</td>\n",
              "      <td>3.180351</td>\n",
              "      <td>26.207793</td>\n",
              "      <td>-23.894474</td>\n",
              "      <td>-2.096943</td>\n",
              "      <td>46.182985</td>\n",
              "      <td>-8.489068e+06</td>\n",
              "      <td>45.373600</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>3.209675</td>\n",
              "      <td>121.873999</td>\n",
              "      <td>122.069432</td>\n",
              "      <td>3.383645</td>\n",
              "      <td>26.779343</td>\n",
              "      <td>-13.777852</td>\n",
              "      <td>4.322790</td>\n",
              "      <td>45.309645</td>\n",
              "      <td>-1.641572e+07</td>\n",
              "      <td>50.753777</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>4.707191</td>\n",
              "      <td>121.659999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.341062</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>12.209356</td>\n",
              "      <td>126.502249</td>\n",
              "      <td>124.780567</td>\n",
              "      <td>3.595914</td>\n",
              "      <td>13.537878</td>\n",
              "      <td>-61.271789</td>\n",
              "      <td>-8.010009</td>\n",
              "      <td>47.702026</td>\n",
              "      <td>-2.877176e+07</td>\n",
              "      <td>39.352361</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>12.101164</td>\n",
              "      <td>127.939555</td>\n",
              "      <td>125.056933</td>\n",
              "      <td>3.600701</td>\n",
              "      <td>12.626289</td>\n",
              "      <td>-66.271030</td>\n",
              "      <td>-12.713027</td>\n",
              "      <td>48.242739</td>\n",
              "      <td>-2.802270e+07</td>\n",
              "      <td>38.897470</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>11.784041</td>\n",
              "      <td>128.40440</td>\n",
              "      <td>125.239687</td>\n",
              "      <td>3.600508</td>\n",
              "      <td>12.038982</td>\n",
              "      <td>-72.536373</td>\n",
              "      <td>-5.833531</td>\n",
              "      <td>48.733946</td>\n",
              "      <td>-2.691609e+07</td>\n",
              "      <td>41.433666</td>\n",
              "      <td>3968172100</td>\n",
              "      <td>11.270592</td>\n",
              "      <td>8.265777e+09</td>\n",
              "      <td>344.123293</td>\n",
              "      <td>0.148392</td>\n",
              "      <td>0.148503</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-30</th>\n",
              "      <td>120.110001</td>\n",
              "      <td>120.400002</td>\n",
              "      <td>118.860001</td>\n",
              "      <td>122.150002</td>\n",
              "      <td>119.696686</td>\n",
              "      <td>85671900</td>\n",
              "      <td>120.635998</td>\n",
              "      <td>120.832595</td>\n",
              "      <td>2.691453</td>\n",
              "      <td>21.226957</td>\n",
              "      <td>-121.101740</td>\n",
              "      <td>-2.154398</td>\n",
              "      <td>37.586286</td>\n",
              "      <td>-3.980378e+07</td>\n",
              "      <td>39.165591</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>1.887372</td>\n",
              "      <td>121.438999</td>\n",
              "      <td>121.297054</td>\n",
              "      <td>3.115316</td>\n",
              "      <td>26.102997</td>\n",
              "      <td>-107.291047</td>\n",
              "      <td>-4.515408</td>\n",
              "      <td>42.077550</td>\n",
              "      <td>-3.015485e+07</td>\n",
              "      <td>35.733984</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>3.437948</td>\n",
              "      <td>121.794666</td>\n",
              "      <td>121.798253</td>\n",
              "      <td>3.326735</td>\n",
              "      <td>26.689178</td>\n",
              "      <td>-102.802413</td>\n",
              "      <td>-0.982735</td>\n",
              "      <td>42.830229</td>\n",
              "      <td>-3.032011e+07</td>\n",
              "      <td>44.068617</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>4.451394</td>\n",
              "      <td>121.398999</td>\n",
              "      <td>...</td>\n",
              "      <td>34.302157</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.350397</td>\n",
              "      <td>126.146250</td>\n",
              "      <td>124.542491</td>\n",
              "      <td>3.569266</td>\n",
              "      <td>13.619278</td>\n",
              "      <td>-81.403218</td>\n",
              "      <td>-10.615772</td>\n",
              "      <td>46.799342</td>\n",
              "      <td>-3.359513e+07</td>\n",
              "      <td>36.980684</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.226903</td>\n",
              "      <td>127.428000</td>\n",
              "      <td>124.832719</td>\n",
              "      <td>3.576908</td>\n",
              "      <td>12.680515</td>\n",
              "      <td>-83.111576</td>\n",
              "      <td>-16.106910</td>\n",
              "      <td>47.434576</td>\n",
              "      <td>-3.235436e+07</td>\n",
              "      <td>36.076173</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>12.030375</td>\n",
              "      <td>128.25960</td>\n",
              "      <td>125.030288</td>\n",
              "      <td>3.579098</td>\n",
              "      <td>12.068096</td>\n",
              "      <td>-88.246503</td>\n",
              "      <td>-5.694508</td>\n",
              "      <td>48.001097</td>\n",
              "      <td>-3.086647e+07</td>\n",
              "      <td>41.671428</td>\n",
              "      <td>3882500200</td>\n",
              "      <td>11.459915</td>\n",
              "      <td>8.295818e+09</td>\n",
              "      <td>338.671918</td>\n",
              "      <td>-1.235042</td>\n",
              "      <td>-1.227446</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1521 rows × 120 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  open        high  ...  daily_log_return  daily_return\n",
              "date                                ...                                \n",
              "2015-03-17   31.475000   31.830000  ...          1.658837      1.672672\n",
              "2015-03-18   31.750000   32.290001  ...          1.119342      1.125630\n",
              "2015-03-19   32.187500   32.312500  ...         -0.757905     -0.755040\n",
              "2015-03-20   32.062500   32.099998  ...         -1.262842     -1.254902\n",
              "2015-03-23   31.780001   31.962500  ...          1.035132      1.040508\n",
              "...                ...         ...  ...               ...           ...\n",
              "2021-03-24  122.820000  122.900002  ...         -2.019609     -1.999351\n",
              "2021-03-25  119.540001  121.660004  ...          0.415490      0.416354\n",
              "2021-03-26  120.349998  121.480003  ...          0.512824      0.514141\n",
              "2021-03-29  121.650002  122.580002  ...          0.148392      0.148503\n",
              "2021-03-30  120.110001  120.400002  ...         -1.235042     -1.227446\n",
              "\n",
              "[1521 rows x 120 columns]"
            ]
          },
          "execution_count": 177,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Drop the Nan values\n",
        "df = df.dropna()\n",
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4XR1vQGs7kPX"
      },
      "source": [
        "# **Feature selection**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TAaJ05KcKr7S"
      },
      "source": [
        "**In this section, we will introduce the three methods for feature selection.**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-yWUccVW9MZI"
      },
      "source": [
        "## **Filter methods**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WtTv_95GHuyI"
      },
      "source": [
        "### **Most Correlated features with the target**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eHJGA6ELHuI8",
        "outputId": "d7ebcaf6-6a29-45ae-83f8-2463c993a542"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['open',\n",
              " 'high',\n",
              " 'low',\n",
              " 'close',\n",
              " 'adj_close',\n",
              " 'sma_indicator5',\n",
              " 'ema_indicator5',\n",
              " 'sma_indicator10',\n",
              " 'ema_indicator10',\n",
              " 'sma_indicator15',\n",
              " 'ema_indicator15',\n",
              " 'sma_indicator20',\n",
              " 'ema_indicator20',\n",
              " 'sma_indicator25',\n",
              " 'ema_indicator25',\n",
              " 'average_true_range25',\n",
              " 'sma_indicator30',\n",
              " 'ema_indicator30',\n",
              " 'average_true_range30',\n",
              " 'sma_indicator35',\n",
              " 'ema_indicator35',\n",
              " 'average_true_range35',\n",
              " 'sma_indicator40',\n",
              " 'ema_indicator40',\n",
              " 'average_true_range40',\n",
              " 'sma_indicator45',\n",
              " 'ema_indicator45',\n",
              " 'average_true_range45',\n",
              " 'sma_indicator50',\n",
              " 'ema_indicator50',\n",
              " 'average_true_range50',\n",
              " 'cumulative_return']"
            ]
          },
          "execution_count": 178,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Create the correlation matrix\n",
        "corr = df.corr()[['close']]\n",
        "\n",
        "# Chosing the features that are correlated (above 0.9),\n",
        "# or negatively correlated with the target (below -0.9)\n",
        "F1 = corr[abs(corr['close']) > 0.9].index.tolist()\n",
        "F1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ihX9gZj-H9cP"
      },
      "source": [
        "### **F-regression test**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wjBscPu-H-KD",
        "outputId": "f8a96367-941c-4cdb-9b96-0839c6f03c57"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['open',\n",
              " 'high',\n",
              " 'low',\n",
              " 'adj_close',\n",
              " 'sma_indicator5',\n",
              " 'ema_indicator5',\n",
              " 'sma_indicator10',\n",
              " 'ema_indicator10',\n",
              " 'sma_indicator15',\n",
              " 'ema_indicator15',\n",
              " 'sma_indicator20',\n",
              " 'ema_indicator20',\n",
              " 'ema_indicator25',\n",
              " 'ema_indicator30',\n",
              " 'cumulative_return']"
            ]
          },
          "execution_count": 179,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from sklearn.datasets import make_regression\n",
        "from sklearn.feature_selection import SelectKBest\n",
        "from sklearn.feature_selection import f_regression\n",
        "\n",
        "data = df.drop('close', axis = 1)\n",
        "fs = SelectKBest(score_func = f_regression, k = 15)\n",
        "fs_tr = fs.fit_transform(data, df.close)\n",
        "F2 = data.columns[(fs.get_support())].tolist()\n",
        "F2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zy0mZy7yB-TY"
      },
      "source": [
        "## **Embedded methods**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mQVlXWn7H3R6"
      },
      "source": [
        "### **RandomForestRegressor**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d-VynFGLH3yT",
        "outputId": "64425260-bea2-4382-a2a3-0f879ba818ee"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['open',\n",
              " 'high',\n",
              " 'low',\n",
              " 'adj_close',\n",
              " 'ema_indicator5',\n",
              " 'acc_dist_index',\n",
              " 'cumulative_return']"
            ]
          },
          "execution_count": 180,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.feature_selection import SelectFromModel\n",
        "\n",
        "data = df.drop('close', axis = 1)\n",
        "sel = SelectFromModel(RandomForestRegressor(n_estimators = 500))\n",
        "sel.fit(data, df.close.values)\n",
        "F3 = data.columns[(sel.get_support())].tolist()\n",
        "F3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rcFExyR2OhDU"
      },
      "source": [
        "### **Lasso regularization**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yVvdStQBCu0J"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV\n",
        "from sklearn.linear_model import Lasso"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-ubJC_arC6A0"
      },
      "outputs": [],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(df, df.close, test_size=0.2, shuffle=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iv6eSt0lO7zK"
      },
      "outputs": [],
      "source": [
        "pipeline = Pipeline([\n",
        "                     ('scaler', MinMaxScaler()),\n",
        "                     ('model', Lasso())\n",
        "])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tHtuzv2vDQ7t",
        "outputId": "2c7ea915-5073-4a9b-a4cf-234e0984c1c0"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.198e+01, tolerance: 1.591e+01\n",
            "  coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+01, tolerance: 1.352e+01\n",
            "  coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.317e+01, tolerance: 1.274e+01\n",
            "  coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/linear_model/_coordinate_descent.py:648: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.810e+01, tolerance: 1.352e+01\n",
            "  coef_, l1_reg, l2_reg, X, y, max_iter, tol, rng, random, positive\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "GridSearchCV(estimator=Pipeline(steps=[('scaler', MinMaxScaler()),\n",
              "                                       ('model', Lasso())]),\n",
              "             param_grid={'model__alpha': array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2, 1.3,\n",
              "       1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. , 2.1, 2.2, 2.3, 2.4, 2.5, 2.6,\n",
              "       2.7, 2.8, 2.9, 3. , 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9,\n",
              "       4. , 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5. , 5.1, 5.2,\n",
              "       5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6. , 6.1, 6.2, 6.3, 6.4, 6.5,\n",
              "       6.6, 6.7, 6.8, 6.9, 7. , 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8,\n",
              "       7.9, 8. , 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 9. , 9.1,\n",
              "       9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9])},\n",
              "             scoring='neg_mean_squared_error')"
            ]
          },
          "execution_count": 184,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "search = GridSearchCV(pipeline,\n",
        "                      {'model__alpha':np.arange(0.1,10,0.1)}, \n",
        "                      scoring=\"neg_mean_squared_error\",\n",
        "                      cv=None\n",
        "                      )\n",
        "\n",
        "search.fit(X_train,y_train)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VOKHA8r9D8FS"
      },
      "source": [
        "**The importance of a feature is the absolute value of its coefficient.**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6nOQsCtADzqK"
      },
      "outputs": [],
      "source": [
        "coefficients = search.best_estimator_.named_steps['model'].coef_\n",
        "importance = np.abs(coefficients)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WXqP1kQLEFLk",
        "outputId": "cf622336-eafa-4cc3-d1a8-14ddb6ef0b80"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['close',\n",
              " 'ema_indicator10',\n",
              " 'ema_indicator15',\n",
              " 'ema_indicator20',\n",
              " 'ema_indicator50',\n",
              " 'acc_dist_index']"
            ]
          },
          "execution_count": 186,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "F4 = np.array(df.columns)[importance > 0].tolist()\n",
        "F4"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IiyuruhHQSsq"
      },
      "source": [
        "## **Wrapper methods**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "METZ68MFR271"
      },
      "source": [
        "### **Bi-directional elimination (Step-wise Selection)**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "loYe8QMcVQ7u"
      },
      "outputs": [],
      "source": [
        "scaler = MinMaxScaler()\n",
        "df_scaled =  df.copy()\n",
        "\n",
        "df_scaled[df.columns.tolist()] = scaler.fit_transform(df_scaled[df.columns.tolist()])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "w7o8v1gcPwCu"
      },
      "outputs": [],
      "source": [
        "def stepwise_selection(data, target,SL_in=0.05,SL_out = 0.05):\n",
        "    initial_features = data.columns.tolist()\n",
        "    best_features = []\n",
        "\n",
        "    while (len(initial_features) > 0):\n",
        "        remaining_features = list(set(initial_features)-set(best_features))\n",
        "        new_pval = pd.Series(index = remaining_features)\n",
        "        for new_column in remaining_features:\n",
        "            model = sm.OLS(target, sm.add_constant(data[best_features+[new_column]])).fit()\n",
        "            new_pval[new_column] = model.pvalues[new_column]\n",
        "        min_p_value = new_pval.min()\n",
        "        if (min_p_value < SL_in):\n",
        "            best_features.append(new_pval.idxmin())\n",
        "            while (len(best_features) > 0):\n",
        "                best_features_with_constant = sm.add_constant(data[best_features])\n",
        "                p_values = sm.OLS(target, best_features_with_constant).fit().pvalues[1:]\n",
        "                max_p_value = p_values.max()\n",
        "                if (max_p_value >= SL_out):\n",
        "                    excluded_feature = p_values.idxmax()\n",
        "                    best_features.remove(excluded_feature)\n",
        "                else:\n",
        "                    break \n",
        "        else:\n",
        "            break\n",
        "    return best_features"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jh5ZYPIHYFo9"
      },
      "outputs": [],
      "source": [
        "data = df_scaled.drop('close', axis = 1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NayvFLICQSvV",
        "outputId": "e9e4a785-fdeb-4aad-a5e4-106ed28c6949"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
            "  import sys\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "['low', 'cumulative_return', 'open', 'high', 'daily_return']"
            ]
          },
          "execution_count": 190,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "F5 = stepwise_selection(data, df_scaled.close)\n",
        "F5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_psucGeXdeEw"
      },
      "source": [
        "## **Set of all features**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yXB5jhCLY9rr"
      },
      "outputs": [],
      "source": [
        "all_F = F1 + F2 + F3 + F4 + F5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z_-hG_dPdGxS",
        "outputId": "5414469b-7ee4-471b-fc1b-0f4721ccd369"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['ema_indicator40',\n",
              " 'adj_close',\n",
              " 'daily_return',\n",
              " 'cumulative_return',\n",
              " 'sma_indicator25',\n",
              " 'ema_indicator20',\n",
              " 'sma_indicator5',\n",
              " 'ema_indicator10',\n",
              " 'ema_indicator45',\n",
              " 'average_true_range45',\n",
              " 'low',\n",
              " 'close',\n",
              " 'ema_indicator15',\n",
              " 'ema_indicator5',\n",
              " 'average_true_range30',\n",
              " 'open',\n",
              " 'average_true_range50',\n",
              " 'acc_dist_index',\n",
              " 'sma_indicator20',\n",
              " 'sma_indicator10',\n",
              " 'average_true_range25',\n",
              " 'ema_indicator50',\n",
              " 'sma_indicator45',\n",
              " 'sma_indicator35',\n",
              " 'sma_indicator15',\n",
              " 'ema_indicator25',\n",
              " 'sma_indicator50',\n",
              " 'sma_indicator40',\n",
              " 'ema_indicator35',\n",
              " 'ema_indicator30',\n",
              " 'average_true_range40',\n",
              " 'high',\n",
              " 'sma_indicator30',\n",
              " 'average_true_range35']"
            ]
          },
          "execution_count": 192,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "all_F = list(set(all_F))\n",
        "all_F"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "15cEy4QvhThX"
      },
      "outputs": [],
      "source": [
        "# Saving the new dataset\n",
        "df = df[all_F]\n",
        "df.to_csv('new_apple_f.csv')"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [
        "DwAcW1H-6MqI",
        "1B2PqxSg6Qz8",
        "6h49D40q6U1n",
        "QStoAOFS6Y1w",
        "ktQX6Ted6cJK",
        "WMvYKas2JuLW",
        "DSsScW_V6_L4",
        "33o_Agbl7FxT",
        "-yWUccVW9MZI",
        "WtTv_95GHuyI",
        "ihX9gZj-H9cP",
        "Zy0mZy7yB-TY",
        "mQVlXWn7H3R6",
        "rcFExyR2OhDU",
        "IiyuruhHQSsq",
        "METZ68MFR271",
        "_psucGeXdeEw"
      ],
      "name": "Data_Construction.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}