Stock_Prediction_Stacked_LSTM.ipynb

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  "metadata": {
    "colab": {
      "name": "Stock_Prediction_Stacked_LSTM.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "l-2AAECceh7f"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import MinMaxScaler"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lHaQ7zzdepp6"
      },
      "source": [
        "df = pd.read_csv('Processed_DJI.csv',index_col='Date', parse_dates = True)\n",
        "df = df.drop('Name', axis = 1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        },
        "id": "f83q3E-UkD2j",
        "outputId": "ae052e72-8bd2-4358-fecf-218a4980669f"
      },
      "source": [
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>Close</th>\n",
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              "      <th>GBP</th>\n",
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              "      <th>TE1</th>\n",
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              "      <th>AUD</th>\n",
              "      <th>Brent</th>\n",
              "      <th>CAC-F</th>\n",
              "      <th>copper-F</th>\n",
              "      <th>WIT-oil</th>\n",
              "      <th>DAX-F</th>\n",
              "      <th>DJI-F</th>\n",
              "      <th>EUR</th>\n",
              "      <th>FTSE-F</th>\n",
              "      <th>gold-F</th>\n",
              "      <th>HSI-F</th>\n",
              "      <th>KOSPI-F</th>\n",
              "      <th>NASDAQ-F</th>\n",
              "      <th>GAS-F</th>\n",
              "      <th>Nikkei-F</th>\n",
              "      <th>NZD</th>\n",
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              "      <th>RUSSELL-F</th>\n",
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              "      <th>CHF</th>\n",
              "      <th>Dollar index-F</th>\n",
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              "      <th>wheat-F</th>\n",
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              "      <th>2009-12-31</th>\n",
              "      <td>10428.049805</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",
              "      <td>0.04</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.69</td>\n",
              "      <td>3.85</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.33</td>\n",
              "      <td>6.39</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.65</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.33</td>\n",
              "      <td>6.35</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.48</td>\n",
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              "      <td>-0.12</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.34</td>\n",
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              "      <td>-0.06</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.30</td>\n",
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              "      <th>2010-01-04</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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",
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              "      <td>0.08</td>\n",
              "      <td>0.18</td>\n",
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              "      <td>3.85</td>\n",
              "      <td>0.026830</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.35</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.004222</td>\n",
              "      <td>-0.004467</td>\n",
              "      <td>-0.010644</td>\n",
              "      <td>-0.001991</td>\n",
              "      <td>0.015565</td>\n",
              "      <td>-0.004609</td>\n",
              "      <td>0.021150</td>\n",
              "      <td>0.004192</td>\n",
              "      <td>0.028318</td>\n",
              "      <td>0.015420</td>\n",
              "      <td>0.012227</td>\n",
              "      <td>0.014078</td>\n",
              "      <td>0.019724</td>\n",
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              "      <td>0.023521</td>\n",
              "      <td>0.019733</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.77</td>\n",
              "      <td>3.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.21</td>\n",
              "      <td>6.31</td>\n",
              "      <td>6.34</td>\n",
              "      <td>-0.100000</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>-0.014870</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.81</td>\n",
              "      <td>1.99</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.71</td>\n",
              "      <td>0.96</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.74</td>\n",
              "      <td>2.05</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.51</td>\n",
              "      <td>5.60</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.52</td>\n",
              "      <td>3.26</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.62</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>3.12</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.10</td>\n",
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              "    <tr>\n",
              "      <th>2010-01-05</th>\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",
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              "      <td>0.07</td>\n",
              "      <td>0.17</td>\n",
              "      <td>2.56</td>\n",
              "      <td>3.77</td>\n",
              "      <td>0.002699</td>\n",
              "      <td>0.001560</td>\n",
              "      <td>5.24</td>\n",
              "      <td>6.30</td>\n",
              "      <td>-0.007628</td>\n",
              "      <td>-0.009838</td>\n",
              "      <td>-0.001441</td>\n",
              "      <td>0.000015</td>\n",
              "      <td>0.001729</td>\n",
              "      <td>0.005900</td>\n",
              "      <td>0.005178</td>\n",
              "      <td>-0.011596</td>\n",
              "      <td>0.019370</td>\n",
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              "      <td>3.74</td>\n",
              "      <td>3.70</td>\n",
              "      <td>3.60</td>\n",
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              "      <td>0.14</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.53</td>\n",
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              "      <td>6.23</td>\n",
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              "      <td>-0.08</td>\n",
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              "      <td>-0.08</td>\n",
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              "    <tr>\n",
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              "      <td>NaN</td>\n",
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              "      <td>2.60</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.016883</td>\n",
              "      <td>0.006009</td>\n",
              "      <td>5.30</td>\n",
              "      <td>6.34</td>\n",
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              "      <td>0.008134</td>\n",
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              "      <td>1.59</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.78</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>6.60</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.15</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.25</td>\n",
              "      <td>1.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-07</th>\n",
              "      <td>10606.860352</td>\n",
              "      <td>9.776045</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</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>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>2.62</td>\n",
              "      <td>3.85</td>\n",
              "      <td>-0.006256</td>\n",
              "      <td>0.000221</td>\n",
              "      <td>5.31</td>\n",
              "      <td>6.33</td>\n",
              "      <td>-0.005609</td>\n",
              "      <td>0.011196</td>\n",
              "      <td>0.002035</td>\n",
              "      <td>-0.000073</td>\n",
              "      <td>-0.001849</td>\n",
              "      <td>-0.017013</td>\n",
              "      <td>0.051780</td>\n",
              "      <td>-0.007137</td>\n",
              "      <td>0.019809</td>\n",
              "      <td>-0.010400</td>\n",
              "      <td>0.036286</td>\n",
              "      <td>-0.003142</td>\n",
              "      <td>0.001775</td>\n",
              "      <td>-0.000597</td>\n",
              "      <td>-0.002481</td>\n",
              "      <td>0.004001</td>\n",
              "      <td>-0.006567</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006301</td>\n",
              "      <td>0.002200</td>\n",
              "      <td>3.83</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.69</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.02</td>\n",
              "      <td>2.48</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.019802</td>\n",
              "      <td>0.007692</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-1.90</td>\n",
              "      <td>-0.63</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-1.27</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-3.38</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.72</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.54</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.58</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>2017-11-09</th>\n",
              "      <td>23461.939453</td>\n",
              "      <td>6.511740</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>0.000392</td>\n",
              "      <td>-0.230990</td>\n",
              "      <td>0.261016</td>\n",
              "      <td>1.290420</td>\n",
              "      <td>2.718486</td>\n",
              "      <td>23462.383792</td>\n",
              "      <td>23305.293603</td>\n",
              "      <td>22853.962112</td>\n",
              "      <td>21532.900862</td>\n",
              "      <td>1.05</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.33</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.33</td>\n",
              "      <td>0.005984</td>\n",
              "      <td>0.000623</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.26</td>\n",
              "      <td>-0.004485</td>\n",
              "      <td>0.001459</td>\n",
              "      <td>-0.002633</td>\n",
              "      <td>-0.001988</td>\n",
              "      <td>-0.002043</td>\n",
              "      <td>-0.003310</td>\n",
              "      <td>-0.006461</td>\n",
              "      <td>-0.006864</td>\n",
              "      <td>-0.000102</td>\n",
              "      <td>-0.005558</td>\n",
              "      <td>-0.004792</td>\n",
              "      <td>0.005990</td>\n",
              "      <td>-0.011639</td>\n",
              "      <td>-0.006056</td>\n",
              "      <td>-0.014935</td>\n",
              "      <td>-0.003762</td>\n",
              "      <td>0.007921</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004528</td>\n",
              "      <td>-0.003638</td>\n",
              "      <td>1.28</td>\n",
              "      <td>1.11</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.66</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.93</td>\n",
              "      <td>3.04</td>\n",
              "      <td>3.21</td>\n",
              "      <td>0.007407</td>\n",
              "      <td>-0.012121</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.69</td>\n",
              "      <td>-1.17</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>0.63</td>\n",
              "      <td>-1.42</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.61</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>0.79</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.62</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>0.53</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>23422.210938</td>\n",
              "      <td>-0.991838</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>-0.496952</td>\n",
              "      <td>-0.051116</td>\n",
              "      <td>0.401138</td>\n",
              "      <td>2.406860</td>\n",
              "      <td>23455.079637</td>\n",
              "      <td>23316.428587</td>\n",
              "      <td>22876.246380</td>\n",
              "      <td>21551.699967</td>\n",
              "      <td>1.03</td>\n",
              "      <td>1.21</td>\n",
              "      <td>1.34</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.40</td>\n",
              "      <td>-0.007173</td>\n",
              "      <td>-0.000389</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.002392</td>\n",
              "      <td>-0.004845</td>\n",
              "      <td>-0.003889</td>\n",
              "      <td>0.000558</td>\n",
              "      <td>-0.006880</td>\n",
              "      <td>-0.003348</td>\n",
              "      <td>0.025013</td>\n",
              "      <td>-0.005629</td>\n",
              "      <td>-0.001229</td>\n",
              "      <td>-0.002616</td>\n",
              "      <td>-0.003519</td>\n",
              "      <td>-0.012266</td>\n",
              "      <td>-0.004998</td>\n",
              "      <td>-0.006828</td>\n",
              "      <td>-0.004179</td>\n",
              "      <td>-0.000898</td>\n",
              "      <td>-0.000537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>-0.001383</td>\n",
              "      <td>1.37</td>\n",
              "      <td>1.19</td>\n",
              "      <td>1.06</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>-1.34</td>\n",
              "      <td>-1.21</td>\n",
              "      <td>-1.03</td>\n",
              "      <td>0.007353</td>\n",
              "      <td>0.024540</td>\n",
              "      <td>0.024876</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.75</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-1.02</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-1.66</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.18</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>23439.699219</td>\n",
              "      <td>-65.347705</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>-0.461690</td>\n",
              "      <td>0.389567</td>\n",
              "      <td>0.712119</td>\n",
              "      <td>2.102797</td>\n",
              "      <td>23452.283197</td>\n",
              "      <td>23328.168647</td>\n",
              "      <td>22898.342570</td>\n",
              "      <td>21570.486029</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.08</td>\n",
              "      <td>2.40</td>\n",
              "      <td>0.000352</td>\n",
              "      <td>-0.004944</td>\n",
              "      <td>3.69</td>\n",
              "      <td>4.33</td>\n",
              "      <td>-0.001837</td>\n",
              "      <td>0.002743</td>\n",
              "      <td>0.001065</td>\n",
              "      <td>0.001357</td>\n",
              "      <td>-0.004008</td>\n",
              "      <td>0.003395</td>\n",
              "      <td>-0.071742</td>\n",
              "      <td>0.001433</td>\n",
              "      <td>0.003589</td>\n",
              "      <td>0.000715</td>\n",
              "      <td>-0.001673</td>\n",
              "      <td>-0.000603</td>\n",
              "      <td>-0.007265</td>\n",
              "      <td>-0.002395</td>\n",
              "      <td>-0.004041</td>\n",
              "      <td>0.000984</td>\n",
              "      <td>0.002104</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000136</td>\n",
              "      <td>-0.000469</td>\n",
              "      <td>1.36</td>\n",
              "      <td>1.18</td>\n",
              "      <td>1.05</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.98</td>\n",
              "      <td>3.11</td>\n",
              "      <td>3.29</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.017964</td>\n",
              "      <td>0.009709</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>1.34</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-1.43</td>\n",
              "      <td>-1.07</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.72</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.83</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-14</th>\n",
              "      <td>23409.470703</td>\n",
              "      <td>-1.387911</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>-0.627237</td>\n",
              "      <td>0.137871</td>\n",
              "      <td>-0.137742</td>\n",
              "      <td>1.791640</td>\n",
              "      <td>23444.499107</td>\n",
              "      <td>23335.911700</td>\n",
              "      <td>22918.386810</td>\n",
              "      <td>21588.784384</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.37</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.38</td>\n",
              "      <td>-0.019376</td>\n",
              "      <td>-0.002621</td>\n",
              "      <td>3.66</td>\n",
              "      <td>4.31</td>\n",
              "      <td>0.000236</td>\n",
              "      <td>-0.000888</td>\n",
              "      <td>0.003538</td>\n",
              "      <td>-0.000105</td>\n",
              "      <td>-0.015118</td>\n",
              "      <td>0.006793</td>\n",
              "      <td>-0.058885</td>\n",
              "      <td>-0.001932</td>\n",
              "      <td>-0.006029</td>\n",
              "      <td>0.001430</td>\n",
              "      <td>0.005957</td>\n",
              "      <td>-0.007842</td>\n",
              "      <td>-0.004877</td>\n",
              "      <td>-0.000108</td>\n",
              "      <td>-0.003131</td>\n",
              "      <td>-0.002310</td>\n",
              "      <td>-0.001030</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002583</td>\n",
              "      <td>-0.002980</td>\n",
              "      <td>1.34</td>\n",
              "      <td>1.14</td>\n",
              "      <td>1.01</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.65</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.94</td>\n",
              "      <td>3.07</td>\n",
              "      <td>3.27</td>\n",
              "      <td>0.021898</td>\n",
              "      <td>-0.011765</td>\n",
              "      <td>-0.009615</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-1.50</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-1.64</td>\n",
              "      <td>-1.87</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>1.12</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.31</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>-2.05</td>\n",
              "      <td>0.67</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-15</th>\n",
              "      <td>23271.279297</td>\n",
              "      <td>3.612171</td>\n",
              "      <td>-0.005903</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-1.239552</td>\n",
              "      <td>-0.698658</td>\n",
              "      <td>-0.249391</td>\n",
              "      <td>0.490896</td>\n",
              "      <td>23413.004596</td>\n",
              "      <td>23329.756233</td>\n",
              "      <td>22932.225731</td>\n",
              "      <td>21605.525627</td>\n",
              "      <td>1.06</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.04</td>\n",
              "      <td>2.33</td>\n",
              "      <td>-0.007006</td>\n",
              "      <td>0.005963</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.28</td>\n",
              "      <td>0.002631</td>\n",
              "      <td>-0.001611</td>\n",
              "      <td>-0.000133</td>\n",
              "      <td>-0.000452</td>\n",
              "      <td>-0.013190</td>\n",
              "      <td>-0.008928</td>\n",
              "      <td>0.020112</td>\n",
              "      <td>-0.002796</td>\n",
              "      <td>0.009458</td>\n",
              "      <td>-0.012731</td>\n",
              "      <td>-0.005366</td>\n",
              "      <td>-0.012524</td>\n",
              "      <td>-0.002696</td>\n",
              "      <td>-0.005638</td>\n",
              "      <td>-0.004382</td>\n",
              "      <td>-0.005526</td>\n",
              "      <td>-0.010306</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004873</td>\n",
              "      <td>-0.004867</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.68</td>\n",
              "      <td>1.95</td>\n",
              "      <td>2.92</td>\n",
              "      <td>3.05</td>\n",
              "      <td>3.22</td>\n",
              "      <td>-0.007143</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.009709</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.55</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.99</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-1.74</td>\n",
              "      <td>0.03</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.01</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>-2.04</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1984 rows × 82 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Close     Volume       mom  ...  wheat-F   XAG   XAU\n",
              "Date                                           ...                     \n",
              "2009-12-31  10428.049805        NaN       NaN  ...    -0.48  0.30  0.39\n",
              "2010-01-04  10583.959961        NaN  0.014951  ...     3.12  3.91  2.10\n",
              "2010-01-05  10572.019531        NaN -0.001128  ...    -0.90  1.42 -0.12\n",
              "2010-01-06  10573.679688   0.515598  0.000157  ...     2.62  2.25  1.77\n",
              "2010-01-07  10606.860352   9.776045  0.003138  ...    -1.85  0.22 -0.58\n",
              "...                  ...        ...       ...  ...      ...   ...   ...\n",
              "2017-11-09  23461.939453   6.511740 -0.004304  ...     0.53 -0.26  0.32\n",
              "2017-11-10  23422.210938  -0.991838 -0.001693  ...     0.70 -0.71 -0.80\n",
              "2017-11-13  23439.699219 -65.347705  0.000747  ...    -1.85  0.83  0.16\n",
              "2017-11-14  23409.470703  -1.387911 -0.001290  ...     1.00  0.01  0.24\n",
              "2017-11-15  23271.279297   3.612171 -0.005903  ...    -2.04 -0.22 -0.11\n",
              "\n",
              "[1984 rows x 82 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1fBs9awNnNJr",
        "outputId": "279d69b5-e4ee-422c-83b4-fda9d8b706a7"
      },
      "source": [
        "# Checking for NAN OR Missing Values\n",
        "df.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Close             0\n",
              "Volume            3\n",
              "mom               1\n",
              "mom1              2\n",
              "mom2              3\n",
              "                 ..\n",
              "Dollar index-F    0\n",
              "Dollar index      0\n",
              "wheat-F           2\n",
              "XAG               0\n",
              "XAU               0\n",
              "Length: 82, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ckVzOnD6e2NX"
      },
      "source": [
        "data = df.fillna(df.median())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        },
        "id": "zYfzLcsqe6hz",
        "outputId": "d2b3d197-805a-4fac-c2f5-24e3b0b3ca47"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>mom</th>\n",
              "      <th>mom1</th>\n",
              "      <th>mom2</th>\n",
              "      <th>mom3</th>\n",
              "      <th>ROC_5</th>\n",
              "      <th>ROC_10</th>\n",
              "      <th>ROC_15</th>\n",
              "      <th>ROC_20</th>\n",
              "      <th>EMA_10</th>\n",
              "      <th>EMA_20</th>\n",
              "      <th>EMA_50</th>\n",
              "      <th>EMA_200</th>\n",
              "      <th>DTB4WK</th>\n",
              "      <th>DTB3</th>\n",
              "      <th>DTB6</th>\n",
              "      <th>DGS5</th>\n",
              "      <th>DGS10</th>\n",
              "      <th>Oil</th>\n",
              "      <th>Gold</th>\n",
              "      <th>DAAA</th>\n",
              "      <th>DBAA</th>\n",
              "      <th>GBP</th>\n",
              "      <th>JPY</th>\n",
              "      <th>CAD</th>\n",
              "      <th>CNY</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AMZN</th>\n",
              "      <th>GE</th>\n",
              "      <th>JNJ</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MSFT</th>\n",
              "      <th>WFC</th>\n",
              "      <th>XOM</th>\n",
              "      <th>FCHI</th>\n",
              "      <th>FTSE</th>\n",
              "      <th>GDAXI</th>\n",
              "      <th>GSPC</th>\n",
              "      <th>HSI</th>\n",
              "      <th>...</th>\n",
              "      <th>RUT</th>\n",
              "      <th>NYSE</th>\n",
              "      <th>TE1</th>\n",
              "      <th>TE2</th>\n",
              "      <th>TE3</th>\n",
              "      <th>TE5</th>\n",
              "      <th>TE6</th>\n",
              "      <th>DE1</th>\n",
              "      <th>DE2</th>\n",
              "      <th>DE4</th>\n",
              "      <th>DE5</th>\n",
              "      <th>DE6</th>\n",
              "      <th>CTB3M</th>\n",
              "      <th>CTB6M</th>\n",
              "      <th>CTB1Y</th>\n",
              "      <th>AUD</th>\n",
              "      <th>Brent</th>\n",
              "      <th>CAC-F</th>\n",
              "      <th>copper-F</th>\n",
              "      <th>WIT-oil</th>\n",
              "      <th>DAX-F</th>\n",
              "      <th>DJI-F</th>\n",
              "      <th>EUR</th>\n",
              "      <th>FTSE-F</th>\n",
              "      <th>gold-F</th>\n",
              "      <th>HSI-F</th>\n",
              "      <th>KOSPI-F</th>\n",
              "      <th>NASDAQ-F</th>\n",
              "      <th>GAS-F</th>\n",
              "      <th>Nikkei-F</th>\n",
              "      <th>NZD</th>\n",
              "      <th>silver-F</th>\n",
              "      <th>RUSSELL-F</th>\n",
              "      <th>S&amp;P-F</th>\n",
              "      <th>CHF</th>\n",
              "      <th>Dollar index-F</th>\n",
              "      <th>Dollar index</th>\n",
              "      <th>wheat-F</th>\n",
              "      <th>XAG</th>\n",
              "      <th>XAU</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>2009-12-31</th>\n",
              "      <td>10428.049805</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.000535</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.69</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.000274</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.33</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>0.000865</td>\n",
              "      <td>0.000829</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>0.000354</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.000194</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000367</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.000544</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000997</td>\n",
              "      <td>0.000517</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.65</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.33</td>\n",
              "      <td>6.35</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.48</td>\n",
              "      <td>-1.19</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.34</td>\n",
              "      <td>1.68</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-1.08</td>\n",
              "      <td>-1.00</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-04</th>\n",
              "      <td>10583.959961</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.18</td>\n",
              "      <td>2.65</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.026830</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.35</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.004222</td>\n",
              "      <td>-0.004467</td>\n",
              "      <td>-0.010644</td>\n",
              "      <td>-0.001991</td>\n",
              "      <td>0.015565</td>\n",
              "      <td>-0.004609</td>\n",
              "      <td>0.021150</td>\n",
              "      <td>0.004192</td>\n",
              "      <td>0.028318</td>\n",
              "      <td>0.015420</td>\n",
              "      <td>0.012227</td>\n",
              "      <td>0.014078</td>\n",
              "      <td>0.019724</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.016043</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.023521</td>\n",
              "      <td>0.019733</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.77</td>\n",
              "      <td>3.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.21</td>\n",
              "      <td>6.31</td>\n",
              "      <td>6.34</td>\n",
              "      <td>-0.100000</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>-0.014870</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.81</td>\n",
              "      <td>1.99</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.71</td>\n",
              "      <td>0.96</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.74</td>\n",
              "      <td>2.05</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.51</td>\n",
              "      <td>5.60</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.52</td>\n",
              "      <td>3.26</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.62</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>3.12</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-05</th>\n",
              "      <td>10572.019531</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.17</td>\n",
              "      <td>2.56</td>\n",
              "      <td>3.77</td>\n",
              "      <td>0.002699</td>\n",
              "      <td>0.001560</td>\n",
              "      <td>5.24</td>\n",
              "      <td>6.30</td>\n",
              "      <td>-0.007628</td>\n",
              "      <td>-0.009838</td>\n",
              "      <td>-0.001441</td>\n",
              "      <td>0.000015</td>\n",
              "      <td>0.001729</td>\n",
              "      <td>0.005900</td>\n",
              "      <td>0.005178</td>\n",
              "      <td>-0.011596</td>\n",
              "      <td>0.019370</td>\n",
              "      <td>0.000323</td>\n",
              "      <td>0.027452</td>\n",
              "      <td>0.003904</td>\n",
              "      <td>-0.000264</td>\n",
              "      <td>0.004036</td>\n",
              "      <td>-0.002718</td>\n",
              "      <td>0.003116</td>\n",
              "      <td>0.020909</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002515</td>\n",
              "      <td>0.003839</td>\n",
              "      <td>3.74</td>\n",
              "      <td>3.70</td>\n",
              "      <td>3.60</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.53</td>\n",
              "      <td>6.13</td>\n",
              "      <td>6.23</td>\n",
              "      <td>6.27</td>\n",
              "      <td>-0.055556</td>\n",
              "      <td>-0.073394</td>\n",
              "      <td>-0.033962</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.59</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.32</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.04</td>\n",
              "      <td>2.03</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-4.20</td>\n",
              "      <td>0.47</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>1.96</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.43</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.90</td>\n",
              "      <td>1.42</td>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-06</th>\n",
              "      <td>10573.679688</td>\n",
              "      <td>0.515598</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.60</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.016883</td>\n",
              "      <td>0.006009</td>\n",
              "      <td>5.30</td>\n",
              "      <td>6.34</td>\n",
              "      <td>0.002067</td>\n",
              "      <td>0.008418</td>\n",
              "      <td>-0.007311</td>\n",
              "      <td>0.000191</td>\n",
              "      <td>-0.015906</td>\n",
              "      <td>-0.018116</td>\n",
              "      <td>-0.005151</td>\n",
              "      <td>0.008134</td>\n",
              "      <td>0.005494</td>\n",
              "      <td>-0.006137</td>\n",
              "      <td>0.001425</td>\n",
              "      <td>0.008643</td>\n",
              "      <td>0.001186</td>\n",
              "      <td>0.001358</td>\n",
              "      <td>0.000410</td>\n",
              "      <td>0.000546</td>\n",
              "      <td>0.006153</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000846</td>\n",
              "      <td>0.003104</td>\n",
              "      <td>3.82</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.70</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.49</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>-0.117647</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.91</td>\n",
              "      <td>1.61</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.41</td>\n",
              "      <td>1.72</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.78</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>6.60</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.15</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.25</td>\n",
              "      <td>1.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-07</th>\n",
              "      <td>10606.860352</td>\n",
              "      <td>9.776045</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>2.62</td>\n",
              "      <td>3.85</td>\n",
              "      <td>-0.006256</td>\n",
              "      <td>0.000221</td>\n",
              "      <td>5.31</td>\n",
              "      <td>6.33</td>\n",
              "      <td>-0.005609</td>\n",
              "      <td>0.011196</td>\n",
              "      <td>0.002035</td>\n",
              "      <td>-0.000073</td>\n",
              "      <td>-0.001849</td>\n",
              "      <td>-0.017013</td>\n",
              "      <td>0.051780</td>\n",
              "      <td>-0.007137</td>\n",
              "      <td>0.019809</td>\n",
              "      <td>-0.010400</td>\n",
              "      <td>0.036286</td>\n",
              "      <td>-0.003142</td>\n",
              "      <td>0.001775</td>\n",
              "      <td>-0.000597</td>\n",
              "      <td>-0.002481</td>\n",
              "      <td>0.004001</td>\n",
              "      <td>-0.006567</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006301</td>\n",
              "      <td>0.002200</td>\n",
              "      <td>3.83</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.69</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.02</td>\n",
              "      <td>2.48</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.019802</td>\n",
              "      <td>0.007692</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-1.90</td>\n",
              "      <td>-0.63</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-1.27</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-3.38</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.72</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.54</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.58</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>2017-11-09</th>\n",
              "      <td>23461.939453</td>\n",
              "      <td>6.511740</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>0.000392</td>\n",
              "      <td>-0.230990</td>\n",
              "      <td>0.261016</td>\n",
              "      <td>1.290420</td>\n",
              "      <td>2.718486</td>\n",
              "      <td>23462.383792</td>\n",
              "      <td>23305.293603</td>\n",
              "      <td>22853.962112</td>\n",
              "      <td>21532.900862</td>\n",
              "      <td>1.05</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.33</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.33</td>\n",
              "      <td>0.005984</td>\n",
              "      <td>0.000623</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.26</td>\n",
              "      <td>-0.004485</td>\n",
              "      <td>0.001459</td>\n",
              "      <td>-0.002633</td>\n",
              "      <td>-0.001988</td>\n",
              "      <td>-0.002043</td>\n",
              "      <td>-0.003310</td>\n",
              "      <td>-0.006461</td>\n",
              "      <td>-0.006864</td>\n",
              "      <td>-0.000102</td>\n",
              "      <td>-0.005558</td>\n",
              "      <td>-0.004792</td>\n",
              "      <td>0.005990</td>\n",
              "      <td>-0.011639</td>\n",
              "      <td>-0.006056</td>\n",
              "      <td>-0.014935</td>\n",
              "      <td>-0.003762</td>\n",
              "      <td>0.007921</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004528</td>\n",
              "      <td>-0.003638</td>\n",
              "      <td>1.28</td>\n",
              "      <td>1.11</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.66</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.93</td>\n",
              "      <td>3.04</td>\n",
              "      <td>3.21</td>\n",
              "      <td>0.007407</td>\n",
              "      <td>-0.012121</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.69</td>\n",
              "      <td>-1.17</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>0.63</td>\n",
              "      <td>-1.42</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.61</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>0.79</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.62</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>0.53</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>23422.210938</td>\n",
              "      <td>-0.991838</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>-0.496952</td>\n",
              "      <td>-0.051116</td>\n",
              "      <td>0.401138</td>\n",
              "      <td>2.406860</td>\n",
              "      <td>23455.079637</td>\n",
              "      <td>23316.428587</td>\n",
              "      <td>22876.246380</td>\n",
              "      <td>21551.699967</td>\n",
              "      <td>1.03</td>\n",
              "      <td>1.21</td>\n",
              "      <td>1.34</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.40</td>\n",
              "      <td>-0.007173</td>\n",
              "      <td>-0.000389</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.002392</td>\n",
              "      <td>-0.004845</td>\n",
              "      <td>-0.003889</td>\n",
              "      <td>0.000558</td>\n",
              "      <td>-0.006880</td>\n",
              "      <td>-0.003348</td>\n",
              "      <td>0.025013</td>\n",
              "      <td>-0.005629</td>\n",
              "      <td>-0.001229</td>\n",
              "      <td>-0.002616</td>\n",
              "      <td>-0.003519</td>\n",
              "      <td>-0.012266</td>\n",
              "      <td>-0.004998</td>\n",
              "      <td>-0.006828</td>\n",
              "      <td>-0.004179</td>\n",
              "      <td>-0.000898</td>\n",
              "      <td>-0.000537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>-0.001383</td>\n",
              "      <td>1.37</td>\n",
              "      <td>1.19</td>\n",
              "      <td>1.06</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>-1.34</td>\n",
              "      <td>-1.21</td>\n",
              "      <td>-1.03</td>\n",
              "      <td>0.007353</td>\n",
              "      <td>0.024540</td>\n",
              "      <td>0.024876</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.75</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-1.02</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-1.66</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.18</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>23439.699219</td>\n",
              "      <td>-65.347705</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>-0.461690</td>\n",
              "      <td>0.389567</td>\n",
              "      <td>0.712119</td>\n",
              "      <td>2.102797</td>\n",
              "      <td>23452.283197</td>\n",
              "      <td>23328.168647</td>\n",
              "      <td>22898.342570</td>\n",
              "      <td>21570.486029</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.08</td>\n",
              "      <td>2.40</td>\n",
              "      <td>0.000352</td>\n",
              "      <td>-0.004944</td>\n",
              "      <td>3.69</td>\n",
              "      <td>4.33</td>\n",
              "      <td>-0.001837</td>\n",
              "      <td>0.002743</td>\n",
              "      <td>0.001065</td>\n",
              "      <td>0.001357</td>\n",
              "      <td>-0.004008</td>\n",
              "      <td>0.003395</td>\n",
              "      <td>-0.071742</td>\n",
              "      <td>0.001433</td>\n",
              "      <td>0.003589</td>\n",
              "      <td>0.000715</td>\n",
              "      <td>-0.001673</td>\n",
              "      <td>-0.000603</td>\n",
              "      <td>-0.007265</td>\n",
              "      <td>-0.002395</td>\n",
              "      <td>-0.004041</td>\n",
              "      <td>0.000984</td>\n",
              "      <td>0.002104</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000136</td>\n",
              "      <td>-0.000469</td>\n",
              "      <td>1.36</td>\n",
              "      <td>1.18</td>\n",
              "      <td>1.05</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.98</td>\n",
              "      <td>3.11</td>\n",
              "      <td>3.29</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.017964</td>\n",
              "      <td>0.009709</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>1.34</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-1.43</td>\n",
              "      <td>-1.07</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.72</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.83</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-14</th>\n",
              "      <td>23409.470703</td>\n",
              "      <td>-1.387911</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>-0.627237</td>\n",
              "      <td>0.137871</td>\n",
              "      <td>-0.137742</td>\n",
              "      <td>1.791640</td>\n",
              "      <td>23444.499107</td>\n",
              "      <td>23335.911700</td>\n",
              "      <td>22918.386810</td>\n",
              "      <td>21588.784384</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.37</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.38</td>\n",
              "      <td>-0.019376</td>\n",
              "      <td>-0.002621</td>\n",
              "      <td>3.66</td>\n",
              "      <td>4.31</td>\n",
              "      <td>0.000236</td>\n",
              "      <td>-0.000888</td>\n",
              "      <td>0.003538</td>\n",
              "      <td>-0.000105</td>\n",
              "      <td>-0.015118</td>\n",
              "      <td>0.006793</td>\n",
              "      <td>-0.058885</td>\n",
              "      <td>-0.001932</td>\n",
              "      <td>-0.006029</td>\n",
              "      <td>0.001430</td>\n",
              "      <td>0.005957</td>\n",
              "      <td>-0.007842</td>\n",
              "      <td>-0.004877</td>\n",
              "      <td>-0.000108</td>\n",
              "      <td>-0.003131</td>\n",
              "      <td>-0.002310</td>\n",
              "      <td>-0.001030</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002583</td>\n",
              "      <td>-0.002980</td>\n",
              "      <td>1.34</td>\n",
              "      <td>1.14</td>\n",
              "      <td>1.01</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.65</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.94</td>\n",
              "      <td>3.07</td>\n",
              "      <td>3.27</td>\n",
              "      <td>0.021898</td>\n",
              "      <td>-0.011765</td>\n",
              "      <td>-0.009615</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-1.50</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-1.64</td>\n",
              "      <td>-1.87</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>1.12</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.31</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>-2.05</td>\n",
              "      <td>0.67</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-15</th>\n",
              "      <td>23271.279297</td>\n",
              "      <td>3.612171</td>\n",
              "      <td>-0.005903</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-1.239552</td>\n",
              "      <td>-0.698658</td>\n",
              "      <td>-0.249391</td>\n",
              "      <td>0.490896</td>\n",
              "      <td>23413.004596</td>\n",
              "      <td>23329.756233</td>\n",
              "      <td>22932.225731</td>\n",
              "      <td>21605.525627</td>\n",
              "      <td>1.06</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.04</td>\n",
              "      <td>2.33</td>\n",
              "      <td>-0.007006</td>\n",
              "      <td>0.005963</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.28</td>\n",
              "      <td>0.002631</td>\n",
              "      <td>-0.001611</td>\n",
              "      <td>-0.000133</td>\n",
              "      <td>-0.000452</td>\n",
              "      <td>-0.013190</td>\n",
              "      <td>-0.008928</td>\n",
              "      <td>0.020112</td>\n",
              "      <td>-0.002796</td>\n",
              "      <td>0.009458</td>\n",
              "      <td>-0.012731</td>\n",
              "      <td>-0.005366</td>\n",
              "      <td>-0.012524</td>\n",
              "      <td>-0.002696</td>\n",
              "      <td>-0.005638</td>\n",
              "      <td>-0.004382</td>\n",
              "      <td>-0.005526</td>\n",
              "      <td>-0.010306</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004873</td>\n",
              "      <td>-0.004867</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.68</td>\n",
              "      <td>1.95</td>\n",
              "      <td>2.92</td>\n",
              "      <td>3.05</td>\n",
              "      <td>3.22</td>\n",
              "      <td>-0.007143</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.009709</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.55</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.99</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-1.74</td>\n",
              "      <td>0.03</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.01</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>-2.04</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1984 rows × 82 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Close     Volume       mom  ...  wheat-F   XAG   XAU\n",
              "Date                                           ...                     \n",
              "2009-12-31  10428.049805  -0.673377  0.000535  ...    -0.48  0.30  0.39\n",
              "2010-01-04  10583.959961  -0.673377  0.014951  ...     3.12  3.91  2.10\n",
              "2010-01-05  10572.019531  -0.673377 -0.001128  ...    -0.90  1.42 -0.12\n",
              "2010-01-06  10573.679688   0.515598  0.000157  ...     2.62  2.25  1.77\n",
              "2010-01-07  10606.860352   9.776045  0.003138  ...    -1.85  0.22 -0.58\n",
              "...                  ...        ...       ...  ...      ...   ...   ...\n",
              "2017-11-09  23461.939453   6.511740 -0.004304  ...     0.53 -0.26  0.32\n",
              "2017-11-10  23422.210938  -0.991838 -0.001693  ...     0.70 -0.71 -0.80\n",
              "2017-11-13  23439.699219 -65.347705  0.000747  ...    -1.85  0.83  0.16\n",
              "2017-11-14  23409.470703  -1.387911 -0.001290  ...     1.00  0.01  0.24\n",
              "2017-11-15  23271.279297   3.612171 -0.005903  ...    -2.04 -0.22 -0.11\n",
              "\n",
              "[1984 rows x 82 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "YaBp7jHSkM-V",
        "outputId": "b25fd495-fafe-4974-da85-a5d660fb09d7"
      },
      "source": [
        "data.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>mom</th>\n",
              "      <th>mom1</th>\n",
              "      <th>mom2</th>\n",
              "      <th>mom3</th>\n",
              "      <th>ROC_5</th>\n",
              "      <th>ROC_10</th>\n",
              "      <th>ROC_15</th>\n",
              "      <th>ROC_20</th>\n",
              "      <th>EMA_10</th>\n",
              "      <th>EMA_20</th>\n",
              "      <th>EMA_50</th>\n",
              "      <th>EMA_200</th>\n",
              "      <th>DTB4WK</th>\n",
              "      <th>DTB3</th>\n",
              "      <th>DTB6</th>\n",
              "      <th>DGS5</th>\n",
              "      <th>DGS10</th>\n",
              "      <th>Oil</th>\n",
              "      <th>Gold</th>\n",
              "      <th>DAAA</th>\n",
              "      <th>DBAA</th>\n",
              "      <th>GBP</th>\n",
              "      <th>JPY</th>\n",
              "      <th>CAD</th>\n",
              "      <th>CNY</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AMZN</th>\n",
              "      <th>GE</th>\n",
              "      <th>JNJ</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MSFT</th>\n",
              "      <th>WFC</th>\n",
              "      <th>XOM</th>\n",
              "      <th>FCHI</th>\n",
              "      <th>FTSE</th>\n",
              "      <th>GDAXI</th>\n",
              "      <th>GSPC</th>\n",
              "      <th>HSI</th>\n",
              "      <th>...</th>\n",
              "      <th>RUT</th>\n",
              "      <th>NYSE</th>\n",
              "      <th>TE1</th>\n",
              "      <th>TE2</th>\n",
              "      <th>TE3</th>\n",
              "      <th>TE5</th>\n",
              "      <th>TE6</th>\n",
              "      <th>DE1</th>\n",
              "      <th>DE2</th>\n",
              "      <th>DE4</th>\n",
              "      <th>DE5</th>\n",
              "      <th>DE6</th>\n",
              "      <th>CTB3M</th>\n",
              "      <th>CTB6M</th>\n",
              "      <th>CTB1Y</th>\n",
              "      <th>AUD</th>\n",
              "      <th>Brent</th>\n",
              "      <th>CAC-F</th>\n",
              "      <th>copper-F</th>\n",
              "      <th>WIT-oil</th>\n",
              "      <th>DAX-F</th>\n",
              "      <th>DJI-F</th>\n",
              "      <th>EUR</th>\n",
              "      <th>FTSE-F</th>\n",
              "      <th>gold-F</th>\n",
              "      <th>HSI-F</th>\n",
              "      <th>KOSPI-F</th>\n",
              "      <th>NASDAQ-F</th>\n",
              "      <th>GAS-F</th>\n",
              "      <th>Nikkei-F</th>\n",
              "      <th>NZD</th>\n",
              "      <th>silver-F</th>\n",
              "      <th>RUSSELL-F</th>\n",
              "      <th>S&amp;P-F</th>\n",
              "      <th>CHF</th>\n",
              "      <th>Dollar index-F</th>\n",
              "      <th>Dollar index</th>\n",
              "      <th>wheat-F</th>\n",
              "      <th>XAG</th>\n",
              "      <th>XAU</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>2009-12-31</th>\n",
              "      <td>10428.049805</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.000535</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.69</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.000274</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.33</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>0.000865</td>\n",
              "      <td>0.000829</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>0.000354</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.000194</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000367</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.000544</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000997</td>\n",
              "      <td>0.000517</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.65</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.33</td>\n",
              "      <td>6.35</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.48</td>\n",
              "      <td>-1.19</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.34</td>\n",
              "      <td>1.68</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-1.08</td>\n",
              "      <td>-1.00</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-04</th>\n",
              "      <td>10583.959961</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.18</td>\n",
              "      <td>2.65</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.026830</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.35</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.004222</td>\n",
              "      <td>-0.004467</td>\n",
              "      <td>-0.010644</td>\n",
              "      <td>-0.001991</td>\n",
              "      <td>0.015565</td>\n",
              "      <td>-0.004609</td>\n",
              "      <td>0.021150</td>\n",
              "      <td>0.004192</td>\n",
              "      <td>0.028318</td>\n",
              "      <td>0.015420</td>\n",
              "      <td>0.012227</td>\n",
              "      <td>0.014078</td>\n",
              "      <td>0.019724</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.016043</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.023521</td>\n",
              "      <td>0.019733</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.77</td>\n",
              "      <td>3.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.21</td>\n",
              "      <td>6.31</td>\n",
              "      <td>6.34</td>\n",
              "      <td>-0.100000</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>-0.014870</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.81</td>\n",
              "      <td>1.99</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.71</td>\n",
              "      <td>0.96</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.74</td>\n",
              "      <td>2.05</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.51</td>\n",
              "      <td>5.60</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.52</td>\n",
              "      <td>3.26</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.62</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>3.12</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-05</th>\n",
              "      <td>10572.019531</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.17</td>\n",
              "      <td>2.56</td>\n",
              "      <td>3.77</td>\n",
              "      <td>0.002699</td>\n",
              "      <td>0.001560</td>\n",
              "      <td>5.24</td>\n",
              "      <td>6.30</td>\n",
              "      <td>-0.007628</td>\n",
              "      <td>-0.009838</td>\n",
              "      <td>-0.001441</td>\n",
              "      <td>0.000015</td>\n",
              "      <td>0.001729</td>\n",
              "      <td>0.005900</td>\n",
              "      <td>0.005178</td>\n",
              "      <td>-0.011596</td>\n",
              "      <td>0.019370</td>\n",
              "      <td>0.000323</td>\n",
              "      <td>0.027452</td>\n",
              "      <td>0.003904</td>\n",
              "      <td>-0.000264</td>\n",
              "      <td>0.004036</td>\n",
              "      <td>-0.002718</td>\n",
              "      <td>0.003116</td>\n",
              "      <td>0.020909</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002515</td>\n",
              "      <td>0.003839</td>\n",
              "      <td>3.74</td>\n",
              "      <td>3.70</td>\n",
              "      <td>3.60</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.53</td>\n",
              "      <td>6.13</td>\n",
              "      <td>6.23</td>\n",
              "      <td>6.27</td>\n",
              "      <td>-0.055556</td>\n",
              "      <td>-0.073394</td>\n",
              "      <td>-0.033962</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.59</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.32</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.04</td>\n",
              "      <td>2.03</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-4.20</td>\n",
              "      <td>0.47</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>1.96</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.43</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.90</td>\n",
              "      <td>1.42</td>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-06</th>\n",
              "      <td>10573.679688</td>\n",
              "      <td>0.515598</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.60</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.016883</td>\n",
              "      <td>0.006009</td>\n",
              "      <td>5.30</td>\n",
              "      <td>6.34</td>\n",
              "      <td>0.002067</td>\n",
              "      <td>0.008418</td>\n",
              "      <td>-0.007311</td>\n",
              "      <td>0.000191</td>\n",
              "      <td>-0.015906</td>\n",
              "      <td>-0.018116</td>\n",
              "      <td>-0.005151</td>\n",
              "      <td>0.008134</td>\n",
              "      <td>0.005494</td>\n",
              "      <td>-0.006137</td>\n",
              "      <td>0.001425</td>\n",
              "      <td>0.008643</td>\n",
              "      <td>0.001186</td>\n",
              "      <td>0.001358</td>\n",
              "      <td>0.000410</td>\n",
              "      <td>0.000546</td>\n",
              "      <td>0.006153</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000846</td>\n",
              "      <td>0.003104</td>\n",
              "      <td>3.82</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.70</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.49</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>-0.117647</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.91</td>\n",
              "      <td>1.61</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.41</td>\n",
              "      <td>1.72</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.78</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>6.60</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.15</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.25</td>\n",
              "      <td>1.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-07</th>\n",
              "      <td>10606.860352</td>\n",
              "      <td>9.776045</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>2.62</td>\n",
              "      <td>3.85</td>\n",
              "      <td>-0.006256</td>\n",
              "      <td>0.000221</td>\n",
              "      <td>5.31</td>\n",
              "      <td>6.33</td>\n",
              "      <td>-0.005609</td>\n",
              "      <td>0.011196</td>\n",
              "      <td>0.002035</td>\n",
              "      <td>-0.000073</td>\n",
              "      <td>-0.001849</td>\n",
              "      <td>-0.017013</td>\n",
              "      <td>0.051780</td>\n",
              "      <td>-0.007137</td>\n",
              "      <td>0.019809</td>\n",
              "      <td>-0.010400</td>\n",
              "      <td>0.036286</td>\n",
              "      <td>-0.003142</td>\n",
              "      <td>0.001775</td>\n",
              "      <td>-0.000597</td>\n",
              "      <td>-0.002481</td>\n",
              "      <td>0.004001</td>\n",
              "      <td>-0.006567</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006301</td>\n",
              "      <td>0.002200</td>\n",
              "      <td>3.83</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.69</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.02</td>\n",
              "      <td>2.48</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.019802</td>\n",
              "      <td>0.007692</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-1.90</td>\n",
              "      <td>-0.63</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-1.27</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-3.38</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.72</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.54</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-08</th>\n",
              "      <td>10618.190430</td>\n",
              "      <td>-0.838081</td>\n",
              "      <td>0.001068</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>1.823357</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.57</td>\n",
              "      <td>3.83</td>\n",
              "      <td>0.001695</td>\n",
              "      <td>-0.003097</td>\n",
              "      <td>5.32</td>\n",
              "      <td>6.32</td>\n",
              "      <td>0.005656</td>\n",
              "      <td>-0.007817</td>\n",
              "      <td>-0.004062</td>\n",
              "      <td>-0.000044</td>\n",
              "      <td>0.006648</td>\n",
              "      <td>0.027077</td>\n",
              "      <td>0.021538</td>\n",
              "      <td>0.003438</td>\n",
              "      <td>-0.002456</td>\n",
              "      <td>0.006897</td>\n",
              "      <td>-0.009269</td>\n",
              "      <td>-0.004012</td>\n",
              "      <td>0.005054</td>\n",
              "      <td>0.001357</td>\n",
              "      <td>0.003032</td>\n",
              "      <td>0.002882</td>\n",
              "      <td>0.001226</td>\n",
              "      <td>...</td>\n",
              "      <td>0.004034</td>\n",
              "      <td>0.004249</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.68</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.00</td>\n",
              "      <td>2.49</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.27</td>\n",
              "      <td>6.30</td>\n",
              "      <td>-0.062500</td>\n",
              "      <td>-0.067961</td>\n",
              "      <td>-0.019084</td>\n",
              "      <td>0.88</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.53</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.45</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.43</td>\n",
              "      <td>0.67</td>\n",
              "      <td>-0.98</td>\n",
              "      <td>1.03</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.98</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>2.07</td>\n",
              "      <td>1.26</td>\n",
              "      <td>0.38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-11</th>\n",
              "      <td>10663.990234</td>\n",
              "      <td>-0.430942</td>\n",
              "      <td>0.004313</td>\n",
              "      <td>0.001068</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>0.756147</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.13</td>\n",
              "      <td>2.58</td>\n",
              "      <td>3.85</td>\n",
              "      <td>-0.002417</td>\n",
              "      <td>0.023297</td>\n",
              "      <td>5.35</td>\n",
              "      <td>6.32</td>\n",
              "      <td>0.005543</td>\n",
              "      <td>-0.006130</td>\n",
              "      <td>0.003884</td>\n",
              "      <td>-0.000147</td>\n",
              "      <td>-0.008822</td>\n",
              "      <td>-0.024041</td>\n",
              "      <td>0.009639</td>\n",
              "      <td>0.000156</td>\n",
              "      <td>-0.003357</td>\n",
              "      <td>-0.012720</td>\n",
              "      <td>-0.002079</td>\n",
              "      <td>0.011220</td>\n",
              "      <td>-0.000507</td>\n",
              "      <td>0.000705</td>\n",
              "      <td>0.000479</td>\n",
              "      <td>0.001747</td>\n",
              "      <td>0.005147</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000884</td>\n",
              "      <td>0.003192</td>\n",
              "      <td>3.84</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.72</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.97</td>\n",
              "      <td>2.47</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>-0.133333</td>\n",
              "      <td>-0.010417</td>\n",
              "      <td>0.003891</td>\n",
              "      <td>0.76</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>1.21</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.84</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-5.13</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>0.64</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-1.01</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>1.08</td>\n",
              "      <td>0.65</td>\n",
              "      <td>1.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-12</th>\n",
              "      <td>10627.259766</td>\n",
              "      <td>-6.158991</td>\n",
              "      <td>-0.003444</td>\n",
              "      <td>0.004313</td>\n",
              "      <td>0.001068</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.522514</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.14</td>\n",
              "      <td>2.49</td>\n",
              "      <td>3.74</td>\n",
              "      <td>-0.021202</td>\n",
              "      <td>-0.001518</td>\n",
              "      <td>5.25</td>\n",
              "      <td>6.22</td>\n",
              "      <td>0.002407</td>\n",
              "      <td>-0.010989</td>\n",
              "      <td>0.005223</td>\n",
              "      <td>0.000015</td>\n",
              "      <td>-0.011375</td>\n",
              "      <td>-0.022715</td>\n",
              "      <td>0.000597</td>\n",
              "      <td>0.005294</td>\n",
              "      <td>-0.023355</td>\n",
              "      <td>-0.006607</td>\n",
              "      <td>-0.025000</td>\n",
              "      <td>-0.004979</td>\n",
              "      <td>-0.010645</td>\n",
              "      <td>-0.007114</td>\n",
              "      <td>-0.016141</td>\n",
              "      <td>-0.009381</td>\n",
              "      <td>-0.003787</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.013183</td>\n",
              "      <td>-0.010552</td>\n",
              "      <td>3.72</td>\n",
              "      <td>3.69</td>\n",
              "      <td>3.60</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.97</td>\n",
              "      <td>2.48</td>\n",
              "      <td>6.08</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.20</td>\n",
              "      <td>0.076923</td>\n",
              "      <td>-0.031579</td>\n",
              "      <td>-0.034884</td>\n",
              "      <td>-1.20</td>\n",
              "      <td>-2.06</td>\n",
              "      <td>-1.04</td>\n",
              "      <td>-2.68</td>\n",
              "      <td>-2.10</td>\n",
              "      <td>-1.42</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-1.89</td>\n",
              "      <td>-1.10</td>\n",
              "      <td>0.27</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>2.51</td>\n",
              "      <td>1.23</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-2.36</td>\n",
              "      <td>-0.67</td>\n",
              "      <td>-0.74</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-6.33</td>\n",
              "      <td>-1.78</td>\n",
              "      <td>-2.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-13</th>\n",
              "      <td>10680.769531</td>\n",
              "      <td>-1.231957</td>\n",
              "      <td>0.005035</td>\n",
              "      <td>-0.003444</td>\n",
              "      <td>0.004313</td>\n",
              "      <td>0.001068</td>\n",
              "      <td>1.012796</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.55</td>\n",
              "      <td>3.80</td>\n",
              "      <td>-0.013987</td>\n",
              "      <td>-0.020847</td>\n",
              "      <td>5.32</td>\n",
              "      <td>6.30</td>\n",
              "      <td>0.008322</td>\n",
              "      <td>0.003876</td>\n",
              "      <td>-0.008083</td>\n",
              "      <td>0.000029</td>\n",
              "      <td>0.014106</td>\n",
              "      <td>0.013820</td>\n",
              "      <td>0.003578</td>\n",
              "      <td>0.006351</td>\n",
              "      <td>0.017475</td>\n",
              "      <td>0.009312</td>\n",
              "      <td>0.017806</td>\n",
              "      <td>-0.004003</td>\n",
              "      <td>0.000203</td>\n",
              "      <td>-0.004583</td>\n",
              "      <td>0.003389</td>\n",
              "      <td>0.008326</td>\n",
              "      <td>-0.025890</td>\n",
              "      <td>...</td>\n",
              "      <td>0.012683</td>\n",
              "      <td>0.008099</td>\n",
              "      <td>3.78</td>\n",
              "      <td>3.74</td>\n",
              "      <td>3.65</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.98</td>\n",
              "      <td>2.50</td>\n",
              "      <td>6.15</td>\n",
              "      <td>6.24</td>\n",
              "      <td>6.28</td>\n",
              "      <td>0.071429</td>\n",
              "      <td>0.054348</td>\n",
              "      <td>0.024096</td>\n",
              "      <td>0.43</td>\n",
              "      <td>-1.25</td>\n",
              "      <td>0.02</td>\n",
              "      <td>1.53</td>\n",
              "      <td>-1.41</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>0.66</td>\n",
              "      <td>-2.06</td>\n",
              "      <td>-1.68</td>\n",
              "      <td>0.91</td>\n",
              "      <td>2.54</td>\n",
              "      <td>-1.56</td>\n",
              "      <td>0.26</td>\n",
              "      <td>1.62</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.66</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.51</td>\n",
              "      <td>1.97</td>\n",
              "      <td>0.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-14</th>\n",
              "      <td>10710.549805</td>\n",
              "      <td>-0.361795</td>\n",
              "      <td>0.002788</td>\n",
              "      <td>0.005035</td>\n",
              "      <td>-0.003444</td>\n",
              "      <td>0.004313</td>\n",
              "      <td>0.977570</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.16875</td>\n",
              "      <td>10606.532910</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.14</td>\n",
              "      <td>2.51</td>\n",
              "      <td>3.76</td>\n",
              "      <td>-0.003892</td>\n",
              "      <td>0.009758</td>\n",
              "      <td>5.17</td>\n",
              "      <td>6.22</td>\n",
              "      <td>0.002941</td>\n",
              "      <td>-0.001816</td>\n",
              "      <td>-0.007179</td>\n",
              "      <td>0.000029</td>\n",
              "      <td>-0.005792</td>\n",
              "      <td>-0.013632</td>\n",
              "      <td>-0.007724</td>\n",
              "      <td>0.002001</td>\n",
              "      <td>0.009943</td>\n",
              "      <td>0.020099</td>\n",
              "      <td>0.014346</td>\n",
              "      <td>0.000144</td>\n",
              "      <td>0.003727</td>\n",
              "      <td>0.004513</td>\n",
              "      <td>0.004316</td>\n",
              "      <td>0.002426</td>\n",
              "      <td>-0.001455</td>\n",
              "      <td>...</td>\n",
              "      <td>0.004460</td>\n",
              "      <td>0.002474</td>\n",
              "      <td>3.74</td>\n",
              "      <td>3.71</td>\n",
              "      <td>3.62</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>1.05</td>\n",
              "      <td>2.46</td>\n",
              "      <td>6.08</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.20</td>\n",
              "      <td>-0.066667</td>\n",
              "      <td>-0.030928</td>\n",
              "      <td>-0.015686</td>\n",
              "      <td>0.82</td>\n",
              "      <td>-0.63</td>\n",
              "      <td>0.36</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>-0.33</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.33</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.55</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>1.14</td>\n",
              "      <td>0.31</td>\n",
              "      <td>-2.53</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.57</td>\n",
              "      <td>0.76</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>-1.49</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 82 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Close    Volume       mom  ...  wheat-F   XAG   XAU\n",
              "Date                                          ...                     \n",
              "2009-12-31  10428.049805 -0.673377  0.000535  ...    -0.48  0.30  0.39\n",
              "2010-01-04  10583.959961 -0.673377  0.014951  ...     3.12  3.91  2.10\n",
              "2010-01-05  10572.019531 -0.673377 -0.001128  ...    -0.90  1.42 -0.12\n",
              "2010-01-06  10573.679688  0.515598  0.000157  ...     2.62  2.25  1.77\n",
              "2010-01-07  10606.860352  9.776045  0.003138  ...    -1.85  0.22 -0.58\n",
              "2010-01-08  10618.190430 -0.838081  0.001068  ...     2.07  1.26  0.38\n",
              "2010-01-11  10663.990234 -0.430942  0.004313  ...     1.08  0.65  1.44\n",
              "2010-01-12  10627.259766 -6.158991 -0.003444  ...    -6.33 -1.78 -2.19\n",
              "2010-01-13  10680.769531 -1.231957  0.005035  ...    -0.51  1.97  0.98\n",
              "2010-01-14  10710.549805 -0.361795  0.002788  ...    -1.49  0.32  0.39\n",
              "\n",
              "[10 rows x 82 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 222
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Qwdflbh_krpM",
        "outputId": "6c20c0fa-a1cd-4a9f-bf05-2b6f53b0acd0"
      },
      "source": [
        "# Checking for NAN OR Missing Values\n",
        "data.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Close             0\n",
              "Volume            0\n",
              "mom               0\n",
              "mom1              0\n",
              "mom2              0\n",
              "                 ..\n",
              "Dollar index-F    0\n",
              "Dollar index      0\n",
              "wheat-F           0\n",
              "XAG               0\n",
              "XAU               0\n",
              "Length: 82, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 223
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "7q5DI1v3kvcB",
        "outputId": "1420fef8-45c8-4c05-e71d-d6a2b54337fc"
      },
      "source": [
        "# Visualizing The Data\n",
        "plt.figure(figsize=(12, 5), dpi=200)\n",
        "\n",
        "\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Prices')\n",
        "\n",
        "\n",
        "plt.plot(data['Close'], label='Close', color='red')\n",
        "\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2400x1000 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dclgje-NlRtp",
        "outputId": "1af2ca4f-8979-44ae-82b2-e642ecf41d61"
      },
      "source": [
        "# Splitting The Data Into Training, Testing Data\n",
        "training_data = data[data.index < '2016-04-20']\n",
        "testing_data = data[data.index >= '2016-04-20']\n",
        "\n",
        "training_data.shape, testing_data.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1585, 82), (399, 82))"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 667
        },
        "id": "8ZTz6TNqmF-u",
        "outputId": "c1a71dcc-1145-48df-fb79-6df12e6ad7da"
      },
      "source": [
        "training_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>mom</th>\n",
              "      <th>mom1</th>\n",
              "      <th>mom2</th>\n",
              "      <th>mom3</th>\n",
              "      <th>ROC_5</th>\n",
              "      <th>ROC_10</th>\n",
              "      <th>ROC_15</th>\n",
              "      <th>ROC_20</th>\n",
              "      <th>EMA_10</th>\n",
              "      <th>EMA_20</th>\n",
              "      <th>EMA_50</th>\n",
              "      <th>EMA_200</th>\n",
              "      <th>DTB4WK</th>\n",
              "      <th>DTB3</th>\n",
              "      <th>DTB6</th>\n",
              "      <th>DGS5</th>\n",
              "      <th>DGS10</th>\n",
              "      <th>Oil</th>\n",
              "      <th>Gold</th>\n",
              "      <th>DAAA</th>\n",
              "      <th>DBAA</th>\n",
              "      <th>GBP</th>\n",
              "      <th>JPY</th>\n",
              "      <th>CAD</th>\n",
              "      <th>CNY</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AMZN</th>\n",
              "      <th>GE</th>\n",
              "      <th>JNJ</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MSFT</th>\n",
              "      <th>WFC</th>\n",
              "      <th>XOM</th>\n",
              "      <th>FCHI</th>\n",
              "      <th>FTSE</th>\n",
              "      <th>GDAXI</th>\n",
              "      <th>GSPC</th>\n",
              "      <th>HSI</th>\n",
              "      <th>...</th>\n",
              "      <th>RUT</th>\n",
              "      <th>NYSE</th>\n",
              "      <th>TE1</th>\n",
              "      <th>TE2</th>\n",
              "      <th>TE3</th>\n",
              "      <th>TE5</th>\n",
              "      <th>TE6</th>\n",
              "      <th>DE1</th>\n",
              "      <th>DE2</th>\n",
              "      <th>DE4</th>\n",
              "      <th>DE5</th>\n",
              "      <th>DE6</th>\n",
              "      <th>CTB3M</th>\n",
              "      <th>CTB6M</th>\n",
              "      <th>CTB1Y</th>\n",
              "      <th>AUD</th>\n",
              "      <th>Brent</th>\n",
              "      <th>CAC-F</th>\n",
              "      <th>copper-F</th>\n",
              "      <th>WIT-oil</th>\n",
              "      <th>DAX-F</th>\n",
              "      <th>DJI-F</th>\n",
              "      <th>EUR</th>\n",
              "      <th>FTSE-F</th>\n",
              "      <th>gold-F</th>\n",
              "      <th>HSI-F</th>\n",
              "      <th>KOSPI-F</th>\n",
              "      <th>NASDAQ-F</th>\n",
              "      <th>GAS-F</th>\n",
              "      <th>Nikkei-F</th>\n",
              "      <th>NZD</th>\n",
              "      <th>silver-F</th>\n",
              "      <th>RUSSELL-F</th>\n",
              "      <th>S&amp;P-F</th>\n",
              "      <th>CHF</th>\n",
              "      <th>Dollar index-F</th>\n",
              "      <th>Dollar index</th>\n",
              "      <th>wheat-F</th>\n",
              "      <th>XAG</th>\n",
              "      <th>XAU</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>2009-12-31</th>\n",
              "      <td>10428.049805</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.000535</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.69</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.000274</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.33</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>0.000865</td>\n",
              "      <td>0.000829</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>0.000354</td>\n",
              "      <td>0.000258</td>\n",
              "      <td>0.000194</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000367</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.000544</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000997</td>\n",
              "      <td>0.000517</td>\n",
              "      <td>3.81</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.65</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.33</td>\n",
              "      <td>6.35</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.35</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.48</td>\n",
              "      <td>-1.19</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.34</td>\n",
              "      <td>1.68</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>0.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-1.08</td>\n",
              "      <td>-1.00</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-04</th>\n",
              "      <td>10583.959961</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.18</td>\n",
              "      <td>2.65</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.026830</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.35</td>\n",
              "      <td>6.39</td>\n",
              "      <td>-0.004222</td>\n",
              "      <td>-0.004467</td>\n",
              "      <td>-0.010644</td>\n",
              "      <td>-0.001991</td>\n",
              "      <td>0.015565</td>\n",
              "      <td>-0.004609</td>\n",
              "      <td>0.021150</td>\n",
              "      <td>0.004192</td>\n",
              "      <td>0.028318</td>\n",
              "      <td>0.015420</td>\n",
              "      <td>0.012227</td>\n",
              "      <td>0.014078</td>\n",
              "      <td>0.019724</td>\n",
              "      <td>0.000416</td>\n",
              "      <td>0.000847</td>\n",
              "      <td>0.016043</td>\n",
              "      <td>0.000394</td>\n",
              "      <td>...</td>\n",
              "      <td>0.023521</td>\n",
              "      <td>0.019733</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.77</td>\n",
              "      <td>3.67</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.54</td>\n",
              "      <td>6.21</td>\n",
              "      <td>6.31</td>\n",
              "      <td>6.34</td>\n",
              "      <td>-0.100000</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>-0.014870</td>\n",
              "      <td>1.73</td>\n",
              "      <td>2.81</td>\n",
              "      <td>1.99</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.71</td>\n",
              "      <td>0.96</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.61</td>\n",
              "      <td>1.74</td>\n",
              "      <td>2.05</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.51</td>\n",
              "      <td>5.60</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.52</td>\n",
              "      <td>3.26</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.62</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>3.12</td>\n",
              "      <td>3.91</td>\n",
              "      <td>2.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-05</th>\n",
              "      <td>10572.019531</td>\n",
              "      <td>-0.673377</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000540</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.17</td>\n",
              "      <td>2.56</td>\n",
              "      <td>3.77</td>\n",
              "      <td>0.002699</td>\n",
              "      <td>0.001560</td>\n",
              "      <td>5.24</td>\n",
              "      <td>6.30</td>\n",
              "      <td>-0.007628</td>\n",
              "      <td>-0.009838</td>\n",
              "      <td>-0.001441</td>\n",
              "      <td>0.000015</td>\n",
              "      <td>0.001729</td>\n",
              "      <td>0.005900</td>\n",
              "      <td>0.005178</td>\n",
              "      <td>-0.011596</td>\n",
              "      <td>0.019370</td>\n",
              "      <td>0.000323</td>\n",
              "      <td>0.027452</td>\n",
              "      <td>0.003904</td>\n",
              "      <td>-0.000264</td>\n",
              "      <td>0.004036</td>\n",
              "      <td>-0.002718</td>\n",
              "      <td>0.003116</td>\n",
              "      <td>0.020909</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002515</td>\n",
              "      <td>0.003839</td>\n",
              "      <td>3.74</td>\n",
              "      <td>3.70</td>\n",
              "      <td>3.60</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.06</td>\n",
              "      <td>2.53</td>\n",
              "      <td>6.13</td>\n",
              "      <td>6.23</td>\n",
              "      <td>6.27</td>\n",
              "      <td>-0.055556</td>\n",
              "      <td>-0.073394</td>\n",
              "      <td>-0.033962</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.59</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.32</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.31</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.04</td>\n",
              "      <td>2.03</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-4.20</td>\n",
              "      <td>0.47</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>1.96</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.43</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.90</td>\n",
              "      <td>1.42</td>\n",
              "      <td>-0.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-06</th>\n",
              "      <td>10573.679688</td>\n",
              "      <td>0.515598</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.000538</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.60</td>\n",
              "      <td>3.85</td>\n",
              "      <td>0.016883</td>\n",
              "      <td>0.006009</td>\n",
              "      <td>5.30</td>\n",
              "      <td>6.34</td>\n",
              "      <td>0.002067</td>\n",
              "      <td>0.008418</td>\n",
              "      <td>-0.007311</td>\n",
              "      <td>0.000191</td>\n",
              "      <td>-0.015906</td>\n",
              "      <td>-0.018116</td>\n",
              "      <td>-0.005151</td>\n",
              "      <td>0.008134</td>\n",
              "      <td>0.005494</td>\n",
              "      <td>-0.006137</td>\n",
              "      <td>0.001425</td>\n",
              "      <td>0.008643</td>\n",
              "      <td>0.001186</td>\n",
              "      <td>0.001358</td>\n",
              "      <td>0.000410</td>\n",
              "      <td>0.000546</td>\n",
              "      <td>0.006153</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000846</td>\n",
              "      <td>0.003104</td>\n",
              "      <td>3.82</td>\n",
              "      <td>3.79</td>\n",
              "      <td>3.70</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.12</td>\n",
              "      <td>1.04</td>\n",
              "      <td>2.49</td>\n",
              "      <td>6.19</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>-0.117647</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.015625</td>\n",
              "      <td>0.91</td>\n",
              "      <td>1.61</td>\n",
              "      <td>0.15</td>\n",
              "      <td>2.41</td>\n",
              "      <td>1.72</td>\n",
              "      <td>-0.01</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.16</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.79</td>\n",
              "      <td>0.78</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>6.60</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.15</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2.25</td>\n",
              "      <td>1.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-01-07</th>\n",
              "      <td>10606.860352</td>\n",
              "      <td>9.776045</td>\n",
              "      <td>0.003138</td>\n",
              "      <td>0.000157</td>\n",
              "      <td>-0.001128</td>\n",
              "      <td>0.014951</td>\n",
              "      <td>0.340396</td>\n",
              "      <td>0.596937</td>\n",
              "      <td>0.924413</td>\n",
              "      <td>1.168750</td>\n",
              "      <td>15933.258788</td>\n",
              "      <td>15911.369569</td>\n",
              "      <td>15986.229431</td>\n",
              "      <td>15822.214111</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.16</td>\n",
              "      <td>2.62</td>\n",
              "      <td>3.85</td>\n",
              "      <td>-0.006256</td>\n",
              "      <td>0.000221</td>\n",
              "      <td>5.31</td>\n",
              "      <td>6.33</td>\n",
              "      <td>-0.005609</td>\n",
              "      <td>0.011196</td>\n",
              "      <td>0.002035</td>\n",
              "      <td>-0.000073</td>\n",
              "      <td>-0.001849</td>\n",
              "      <td>-0.017013</td>\n",
              "      <td>0.051780</td>\n",
              "      <td>-0.007137</td>\n",
              "      <td>0.019809</td>\n",
              "      <td>-0.010400</td>\n",
              "      <td>0.036286</td>\n",
              "      <td>-0.003142</td>\n",
              "      <td>0.001775</td>\n",
              "      <td>-0.000597</td>\n",
              "      <td>-0.002481</td>\n",
              "      <td>0.004001</td>\n",
              "      <td>-0.006567</td>\n",
              "      <td>...</td>\n",
              "      <td>0.006301</td>\n",
              "      <td>0.002200</td>\n",
              "      <td>3.83</td>\n",
              "      <td>3.80</td>\n",
              "      <td>3.69</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.02</td>\n",
              "      <td>2.48</td>\n",
              "      <td>6.17</td>\n",
              "      <td>6.28</td>\n",
              "      <td>6.31</td>\n",
              "      <td>0.066667</td>\n",
              "      <td>0.019802</td>\n",
              "      <td>0.007692</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-1.90</td>\n",
              "      <td>-0.63</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-1.27</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-3.38</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.72</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.54</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.58</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>2016-04-13</th>\n",
              "      <td>17908.279297</td>\n",
              "      <td>-0.102800</td>\n",
              "      <td>0.010554</td>\n",
              "      <td>0.009389</td>\n",
              "      <td>-0.001169</td>\n",
              "      <td>0.001995</td>\n",
              "      <td>1.085053</td>\n",
              "      <td>1.081576</td>\n",
              "      <td>1.852454</td>\n",
              "      <td>3.806909</td>\n",
              "      <td>17673.862921</td>\n",
              "      <td>17547.543748</td>\n",
              "      <td>17229.665013</td>\n",
              "      <td>17155.070815</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.35</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.77</td>\n",
              "      <td>-0.009972</td>\n",
              "      <td>-0.007054</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.78</td>\n",
              "      <td>-0.005393</td>\n",
              "      <td>0.007180</td>\n",
              "      <td>0.004065</td>\n",
              "      <td>0.001983</td>\n",
              "      <td>0.014487</td>\n",
              "      <td>0.019315</td>\n",
              "      <td>0.005518</td>\n",
              "      <td>0.002464</td>\n",
              "      <td>0.042341</td>\n",
              "      <td>0.012809</td>\n",
              "      <td>0.026376</td>\n",
              "      <td>0.005691</td>\n",
              "      <td>0.033227</td>\n",
              "      <td>0.019303</td>\n",
              "      <td>0.027110</td>\n",
              "      <td>0.010040</td>\n",
              "      <td>0.031909</td>\n",
              "      <td>...</td>\n",
              "      <td>0.021905</td>\n",
              "      <td>0.011800</td>\n",
              "      <td>1.56</td>\n",
              "      <td>1.54</td>\n",
              "      <td>1.42</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.18</td>\n",
              "      <td>3.01</td>\n",
              "      <td>4.43</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4.57</td>\n",
              "      <td>0.058824</td>\n",
              "      <td>0.013514</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>-1.14</td>\n",
              "      <td>3.36</td>\n",
              "      <td>1.03</td>\n",
              "      <td>-0.97</td>\n",
              "      <td>2.39</td>\n",
              "      <td>1.08</td>\n",
              "      <td>-0.98</td>\n",
              "      <td>1.81</td>\n",
              "      <td>-1.00</td>\n",
              "      <td>3.64</td>\n",
              "      <td>0.04</td>\n",
              "      <td>1.29</td>\n",
              "      <td>1.60</td>\n",
              "      <td>3.08</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.64</td>\n",
              "      <td>2.22</td>\n",
              "      <td>0.99</td>\n",
              "      <td>1.21</td>\n",
              "      <td>0.87</td>\n",
              "      <td>0.83</td>\n",
              "      <td>2.37</td>\n",
              "      <td>0.19</td>\n",
              "      <td>-1.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-14</th>\n",
              "      <td>17926.429688</td>\n",
              "      <td>0.034493</td>\n",
              "      <td>0.001014</td>\n",
              "      <td>0.010554</td>\n",
              "      <td>0.009389</td>\n",
              "      <td>-0.001169</td>\n",
              "      <td>2.191709</td>\n",
              "      <td>1.364652</td>\n",
              "      <td>2.421584</td>\n",
              "      <td>3.466918</td>\n",
              "      <td>17719.784151</td>\n",
              "      <td>17583.628123</td>\n",
              "      <td>17256.989118</td>\n",
              "      <td>17162.746028</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.26</td>\n",
              "      <td>1.80</td>\n",
              "      <td>-0.005995</td>\n",
              "      <td>-0.009552</td>\n",
              "      <td>3.62</td>\n",
              "      <td>4.79</td>\n",
              "      <td>-0.003240</td>\n",
              "      <td>-0.000950</td>\n",
              "      <td>0.001646</td>\n",
              "      <td>0.000649</td>\n",
              "      <td>0.000535</td>\n",
              "      <td>0.009645</td>\n",
              "      <td>0.001291</td>\n",
              "      <td>-0.000273</td>\n",
              "      <td>0.012947</td>\n",
              "      <td>0.000181</td>\n",
              "      <td>-0.004895</td>\n",
              "      <td>0.007073</td>\n",
              "      <td>0.004721</td>\n",
              "      <td>0.000346</td>\n",
              "      <td>0.006737</td>\n",
              "      <td>0.000173</td>\n",
              "      <td>0.008465</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.001186</td>\n",
              "      <td>0.000071</td>\n",
              "      <td>1.59</td>\n",
              "      <td>1.58</td>\n",
              "      <td>1.44</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1.17</td>\n",
              "      <td>2.99</td>\n",
              "      <td>4.43</td>\n",
              "      <td>4.57</td>\n",
              "      <td>4.58</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>0.026667</td>\n",
              "      <td>0.032787</td>\n",
              "      <td>0.56</td>\n",
              "      <td>-0.77</td>\n",
              "      <td>0.48</td>\n",
              "      <td>0.18</td>\n",
              "      <td>-0.62</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.08</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>0.23</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>0.60</td>\n",
              "      <td>2.09</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>-3.24</td>\n",
              "      <td>2.92</td>\n",
              "      <td>-1.04</td>\n",
              "      <td>-0.94</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-1.24</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>-1.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-15</th>\n",
              "      <td>17897.460938</td>\n",
              "      <td>2.806720</td>\n",
              "      <td>-0.001616</td>\n",
              "      <td>0.001014</td>\n",
              "      <td>0.010554</td>\n",
              "      <td>0.009389</td>\n",
              "      <td>1.823410</td>\n",
              "      <td>0.588503</td>\n",
              "      <td>2.179358</td>\n",
              "      <td>2.379492</td>\n",
              "      <td>17752.089021</td>\n",
              "      <td>17613.516963</td>\n",
              "      <td>17282.105660</td>\n",
              "      <td>17170.056624</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.76</td>\n",
              "      <td>-0.025332</td>\n",
              "      <td>-0.005471</td>\n",
              "      <td>3.59</td>\n",
              "      <td>4.75</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>-0.020071</td>\n",
              "      <td>0.008280</td>\n",
              "      <td>0.000322</td>\n",
              "      <td>0.003095</td>\n",
              "      <td>-0.011503</td>\n",
              "      <td>0.005238</td>\n",
              "      <td>-0.011068</td>\n",
              "      <td>-0.005385</td>\n",
              "      <td>-0.003622</td>\n",
              "      <td>-0.003346</td>\n",
              "      <td>-0.004169</td>\n",
              "      <td>-0.000984</td>\n",
              "      <td>-0.001000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.002065</td>\n",
              "      <td>-0.000451</td>\n",
              "      <td>1.57</td>\n",
              "      <td>1.54</td>\n",
              "      <td>1.40</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1.16</td>\n",
              "      <td>2.99</td>\n",
              "      <td>4.39</td>\n",
              "      <td>4.53</td>\n",
              "      <td>4.56</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.038961</td>\n",
              "      <td>-0.031746</td>\n",
              "      <td>0.36</td>\n",
              "      <td>-1.69</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.88</td>\n",
              "      <td>-2.75</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.13</td>\n",
              "      <td>-0.30</td>\n",
              "      <td>-0.92</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-3.45</td>\n",
              "      <td>-0.83</td>\n",
              "      <td>1.08</td>\n",
              "      <td>0.87</td>\n",
              "      <td>0.31</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.07</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-18</th>\n",
              "      <td>18004.160156</td>\n",
              "      <td>-0.734593</td>\n",
              "      <td>0.005962</td>\n",
              "      <td>-0.001616</td>\n",
              "      <td>0.001014</td>\n",
              "      <td>0.010554</td>\n",
              "      <td>2.550351</td>\n",
              "      <td>1.506231</td>\n",
              "      <td>2.673277</td>\n",
              "      <td>2.282993</td>\n",
              "      <td>17797.920137</td>\n",
              "      <td>17650.721076</td>\n",
              "      <td>17310.421523</td>\n",
              "      <td>17178.356162</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.35</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.78</td>\n",
              "      <td>-0.016337</td>\n",
              "      <td>0.005867</td>\n",
              "      <td>3.61</td>\n",
              "      <td>4.77</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>-0.021575</td>\n",
              "      <td>0.015114</td>\n",
              "      <td>0.000967</td>\n",
              "      <td>0.006807</td>\n",
              "      <td>0.006465</td>\n",
              "      <td>0.014555</td>\n",
              "      <td>0.012228</td>\n",
              "      <td>0.009533</td>\n",
              "      <td>0.002596</td>\n",
              "      <td>0.001529</td>\n",
              "      <td>0.006839</td>\n",
              "      <td>0.006541</td>\n",
              "      <td>-0.007270</td>\n",
              "      <td>...</td>\n",
              "      <td>0.007392</td>\n",
              "      <td>0.006698</td>\n",
              "      <td>1.63</td>\n",
              "      <td>1.56</td>\n",
              "      <td>1.43</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1.16</td>\n",
              "      <td>2.99</td>\n",
              "      <td>4.42</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4.62</td>\n",
              "      <td>-0.054054</td>\n",
              "      <td>0.013514</td>\n",
              "      <td>0.016393</td>\n",
              "      <td>0.34</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-1.52</td>\n",
              "      <td>0.56</td>\n",
              "      <td>-1.44</td>\n",
              "      <td>0.80</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.13</td>\n",
              "      <td>1.59</td>\n",
              "      <td>-0.82</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>0.18</td>\n",
              "      <td>2.00</td>\n",
              "      <td>-2.63</td>\n",
              "      <td>0.40</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.57</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>2.66</td>\n",
              "      <td>-0.06</td>\n",
              "      <td>-0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-19</th>\n",
              "      <td>18053.599609</td>\n",
              "      <td>-0.367198</td>\n",
              "      <td>0.002746</td>\n",
              "      <td>0.005962</td>\n",
              "      <td>-0.001616</td>\n",
              "      <td>0.001014</td>\n",
              "      <td>1.875430</td>\n",
              "      <td>2.557923</td>\n",
              "      <td>2.384663</td>\n",
              "      <td>2.438344</td>\n",
              "      <td>17844.407314</td>\n",
              "      <td>17689.090461</td>\n",
              "      <td>17339.565761</td>\n",
              "      <td>17187.065052</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.26</td>\n",
              "      <td>1.79</td>\n",
              "      <td>0.028686</td>\n",
              "      <td>0.017095</td>\n",
              "      <td>3.52</td>\n",
              "      <td>4.75</td>\n",
              "      <td>0.006978</td>\n",
              "      <td>0.001531</td>\n",
              "      <td>-0.005717</td>\n",
              "      <td>-0.002645</td>\n",
              "      <td>-0.005303</td>\n",
              "      <td>-0.011726</td>\n",
              "      <td>0.002898</td>\n",
              "      <td>0.015776</td>\n",
              "      <td>0.016862</td>\n",
              "      <td>-0.001240</td>\n",
              "      <td>0.021294</td>\n",
              "      <td>0.005013</td>\n",
              "      <td>0.013233</td>\n",
              "      <td>0.008169</td>\n",
              "      <td>0.022655</td>\n",
              "      <td>0.003084</td>\n",
              "      <td>0.012982</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000834</td>\n",
              "      <td>0.008861</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.58</td>\n",
              "      <td>1.43</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.18</td>\n",
              "      <td>1.23</td>\n",
              "      <td>2.96</td>\n",
              "      <td>4.39</td>\n",
              "      <td>4.54</td>\n",
              "      <td>4.57</td>\n",
              "      <td>0.028571</td>\n",
              "      <td>0.026667</td>\n",
              "      <td>0.016129</td>\n",
              "      <td>0.81</td>\n",
              "      <td>2.61</td>\n",
              "      <td>1.43</td>\n",
              "      <td>2.73</td>\n",
              "      <td>3.27</td>\n",
              "      <td>2.11</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.82</td>\n",
              "      <td>1.61</td>\n",
              "      <td>1.26</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>7.63</td>\n",
              "      <td>3.37</td>\n",
              "      <td>1.35</td>\n",
              "      <td>4.45</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.34</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.54</td>\n",
              "      <td>-0.54</td>\n",
              "      <td>2.75</td>\n",
              "      <td>4.37</td>\n",
              "      <td>1.54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1585 rows × 82 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Close    Volume       mom  ...  wheat-F   XAG   XAU\n",
              "Date                                          ...                     \n",
              "2009-12-31  10428.049805 -0.673377  0.000535  ...    -0.48  0.30  0.39\n",
              "2010-01-04  10583.959961 -0.673377  0.014951  ...     3.12  3.91  2.10\n",
              "2010-01-05  10572.019531 -0.673377 -0.001128  ...    -0.90  1.42 -0.12\n",
              "2010-01-06  10573.679688  0.515598  0.000157  ...     2.62  2.25  1.77\n",
              "2010-01-07  10606.860352  9.776045  0.003138  ...    -1.85  0.22 -0.58\n",
              "...                  ...       ...       ...  ...      ...   ...   ...\n",
              "2016-04-13  17908.279297 -0.102800  0.010554  ...     2.37  0.19 -1.02\n",
              "2016-04-14  17926.429688  0.034493  0.001014  ...    -1.24 -0.37 -1.27\n",
              "2016-04-15  17897.460938  2.806720 -0.001616  ...     0.38  0.50  0.54\n",
              "2016-04-18  18004.160156 -0.734593  0.005962  ...     2.66 -0.06 -0.20\n",
              "2016-04-19  18053.599609 -0.367198  0.002746  ...     2.75  4.37  1.54\n",
              "\n",
              "[1585 rows x 82 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 226
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 667
        },
        "id": "IP_syUaLl9GH",
        "outputId": "abfe8af4-b66c-4a65-ff93-1712b2d7c495"
      },
      "source": [
        "testing_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\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>Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>mom</th>\n",
              "      <th>mom1</th>\n",
              "      <th>mom2</th>\n",
              "      <th>mom3</th>\n",
              "      <th>ROC_5</th>\n",
              "      <th>ROC_10</th>\n",
              "      <th>ROC_15</th>\n",
              "      <th>ROC_20</th>\n",
              "      <th>EMA_10</th>\n",
              "      <th>EMA_20</th>\n",
              "      <th>EMA_50</th>\n",
              "      <th>EMA_200</th>\n",
              "      <th>DTB4WK</th>\n",
              "      <th>DTB3</th>\n",
              "      <th>DTB6</th>\n",
              "      <th>DGS5</th>\n",
              "      <th>DGS10</th>\n",
              "      <th>Oil</th>\n",
              "      <th>Gold</th>\n",
              "      <th>DAAA</th>\n",
              "      <th>DBAA</th>\n",
              "      <th>GBP</th>\n",
              "      <th>JPY</th>\n",
              "      <th>CAD</th>\n",
              "      <th>CNY</th>\n",
              "      <th>AAPL</th>\n",
              "      <th>AMZN</th>\n",
              "      <th>GE</th>\n",
              "      <th>JNJ</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MSFT</th>\n",
              "      <th>WFC</th>\n",
              "      <th>XOM</th>\n",
              "      <th>FCHI</th>\n",
              "      <th>FTSE</th>\n",
              "      <th>GDAXI</th>\n",
              "      <th>GSPC</th>\n",
              "      <th>HSI</th>\n",
              "      <th>...</th>\n",
              "      <th>RUT</th>\n",
              "      <th>NYSE</th>\n",
              "      <th>TE1</th>\n",
              "      <th>TE2</th>\n",
              "      <th>TE3</th>\n",
              "      <th>TE5</th>\n",
              "      <th>TE6</th>\n",
              "      <th>DE1</th>\n",
              "      <th>DE2</th>\n",
              "      <th>DE4</th>\n",
              "      <th>DE5</th>\n",
              "      <th>DE6</th>\n",
              "      <th>CTB3M</th>\n",
              "      <th>CTB6M</th>\n",
              "      <th>CTB1Y</th>\n",
              "      <th>AUD</th>\n",
              "      <th>Brent</th>\n",
              "      <th>CAC-F</th>\n",
              "      <th>copper-F</th>\n",
              "      <th>WIT-oil</th>\n",
              "      <th>DAX-F</th>\n",
              "      <th>DJI-F</th>\n",
              "      <th>EUR</th>\n",
              "      <th>FTSE-F</th>\n",
              "      <th>gold-F</th>\n",
              "      <th>HSI-F</th>\n",
              "      <th>KOSPI-F</th>\n",
              "      <th>NASDAQ-F</th>\n",
              "      <th>GAS-F</th>\n",
              "      <th>Nikkei-F</th>\n",
              "      <th>NZD</th>\n",
              "      <th>silver-F</th>\n",
              "      <th>RUSSELL-F</th>\n",
              "      <th>S&amp;P-F</th>\n",
              "      <th>CHF</th>\n",
              "      <th>Dollar index-F</th>\n",
              "      <th>Dollar index</th>\n",
              "      <th>wheat-F</th>\n",
              "      <th>XAG</th>\n",
              "      <th>XAU</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>2016-04-20</th>\n",
              "      <td>18096.269531</td>\n",
              "      <td>-23.600606</td>\n",
              "      <td>0.002364</td>\n",
              "      <td>0.002746</td>\n",
              "      <td>0.005962</td>\n",
              "      <td>-0.001616</td>\n",
              "      <td>1.049739</td>\n",
              "      <td>2.146182</td>\n",
              "      <td>2.142669</td>\n",
              "      <td>2.921639</td>\n",
              "      <td>17890.200444</td>\n",
              "      <td>17727.869420</td>\n",
              "      <td>17369.240419</td>\n",
              "      <td>17196.111863</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.35</td>\n",
              "      <td>1.32</td>\n",
              "      <td>1.85</td>\n",
              "      <td>0.045010</td>\n",
              "      <td>-0.002708</td>\n",
              "      <td>3.57</td>\n",
              "      <td>4.78</td>\n",
              "      <td>-0.003513</td>\n",
              "      <td>0.005474</td>\n",
              "      <td>-0.003993</td>\n",
              "      <td>0.001970</td>\n",
              "      <td>0.002058</td>\n",
              "      <td>0.008106</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.007987</td>\n",
              "      <td>0.014529</td>\n",
              "      <td>-0.014187</td>\n",
              "      <td>0.011427</td>\n",
              "      <td>0.006844</td>\n",
              "      <td>0.005571</td>\n",
              "      <td>0.000765</td>\n",
              "      <td>0.006928</td>\n",
              "      <td>0.000762</td>\n",
              "      <td>-0.009325</td>\n",
              "      <td>...</td>\n",
              "      <td>0.001807</td>\n",
              "      <td>0.000997</td>\n",
              "      <td>1.67</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.50</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1.21</td>\n",
              "      <td>2.93</td>\n",
              "      <td>4.43</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4.60</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.038961</td>\n",
              "      <td>0.047619</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>4.02</td>\n",
              "      <td>0.57</td>\n",
              "      <td>0.85</td>\n",
              "      <td>3.77</td>\n",
              "      <td>0.89</td>\n",
              "      <td>0.42</td>\n",
              "      <td>-0.54</td>\n",
              "      <td>0.21</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.76</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.91</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.94</td>\n",
              "      <td>0.94</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1.06</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.54</td>\n",
              "      <td>3.60</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-21</th>\n",
              "      <td>17982.519531</td>\n",
              "      <td>-1.033994</td>\n",
              "      <td>-0.006286</td>\n",
              "      <td>0.002364</td>\n",
              "      <td>0.002746</td>\n",
              "      <td>0.005962</td>\n",
              "      <td>0.312889</td>\n",
              "      <td>2.511456</td>\n",
              "      <td>1.681810</td>\n",
              "      <td>2.742050</td>\n",
              "      <td>17906.985733</td>\n",
              "      <td>17752.121811</td>\n",
              "      <td>17393.290580</td>\n",
              "      <td>17203.936815</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.35</td>\n",
              "      <td>1.88</td>\n",
              "      <td>0.010768</td>\n",
              "      <td>-0.002196</td>\n",
              "      <td>3.57</td>\n",
              "      <td>4.79</td>\n",
              "      <td>-0.001117</td>\n",
              "      <td>-0.003651</td>\n",
              "      <td>0.006231</td>\n",
              "      <td>0.001718</td>\n",
              "      <td>-0.010828</td>\n",
              "      <td>-0.003144</td>\n",
              "      <td>-0.005457</td>\n",
              "      <td>-0.000088</td>\n",
              "      <td>-0.009963</td>\n",
              "      <td>0.003418</td>\n",
              "      <td>-0.007929</td>\n",
              "      <td>-0.000115</td>\n",
              "      <td>-0.001980</td>\n",
              "      <td>-0.004508</td>\n",
              "      <td>0.001386</td>\n",
              "      <td>-0.005194</td>\n",
              "      <td>0.018174</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.005708</td>\n",
              "      <td>-0.006931</td>\n",
              "      <td>1.69</td>\n",
              "      <td>1.65</td>\n",
              "      <td>1.52</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1.22</td>\n",
              "      <td>2.91</td>\n",
              "      <td>4.43</td>\n",
              "      <td>4.56</td>\n",
              "      <td>4.60</td>\n",
              "      <td>0.027778</td>\n",
              "      <td>0.025000</td>\n",
              "      <td>0.022727</td>\n",
              "      <td>-0.72</td>\n",
              "      <td>-2.77</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>0.45</td>\n",
              "      <td>1.29</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-0.77</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>1.52</td>\n",
              "      <td>0.79</td>\n",
              "      <td>-0.84</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>3.20</td>\n",
              "      <td>-0.95</td>\n",
              "      <td>1.41</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-1.42</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-22</th>\n",
              "      <td>18003.750000</td>\n",
              "      <td>-15.300853</td>\n",
              "      <td>0.001181</td>\n",
              "      <td>-0.006286</td>\n",
              "      <td>0.002364</td>\n",
              "      <td>0.002746</td>\n",
              "      <td>0.593878</td>\n",
              "      <td>2.428116</td>\n",
              "      <td>1.185876</td>\n",
              "      <td>2.786179</td>\n",
              "      <td>17924.579236</td>\n",
              "      <td>17776.086401</td>\n",
              "      <td>17417.230165</td>\n",
              "      <td>17211.895155</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.37</td>\n",
              "      <td>1.37</td>\n",
              "      <td>1.89</td>\n",
              "      <td>-0.009727</td>\n",
              "      <td>-0.004803</td>\n",
              "      <td>3.59</td>\n",
              "      <td>4.78</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>-0.002737</td>\n",
              "      <td>-0.016640</td>\n",
              "      <td>-0.007101</td>\n",
              "      <td>-0.002201</td>\n",
              "      <td>0.005818</td>\n",
              "      <td>-0.071710</td>\n",
              "      <td>0.011389</td>\n",
              "      <td>0.008526</td>\n",
              "      <td>-0.002874</td>\n",
              "      <td>-0.011126</td>\n",
              "      <td>-0.005964</td>\n",
              "      <td>0.000048</td>\n",
              "      <td>-0.007178</td>\n",
              "      <td>...</td>\n",
              "      <td>0.009615</td>\n",
              "      <td>0.005374</td>\n",
              "      <td>1.70</td>\n",
              "      <td>1.66</td>\n",
              "      <td>1.52</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.18</td>\n",
              "      <td>1.19</td>\n",
              "      <td>2.89</td>\n",
              "      <td>4.41</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4.59</td>\n",
              "      <td>0.027027</td>\n",
              "      <td>0.024390</td>\n",
              "      <td>0.014815</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>1.30</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.75</td>\n",
              "      <td>1.27</td>\n",
              "      <td>-0.84</td>\n",
              "      <td>0.10</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-1.43</td>\n",
              "      <td>-3.28</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>3.48</td>\n",
              "      <td>0.92</td>\n",
              "      <td>-0.85</td>\n",
              "      <td>-1.11</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.55</td>\n",
              "      <td>-5.77</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-1.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-25</th>\n",
              "      <td>17977.240234</td>\n",
              "      <td>-1.198861</td>\n",
              "      <td>-0.001472</td>\n",
              "      <td>0.001181</td>\n",
              "      <td>-0.006286</td>\n",
              "      <td>0.002364</td>\n",
              "      <td>-0.149521</td>\n",
              "      <td>2.397017</td>\n",
              "      <td>1.354458</td>\n",
              "      <td>2.519759</td>\n",
              "      <td>17934.153963</td>\n",
              "      <td>17795.243909</td>\n",
              "      <td>17439.191344</td>\n",
              "      <td>17219.510529</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.40</td>\n",
              "      <td>1.38</td>\n",
              "      <td>1.91</td>\n",
              "      <td>-0.025491</td>\n",
              "      <td>-0.003499</td>\n",
              "      <td>3.62</td>\n",
              "      <td>4.79</td>\n",
              "      <td>-0.000106</td>\n",
              "      <td>0.000117</td>\n",
              "      <td>-0.000084</td>\n",
              "      <td>-0.000016</td>\n",
              "      <td>-0.005677</td>\n",
              "      <td>0.009186</td>\n",
              "      <td>-0.002601</td>\n",
              "      <td>0.001677</td>\n",
              "      <td>-0.005784</td>\n",
              "      <td>0.006373</td>\n",
              "      <td>-0.002173</td>\n",
              "      <td>-0.002285</td>\n",
              "      <td>-0.005151</td>\n",
              "      <td>-0.007844</td>\n",
              "      <td>-0.007629</td>\n",
              "      <td>-0.001812</td>\n",
              "      <td>-0.007574</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.007491</td>\n",
              "      <td>-0.004314</td>\n",
              "      <td>1.75</td>\n",
              "      <td>1.66</td>\n",
              "      <td>1.51</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.24</td>\n",
              "      <td>1.17</td>\n",
              "      <td>2.88</td>\n",
              "      <td>4.39</td>\n",
              "      <td>4.54</td>\n",
              "      <td>4.63</td>\n",
              "      <td>0.052632</td>\n",
              "      <td>0.011905</td>\n",
              "      <td>0.007299</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-1.40</td>\n",
              "      <td>-0.51</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-2.49</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.30</td>\n",
              "      <td>-0.65</td>\n",
              "      <td>2.55</td>\n",
              "      <td>-0.88</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-3.60</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-0.78</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>2.03</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-04-26</th>\n",
              "      <td>17990.320313</td>\n",
              "      <td>-0.425596</td>\n",
              "      <td>0.000728</td>\n",
              "      <td>-0.001472</td>\n",
              "      <td>0.001181</td>\n",
              "      <td>-0.006286</td>\n",
              "      <td>-0.350508</td>\n",
              "      <td>1.518348</td>\n",
              "      <td>2.198449</td>\n",
              "      <td>2.025797</td>\n",
              "      <td>17944.366026</td>\n",
              "      <td>17813.822614</td>\n",
              "      <td>17460.804245</td>\n",
              "      <td>17227.180278</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.42</td>\n",
              "      <td>1.40</td>\n",
              "      <td>1.94</td>\n",
              "      <td>0.020398</td>\n",
              "      <td>0.002260</td>\n",
              "      <td>3.65</td>\n",
              "      <td>4.79</td>\n",
              "      <td>0.005977</td>\n",
              "      <td>0.000846</td>\n",
              "      <td>-0.005286</td>\n",
              "      <td>0.000077</td>\n",
              "      <td>-0.006947</td>\n",
              "      <td>-0.014883</td>\n",
              "      <td>0.007171</td>\n",
              "      <td>-0.005286</td>\n",
              "      <td>0.005189</td>\n",
              "      <td>-0.012857</td>\n",
              "      <td>0.008117</td>\n",
              "      <td>0.003435</td>\n",
              "      <td>-0.002846</td>\n",
              "      <td>0.003769</td>\n",
              "      <td>-0.003377</td>\n",
              "      <td>0.001873</td>\n",
              "      <td>0.004827</td>\n",
              "      <td>...</td>\n",
              "      <td>0.011097</td>\n",
              "      <td>0.005440</td>\n",
              "      <td>1.75</td>\n",
              "      <td>1.70</td>\n",
              "      <td>1.52</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.23</td>\n",
              "      <td>1.14</td>\n",
              "      <td>2.85</td>\n",
              "      <td>4.37</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4.60</td>\n",
              "      <td>0.075000</td>\n",
              "      <td>0.011765</td>\n",
              "      <td>0.014493</td>\n",
              "      <td>0.43</td>\n",
              "      <td>2.83</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>3.28</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-1.50</td>\n",
              "      <td>-0.86</td>\n",
              "      <td>0.69</td>\n",
              "      <td>0.59</td>\n",
              "      <td>1.17</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>2.41</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.45</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>2017-11-09</th>\n",
              "      <td>23461.939453</td>\n",
              "      <td>6.511740</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>0.000392</td>\n",
              "      <td>-0.230990</td>\n",
              "      <td>0.261016</td>\n",
              "      <td>1.290420</td>\n",
              "      <td>2.718486</td>\n",
              "      <td>23462.383792</td>\n",
              "      <td>23305.293603</td>\n",
              "      <td>22853.962112</td>\n",
              "      <td>21532.900862</td>\n",
              "      <td>1.05</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.33</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.33</td>\n",
              "      <td>0.005984</td>\n",
              "      <td>0.000623</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.26</td>\n",
              "      <td>-0.004485</td>\n",
              "      <td>0.001459</td>\n",
              "      <td>-0.002633</td>\n",
              "      <td>-0.001988</td>\n",
              "      <td>-0.002043</td>\n",
              "      <td>-0.003310</td>\n",
              "      <td>-0.006461</td>\n",
              "      <td>-0.006864</td>\n",
              "      <td>-0.000102</td>\n",
              "      <td>-0.005558</td>\n",
              "      <td>-0.004792</td>\n",
              "      <td>0.005990</td>\n",
              "      <td>-0.011639</td>\n",
              "      <td>-0.006056</td>\n",
              "      <td>-0.014935</td>\n",
              "      <td>-0.003762</td>\n",
              "      <td>0.007921</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004528</td>\n",
              "      <td>-0.003638</td>\n",
              "      <td>1.28</td>\n",
              "      <td>1.11</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.66</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.93</td>\n",
              "      <td>3.04</td>\n",
              "      <td>3.21</td>\n",
              "      <td>0.007407</td>\n",
              "      <td>-0.012121</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.69</td>\n",
              "      <td>-1.17</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>0.63</td>\n",
              "      <td>-1.42</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.61</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>0.79</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.62</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.44</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>0.53</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-10</th>\n",
              "      <td>23422.210938</td>\n",
              "      <td>-0.991838</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.000374</td>\n",
              "      <td>-0.496952</td>\n",
              "      <td>-0.051116</td>\n",
              "      <td>0.401138</td>\n",
              "      <td>2.406860</td>\n",
              "      <td>23455.079637</td>\n",
              "      <td>23316.428587</td>\n",
              "      <td>22876.246380</td>\n",
              "      <td>21551.699967</td>\n",
              "      <td>1.03</td>\n",
              "      <td>1.21</td>\n",
              "      <td>1.34</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.40</td>\n",
              "      <td>-0.007173</td>\n",
              "      <td>-0.000389</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.002392</td>\n",
              "      <td>-0.004845</td>\n",
              "      <td>-0.003889</td>\n",
              "      <td>0.000558</td>\n",
              "      <td>-0.006880</td>\n",
              "      <td>-0.003348</td>\n",
              "      <td>0.025013</td>\n",
              "      <td>-0.005629</td>\n",
              "      <td>-0.001229</td>\n",
              "      <td>-0.002616</td>\n",
              "      <td>-0.003519</td>\n",
              "      <td>-0.012266</td>\n",
              "      <td>-0.004998</td>\n",
              "      <td>-0.006828</td>\n",
              "      <td>-0.004179</td>\n",
              "      <td>-0.000898</td>\n",
              "      <td>-0.000537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000169</td>\n",
              "      <td>-0.001383</td>\n",
              "      <td>1.37</td>\n",
              "      <td>1.19</td>\n",
              "      <td>1.06</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-2.40</td>\n",
              "      <td>-1.34</td>\n",
              "      <td>-1.21</td>\n",
              "      <td>-1.03</td>\n",
              "      <td>0.007353</td>\n",
              "      <td>0.024540</td>\n",
              "      <td>0.024876</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.75</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-1.02</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-1.66</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.18</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-13</th>\n",
              "      <td>23439.699219</td>\n",
              "      <td>-65.347705</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>-0.461690</td>\n",
              "      <td>0.389567</td>\n",
              "      <td>0.712119</td>\n",
              "      <td>2.102797</td>\n",
              "      <td>23452.283197</td>\n",
              "      <td>23328.168647</td>\n",
              "      <td>22898.342570</td>\n",
              "      <td>21570.486029</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.22</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.08</td>\n",
              "      <td>2.40</td>\n",
              "      <td>0.000352</td>\n",
              "      <td>-0.004944</td>\n",
              "      <td>3.69</td>\n",
              "      <td>4.33</td>\n",
              "      <td>-0.001837</td>\n",
              "      <td>0.002743</td>\n",
              "      <td>0.001065</td>\n",
              "      <td>0.001357</td>\n",
              "      <td>-0.004008</td>\n",
              "      <td>0.003395</td>\n",
              "      <td>-0.071742</td>\n",
              "      <td>0.001433</td>\n",
              "      <td>0.003589</td>\n",
              "      <td>0.000715</td>\n",
              "      <td>-0.001673</td>\n",
              "      <td>-0.000603</td>\n",
              "      <td>-0.007265</td>\n",
              "      <td>-0.002395</td>\n",
              "      <td>-0.004041</td>\n",
              "      <td>0.000984</td>\n",
              "      <td>0.002104</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000136</td>\n",
              "      <td>-0.000469</td>\n",
              "      <td>1.36</td>\n",
              "      <td>1.18</td>\n",
              "      <td>1.05</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.64</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.98</td>\n",
              "      <td>3.11</td>\n",
              "      <td>3.29</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.017964</td>\n",
              "      <td>0.009709</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.57</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>1.34</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-1.43</td>\n",
              "      <td>-1.07</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.72</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-1.85</td>\n",
              "      <td>0.83</td>\n",
              "      <td>0.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-14</th>\n",
              "      <td>23409.470703</td>\n",
              "      <td>-1.387911</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-0.004304</td>\n",
              "      <td>-0.627237</td>\n",
              "      <td>0.137871</td>\n",
              "      <td>-0.137742</td>\n",
              "      <td>1.791640</td>\n",
              "      <td>23444.499107</td>\n",
              "      <td>23335.911700</td>\n",
              "      <td>22918.386810</td>\n",
              "      <td>21588.784384</td>\n",
              "      <td>1.04</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.37</td>\n",
              "      <td>2.06</td>\n",
              "      <td>2.38</td>\n",
              "      <td>-0.019376</td>\n",
              "      <td>-0.002621</td>\n",
              "      <td>3.66</td>\n",
              "      <td>4.31</td>\n",
              "      <td>0.000236</td>\n",
              "      <td>-0.000888</td>\n",
              "      <td>0.003538</td>\n",
              "      <td>-0.000105</td>\n",
              "      <td>-0.015118</td>\n",
              "      <td>0.006793</td>\n",
              "      <td>-0.058885</td>\n",
              "      <td>-0.001932</td>\n",
              "      <td>-0.006029</td>\n",
              "      <td>0.001430</td>\n",
              "      <td>0.005957</td>\n",
              "      <td>-0.007842</td>\n",
              "      <td>-0.004877</td>\n",
              "      <td>-0.000108</td>\n",
              "      <td>-0.003131</td>\n",
              "      <td>-0.002310</td>\n",
              "      <td>-0.001030</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.002583</td>\n",
              "      <td>-0.002980</td>\n",
              "      <td>1.34</td>\n",
              "      <td>1.14</td>\n",
              "      <td>1.01</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.65</td>\n",
              "      <td>1.93</td>\n",
              "      <td>2.94</td>\n",
              "      <td>3.07</td>\n",
              "      <td>3.27</td>\n",
              "      <td>0.021898</td>\n",
              "      <td>-0.011765</td>\n",
              "      <td>-0.009615</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-1.50</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-1.64</td>\n",
              "      <td>-1.87</td>\n",
              "      <td>-0.42</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>1.12</td>\n",
              "      <td>-0.08</td>\n",
              "      <td>0.31</td>\n",
              "      <td>-0.04</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.29</td>\n",
              "      <td>-2.05</td>\n",
              "      <td>0.67</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-0.70</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-11-15</th>\n",
              "      <td>23271.279297</td>\n",
              "      <td>3.612171</td>\n",
              "      <td>-0.005903</td>\n",
              "      <td>-0.001290</td>\n",
              "      <td>0.000747</td>\n",
              "      <td>-0.001693</td>\n",
              "      <td>-1.239552</td>\n",
              "      <td>-0.698658</td>\n",
              "      <td>-0.249391</td>\n",
              "      <td>0.490896</td>\n",
              "      <td>23413.004596</td>\n",
              "      <td>23329.756233</td>\n",
              "      <td>22932.225731</td>\n",
              "      <td>21605.525627</td>\n",
              "      <td>1.06</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.36</td>\n",
              "      <td>2.04</td>\n",
              "      <td>2.33</td>\n",
              "      <td>-0.007006</td>\n",
              "      <td>0.005963</td>\n",
              "      <td>3.60</td>\n",
              "      <td>4.28</td>\n",
              "      <td>0.002631</td>\n",
              "      <td>-0.001611</td>\n",
              "      <td>-0.000133</td>\n",
              "      <td>-0.000452</td>\n",
              "      <td>-0.013190</td>\n",
              "      <td>-0.008928</td>\n",
              "      <td>0.020112</td>\n",
              "      <td>-0.002796</td>\n",
              "      <td>0.009458</td>\n",
              "      <td>-0.012731</td>\n",
              "      <td>-0.005366</td>\n",
              "      <td>-0.012524</td>\n",
              "      <td>-0.002696</td>\n",
              "      <td>-0.005638</td>\n",
              "      <td>-0.004382</td>\n",
              "      <td>-0.005526</td>\n",
              "      <td>-0.010306</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.004873</td>\n",
              "      <td>-0.004867</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.97</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.30</td>\n",
              "      <td>0.68</td>\n",
              "      <td>1.95</td>\n",
              "      <td>2.92</td>\n",
              "      <td>3.05</td>\n",
              "      <td>3.22</td>\n",
              "      <td>-0.007143</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-0.009709</td>\n",
              "      <td>-0.56</td>\n",
              "      <td>-0.55</td>\n",
              "      <td>-0.27</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.66</td>\n",
              "      <td>-0.36</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>-0.05</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.99</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.71</td>\n",
              "      <td>-1.74</td>\n",
              "      <td>0.03</td>\n",
              "      <td>-0.60</td>\n",
              "      <td>-0.46</td>\n",
              "      <td>-0.50</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.01</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>-2.04</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>399 rows × 82 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                   Close     Volume       mom  ...  wheat-F   XAG   XAU\n",
              "Date                                           ...                     \n",
              "2016-04-20  18096.269531 -23.600606  0.002364  ...     3.60  0.12 -0.52\n",
              "2016-04-21  17982.519531  -1.033994 -0.006286  ...    -1.42  0.24  0.39\n",
              "2016-04-22  18003.750000 -15.300853  0.001181  ...    -5.77 -0.24 -1.33\n",
              "2016-04-25  17977.240234  -1.198861 -0.001472  ...     2.03  0.24  0.45\n",
              "2016-04-26  17990.320313  -0.425596  0.000728  ...     2.41  1.00  0.45\n",
              "...                  ...        ...       ...  ...      ...   ...   ...\n",
              "2017-11-09  23461.939453   6.511740 -0.004304  ...     0.53 -0.26  0.32\n",
              "2017-11-10  23422.210938  -0.991838 -0.001693  ...     0.70 -0.71 -0.80\n",
              "2017-11-13  23439.699219 -65.347705  0.000747  ...    -1.85  0.83  0.16\n",
              "2017-11-14  23409.470703  -1.387911 -0.001290  ...     1.00  0.01  0.24\n",
              "2017-11-15  23271.279297   3.612171 -0.005903  ...    -2.04 -0.22 -0.11\n",
              "\n",
              "[399 rows x 82 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 227
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RW3XMzBXnvrt",
        "outputId": "b14f56fa-1f11-4256-8568-5aac198a9eba"
      },
      "source": [
        "# Normalizing The Data\n",
        "scaler = MinMaxScaler(feature_range=(0, 1))\n",
        "scaled_training_data = scaler.fit_transform(training_data)\n",
        "\n",
        "scaled_training_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.08596998, 0.6191131 , 0.57216966, ..., 0.45271716, 0.67985612,\n",
              "        0.69756481],\n",
              "       [0.10404461, 0.6191131 , 0.71946056, ..., 0.6067608 , 0.86536485,\n",
              "        0.83189317],\n",
              "       [0.10266036, 0.6191131 , 0.55517186, ..., 0.4347454 , 0.73741007,\n",
              "        0.65750196],\n",
              "       ...,\n",
              "       [0.95189729, 0.62064463, 0.55018761, ..., 0.48951647, 0.69013361,\n",
              "        0.709348  ],\n",
              "       [0.9642669 , 0.61908616, 0.62761226, ..., 0.58707745, 0.66135663,\n",
              "        0.6512176 ],\n",
              "       [0.96999841, 0.61924785, 0.59475601, ..., 0.59092854, 0.88900308,\n",
              "        0.78790259]])"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nWnjnp-Xe-uU"
      },
      "source": [
        "# Spitting The Data Into X_train, y_train with 60 timestamp\n",
        "X_train = []\n",
        "y_train = []\n",
        "\n",
        "for i in range(60, scaled_training_data.shape[0]-60):\n",
        "    X_train.append(scaled_training_data[i-60:i])\n",
        "    y_train.append(scaled_training_data[i,[0, 3]])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vrHKUNMWfCd-",
        "outputId": "ae43736b-0bdb-4ba9-cc05-f4ce55aedf2f"
      },
      "source": [
        "# Converting Lists Into Numpy Arrays\n",
        "X_train, y_train = np.array(X_train), np.array(y_train)\n",
        "X_train.shape, y_train.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1465, 60, 82), (1465, 2))"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hNXGaoHPutHA"
      },
      "source": [
        "Building the Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pIAhevWafDAR"
      },
      "source": [
        "from tensorflow import keras\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import LSTM, Dense, Dropout\n",
        "from tensorflow.keras.optimizers import Adam, RMSprop\n",
        "from sklearn.metrics import mean_squared_error"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b-einCBcfWRk"
      },
      "source": [
        "model = Sequential()\n",
        "\n",
        "model.add(LSTM(units = 50, return_sequences = True, input_shape = (X_train.shape[1], 82)))\n",
        "model.add(Dropout(0.2))\n",
        "\n",
        "model.add(LSTM(units = 50, return_sequences = True))\n",
        "model.add(Dropout(0.2))\n",
        "\n",
        "# model.add(LSTM(units = 50, return_sequences = True))\n",
        "# model.add(Dropout(0.2))\n",
        "\n",
        "model.add(LSTM(units = 50))\n",
        "model.add(Dropout(0.2))\n",
        "\n",
        "model.add(Dense(units = 2))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "69IZMZ1rfgi3"
      },
      "source": [
        "model.compile(optimizer = Adam(), loss = 'mean_squared_error')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "503BWb0SfoVL",
        "outputId": "400ff882-f3f5-423c-c526-cd9c880e7fae"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "lstm (LSTM)                  (None, 60, 50)            26600     \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 60, 50)            0         \n",
            "_________________________________________________________________\n",
            "lstm_1 (LSTM)                (None, 60, 50)            20200     \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 60, 50)            0         \n",
            "_________________________________________________________________\n",
            "lstm_2 (LSTM)                (None, 50)                20200     \n",
            "_________________________________________________________________\n",
            "dropout_2 (Dropout)          (None, 50)                0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 2)                 102       \n",
            "=================================================================\n",
            "Total params: 67,102\n",
            "Trainable params: 67,102\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dO3uUF5OfqSj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ce517c30-1e10-46d2-f861-a6c6e2c83147"
      },
      "source": [
        "# Train The Model\n",
        "model.fit(X_train, y_train, epochs=100, batch_size=32, validation_split=0.2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "37/37 [==============================] - 8s 134ms/step - loss: 0.0082 - val_loss: 0.0064\n",
            "Epoch 2/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0082 - val_loss: 0.0097\n",
            "Epoch 3/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0080 - val_loss: 0.0081\n",
            "Epoch 4/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0080 - val_loss: 0.0067\n",
            "Epoch 5/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0078 - val_loss: 0.0093\n",
            "Epoch 6/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0075 - val_loss: 0.0061\n",
            "Epoch 7/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0074 - val_loss: 0.0064\n",
            "Epoch 8/100\n",
            "37/37 [==============================] - 4s 100ms/step - loss: 0.0076 - val_loss: 0.0074\n",
            "Epoch 9/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0074 - val_loss: 0.0079\n",
            "Epoch 10/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0073 - val_loss: 0.0080\n",
            "Epoch 11/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0075 - val_loss: 0.0077\n",
            "Epoch 12/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0074 - val_loss: 0.0067\n",
            "Epoch 13/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0073 - val_loss: 0.0061\n",
            "Epoch 14/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0074 - val_loss: 0.0070\n",
            "Epoch 15/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0074 - val_loss: 0.0062\n",
            "Epoch 16/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0067 - val_loss: 0.0066\n",
            "Epoch 17/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0069 - val_loss: 0.0068\n",
            "Epoch 18/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0067 - val_loss: 0.0086\n",
            "Epoch 19/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0067 - val_loss: 0.0059\n",
            "Epoch 20/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0067 - val_loss: 0.0070\n",
            "Epoch 21/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0068 - val_loss: 0.0067\n",
            "Epoch 22/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0070 - val_loss: 0.0081\n",
            "Epoch 23/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0070 - val_loss: 0.0095\n",
            "Epoch 24/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0068 - val_loss: 0.0062\n",
            "Epoch 25/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0066 - val_loss: 0.0066\n",
            "Epoch 26/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0064 - val_loss: 0.0073\n",
            "Epoch 27/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0063 - val_loss: 0.0062\n",
            "Epoch 28/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0063 - val_loss: 0.0058\n",
            "Epoch 29/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0061 - val_loss: 0.0063\n",
            "Epoch 30/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0064 - val_loss: 0.0067\n",
            "Epoch 31/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0059 - val_loss: 0.0072\n",
            "Epoch 32/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0060 - val_loss: 0.0062\n",
            "Epoch 33/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0056 - val_loss: 0.0064\n",
            "Epoch 34/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0056 - val_loss: 0.0049\n",
            "Epoch 35/100\n",
            "37/37 [==============================] - 4s 109ms/step - loss: 0.0052 - val_loss: 0.0052\n",
            "Epoch 36/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0045 - val_loss: 0.0053\n",
            "Epoch 37/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0045 - val_loss: 0.0046\n",
            "Epoch 38/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0042 - val_loss: 0.0051\n",
            "Epoch 39/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0038 - val_loss: 0.0052\n",
            "Epoch 40/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0038 - val_loss: 0.0044\n",
            "Epoch 41/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0036 - val_loss: 0.0033\n",
            "Epoch 42/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0033 - val_loss: 0.0045\n",
            "Epoch 43/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0035 - val_loss: 0.0040\n",
            "Epoch 44/100\n",
            "37/37 [==============================] - 4s 110ms/step - loss: 0.0030 - val_loss: 0.0031\n",
            "Epoch 45/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0031 - val_loss: 0.0049\n",
            "Epoch 46/100\n",
            "37/37 [==============================] - 4s 114ms/step - loss: 0.0031 - val_loss: 0.0069\n",
            "Epoch 47/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0030 - val_loss: 0.0026\n",
            "Epoch 48/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0028 - val_loss: 0.0040\n",
            "Epoch 49/100\n",
            "37/37 [==============================] - 4s 110ms/step - loss: 0.0026 - val_loss: 0.0036\n",
            "Epoch 50/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0026 - val_loss: 0.0030\n",
            "Epoch 51/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0028 - val_loss: 0.0034\n",
            "Epoch 52/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0026 - val_loss: 0.0020\n",
            "Epoch 53/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0029 - val_loss: 0.0021\n",
            "Epoch 54/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0024 - val_loss: 0.0031\n",
            "Epoch 55/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0024 - val_loss: 0.0029\n",
            "Epoch 56/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0024 - val_loss: 0.0028\n",
            "Epoch 57/100\n",
            "37/37 [==============================] - 4s 109ms/step - loss: 0.0024 - val_loss: 0.0032\n",
            "Epoch 58/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0023 - val_loss: 0.0038\n",
            "Epoch 59/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0022 - val_loss: 0.0042\n",
            "Epoch 60/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0024 - val_loss: 0.0026\n",
            "Epoch 61/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0023 - val_loss: 0.0027\n",
            "Epoch 62/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0021 - val_loss: 0.0018\n",
            "Epoch 63/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0022 - val_loss: 0.0028\n",
            "Epoch 64/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0020 - val_loss: 0.0030\n",
            "Epoch 65/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0020 - val_loss: 0.0029\n",
            "Epoch 66/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0020 - val_loss: 0.0024\n",
            "Epoch 67/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0020 - val_loss: 0.0017\n",
            "Epoch 68/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0018 - val_loss: 0.0018\n",
            "Epoch 69/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0021 - val_loss: 0.0021\n",
            "Epoch 70/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0019 - val_loss: 0.0015\n",
            "Epoch 71/100\n",
            "37/37 [==============================] - 4s 102ms/step - loss: 0.0021 - val_loss: 0.0012\n",
            "Epoch 72/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0019 - val_loss: 0.0017\n",
            "Epoch 73/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0019 - val_loss: 0.0019\n",
            "Epoch 74/100\n",
            "37/37 [==============================] - 4s 101ms/step - loss: 0.0019 - val_loss: 0.0019\n",
            "Epoch 75/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0019 - val_loss: 0.0017\n",
            "Epoch 76/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0017 - val_loss: 0.0018\n",
            "Epoch 77/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0016 - val_loss: 0.0017\n",
            "Epoch 78/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0018 - val_loss: 0.0016\n",
            "Epoch 79/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0018 - val_loss: 0.0023\n",
            "Epoch 80/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0016 - val_loss: 0.0015\n",
            "Epoch 81/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0017 - val_loss: 0.0021\n",
            "Epoch 82/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0017 - val_loss: 0.0012\n",
            "Epoch 83/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0016 - val_loss: 0.0033\n",
            "Epoch 84/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0017 - val_loss: 0.0019\n",
            "Epoch 85/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0016 - val_loss: 0.0019\n",
            "Epoch 86/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0016 - val_loss: 0.0016\n",
            "Epoch 87/100\n",
            "37/37 [==============================] - 4s 106ms/step - loss: 0.0015 - val_loss: 0.0028\n",
            "Epoch 88/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0018 - val_loss: 0.0011\n",
            "Epoch 89/100\n",
            "37/37 [==============================] - 4s 112ms/step - loss: 0.0018 - val_loss: 0.0025\n",
            "Epoch 90/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0015 - val_loss: 0.0029\n",
            "Epoch 91/100\n",
            "37/37 [==============================] - 4s 105ms/step - loss: 0.0016 - val_loss: 0.0029\n",
            "Epoch 92/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0016 - val_loss: 0.0033\n",
            "Epoch 93/100\n",
            "37/37 [==============================] - 4s 103ms/step - loss: 0.0016 - val_loss: 0.0024\n",
            "Epoch 94/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0014 - val_loss: 0.0027\n",
            "Epoch 95/100\n",
            "37/37 [==============================] - 4s 104ms/step - loss: 0.0014 - val_loss: 0.0011\n",
            "Epoch 96/100\n",
            "37/37 [==============================] - 4s 107ms/step - loss: 0.0015 - val_loss: 0.0017\n",
            "Epoch 97/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0014 - val_loss: 0.0019\n",
            "Epoch 98/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0014 - val_loss: 0.0012\n",
            "Epoch 99/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0014 - val_loss: 0.0019\n",
            "Epoch 100/100\n",
            "37/37 [==============================] - 4s 108ms/step - loss: 0.0012 - val_loss: 0.0019\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f437d279810>"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "ckbIYR0Gghgi",
        "outputId": "41f2a24a-e85a-4bf9-cf00-1eaa31b25741"
      },
      "source": [
        "metrics = pd.DataFrame(model.history.history)\n",
        "metrics.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>loss</th>\n",
              "      <th>val_loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.047421</td>\n",
              "      <td>0.009798</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.011903</td>\n",
              "      <td>0.013372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.011373</td>\n",
              "      <td>0.006759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.009926</td>\n",
              "      <td>0.006495</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.010043</td>\n",
              "      <td>0.008113</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       loss  val_loss\n",
              "0  0.047421  0.009798\n",
              "1  0.011903  0.013372\n",
              "2  0.011373  0.006759\n",
              "3  0.009926  0.006495\n",
              "4  0.010043  0.008113"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 367
        },
        "id": "8xxWXb3ihTfa",
        "outputId": "027a6ac3-7c6b-4381-a3cd-5d892bdca694"
      },
      "source": [
        "# Visualizing The Loss vs Val_loss\n",
        "metrics[['loss','val_loss']].plot(figsize=(12, 5))\n",
        "plt.title(\"Loss Vs Val_loss\")\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Loss')"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-9Q9i8J1gzE4"
      },
      "source": [
        "# Saving The Model\n",
        "model.save('Processed_DJI_Model1.h5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dfwwxj9Eu5ps"
      },
      "source": [
        "Test Data Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mXo0jhUBhCIS"
      },
      "source": [
        "# Get past 60 days data from the training data\n",
        "past_60_days_data = training_data.tail(60)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Muw-l9cnqu4K",
        "outputId": "c0ab0ad7-edb0-4667-f9a1-a5fe93c3bc46"
      },
      "source": [
        "# Create The New Testing DataFrame\n",
        "new_testing_data = past_60_days_data.append(testing_data)\n",
        "new_testing_data.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(459, 82)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hg7hryrEhJb2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eea9760e-8f7b-4468-955c-5c724d8f06ae"
      },
      "source": [
        "# Normalizing The Data\n",
        "scaled_testing_data = scaler.transform(new_testing_data)\n",
        "scaled_testing_data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.71861857, 0.63306638, 0.43445939, ..., 0.52503209, 0.74152107,\n",
              "        0.73684211],\n",
              "       [0.75131202, 0.61897928, 0.74808981, ..., 0.50877193, 0.75847893,\n",
              "        0.75569521],\n",
              "       [0.72548628, 0.62205814, 0.42591093, ..., 0.39623449, 0.65724563,\n",
              "        0.70227808],\n",
              "       ...,\n",
              "       [1.59440784, 0.59065104, 0.57432774, ..., 0.39409499, 0.70709147,\n",
              "        0.67949725],\n",
              "       [1.59090345, 0.61879865, 0.55352209, ..., 0.51604621, 0.66495375,\n",
              "        0.68578162],\n",
              "       [1.57488295, 0.6209991 , 0.5063828 , ..., 0.38596491, 0.65313464,\n",
              "        0.65828751]])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p8JrxGEhhcS3"
      },
      "source": [
        "# Splitting The Test Data Into X_test, y_test\n",
        "X_test = []\n",
        "y_test = []\n",
        "\n",
        "for i in range(60, scaled_testing_data.shape[0]):\n",
        "    X_test.append(scaled_testing_data[i-60:i])\n",
        "    y_test.append(scaled_testing_data[i,[0,3]])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hPmpvuMKhehy",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "02698689-4d19-4718-bffa-b1d2576332be"
      },
      "source": [
        "# Converting Lists Into Numpy Array\n",
        "X_test, y_test = np.array(X_test), np.array(y_test)\n",
        "X_test.shape, y_test.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((399, 60, 82), (399, 2))"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RemgJ17RrAg0",
        "outputId": "7141c7a7-21b3-4534-bf59-b9b6c127d267"
      },
      "source": [
        "# Evaluate The Model\n",
        "loss = model.evaluate(X_test, y_test)\n",
        "loss"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "13/13 [==============================] - 0s 25ms/step - loss: 0.0774\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.07736527919769287"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iwNwjAs7vBkw"
      },
      "source": [
        "Predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LHfJA_vLrLEn"
      },
      "source": [
        "# Load The Model\n",
        "model = keras.models.load_model('Processed_DJI_Model1.h5')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u0niHLM1ra7h"
      },
      "source": [
        "# Make Predictions\n",
        "predictions = model.predict(X_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Bzy-9umSrdee",
        "outputId": "25bd728e-4194-4e01-c241-a23a4ce9146b"
      },
      "source": [
        "# Find The Mean Squared Error\n",
        "mean_error = mean_squared_error(y_test, predictions)\n",
        "\n",
        "mean_error"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.07736528488367285"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1pacJmo9rh6K",
        "outputId": "50e157a7-c8db-48c9-84bd-c0bd0d36b170"
      },
      "source": [
        "# Check Scale\n",
        "scaler.scale_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "       1.75746924e-01, 1.02669405e-01, 6.06428138e-02, 7.58725341e-02,\n",
              "       8.38222967e-02, 7.96812749e-02, 3.39904827e-02, 6.21890547e-02,\n",
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              "       5.13874615e-02, 7.85545954e-02])"
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        "id": "RlRFSIWAKWJ9",
        "outputId": "d9e3f332-b5a0-4b11-9511-ee131faefcb5"
      },
      "source": [
        "predictions"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "       [0.8813913 , 0.5864406 ]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "55UdW7n7rh48"
      },
      "source": [
        "scale_close = 1/5.00575662e-03\n",
        "\n",
        "# Unscaling The Predictions\n",
        "predicted_close = predictions[:, 1]\n",
        "predicted_close = predicted_close * scale_close"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sEl8KjSNr0E-"
      },
      "source": [
        "# Unscaling the y_test\n",
        "actual_close = y_test[:, 1]\n",
        "actual_close = actual_close * scale_close"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 203
        },
        "id": "rE__SE-ZsD2N",
        "outputId": "e4a115b5-cdfb-4d2d-d1f9-9e0965dc2bda"
      },
      "source": [
        "# Create The DataFrame For Actual_Close VS Predicted_Close\n",
        "new_close_df = pd.DataFrame({\"Actual Close\": actual_close, \"Predicted Close\": predicted_close})\n",
        "new_close_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Actual Close</th>\n",
              "      <th>Predicted Close</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>118.814408</td>\n",
              "      <td>119.069519</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>118.033695</td>\n",
              "      <td>119.076370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100.379152</td>\n",
              "      <td>119.057053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>115.619234</td>\n",
              "      <td>119.062843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>110.203927</td>\n",
              "      <td>119.026192</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Actual Close  Predicted Close\n",
              "0    118.814408       119.069519\n",
              "1    118.033695       119.076370\n",
              "2    100.379152       119.057053\n",
              "3    115.619234       119.062843\n",
              "4    110.203927       119.026192"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 503
        },
        "id": "f0hh7hB5sJKR",
        "outputId": "7a648e69-643b-4794-82bb-57b1a8be6314"
      },
      "source": [
        "# Visualizing The Close Prices\n",
        "sns.set(style='darkgrid')\n",
        "plt.figure(figsize=(15, 6), dpi=200)\n",
        "plt.title(\"DJI Stock Market Close Price\")\n",
        "plt.xlabel('Timestamps')\n",
        "plt.ylabel('Close')\n",
        "plt.plot(new_close_df['Actual Close'], color='purple')\n",
        "plt.plot(new_close_df['Predicted Close'], color='blue')\n",
        "plt.legend(['Actual', 'Prediction'], loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 3000x1200 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}