Stock_Market_Prediction.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Stock_Market_Prediction.ipynb",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
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        "id": "F7EvOM7quTyq",
        "colab_type": "code",
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          "base_uri": "https://localhost:8080/",
          "height": 267
        },
        "outputId": "9d242f3d-9b66-4b13-befc-41e3c0cae235"
      },
      "source": [
        "!pip install pmdarima\n",
        "from pmdarima import auto_arima"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: pmdarima in /usr/local/lib/python3.6/dist-packages (1.6.1)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.15.1)\n",
            "Requirement already satisfied: pandas>=0.19 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.0.5)\n",
            "Requirement already satisfied: scikit-learn>=0.22 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.22.2.post1)\n",
            "Requirement already satisfied: Cython<0.29.18,>=0.29 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.29.17)\n",
            "Requirement already satisfied: urllib3 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.24.3)\n",
            "Requirement already satisfied: statsmodels>=0.11 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (0.11.1)\n",
            "Requirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.4.1)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.6/dist-packages (from pmdarima) (1.18.5)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.19->pmdarima) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.19->pmdarima) (2.8.1)\n",
            "Requirement already satisfied: patsy>=0.5 in /usr/local/lib/python3.6/dist-packages (from statsmodels>=0.11->pmdarima) (0.5.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas>=0.19->pmdarima) (1.12.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4t77CiKiy0lw",
        "colab_type": "code",
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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 91
        },
        "outputId": "7ee0c4cb-e58f-44c9-a94c-222350c68d3a"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-3e80aeaa-9e52-4da1-aeff-1b3ea20d17de\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-3e80aeaa-9e52-4da1-aeff-1b3ea20d17de\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving kaggle.json to kaggle.json\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'kaggle.json': b'{\"username\":\"rohansirohia\",\"key\":\"2c005421e079222405330ff20409a081\"}'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tNdSc1OlzdCA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install -q kaggle"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n90vcaFdzkcx",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!mkdir -p ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jhtfjw-vztcY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "d92c7772-d8b4-434e-f04f-4d0cd40713ac"
      },
      "source": [
        "!kaggle datasets download rohanrao/nifty50-stock-market-data\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Warning: Your Kaggle API key is readable by other users on this system! To fix this, you can run 'chmod 600 /root/.kaggle/kaggle.json'\n",
            "Downloading nifty50-stock-market-data.zip to /content\n",
            "\r  0% 0.00/17.6M [00:00<?, ?B/s]\r 28% 5.00M/17.6M [00:00<00:00, 44.4MB/s]\r 74% 13.0M/17.6M [00:00<00:00, 51.7MB/s]\n",
            "\r100% 17.6M/17.6M [00:00<00:00, 69.6MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F1VayhVN0nNn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from zipfile import ZipFile\n",
        "ob = ZipFile('nifty50-stock-market-data.zip')\n",
        "ob.extractall()"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1QW6jQf709E8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EUwmJrqp2C5J",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('HDFCBANK.csv')"
      ],
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E3ziDmya2Ptu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df.set_index(\"Date\", drop=False, inplace=True)\n"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "omTeKPdJ6i6t",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 581
        },
        "outputId": "22e4ec76-8dfa-4ccf-89e7-f259ec095dd8"
      },
      "source": [
        "df.tail(10)"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Series</th>\n",
              "      <th>Prev Close</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Last</th>\n",
              "      <th>Close</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Turnover</th>\n",
              "      <th>Trades</th>\n",
              "      <th>Deliverable Volume</th>\n",
              "      <th>%Deliverble</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>2020-05-15</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>893.70</td>\n",
              "      <td>890.50</td>\n",
              "      <td>892.40</td>\n",
              "      <td>875.00</td>\n",
              "      <td>888.00</td>\n",
              "      <td>888.15</td>\n",
              "      <td>885.00</td>\n",
              "      <td>12174870</td>\n",
              "      <td>1.077480e+15</td>\n",
              "      <td>280499.0</td>\n",
              "      <td>4280446.0</td>\n",
              "      <td>0.3516</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>2020-05-18</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>888.15</td>\n",
              "      <td>888.00</td>\n",
              "      <td>888.00</td>\n",
              "      <td>831.30</td>\n",
              "      <td>838.00</td>\n",
              "      <td>836.65</td>\n",
              "      <td>847.83</td>\n",
              "      <td>23326656</td>\n",
              "      <td>1.977695e+15</td>\n",
              "      <td>533951.0</td>\n",
              "      <td>10660724.0</td>\n",
              "      <td>0.4570</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>2020-05-19</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>836.65</td>\n",
              "      <td>860.85</td>\n",
              "      <td>867.30</td>\n",
              "      <td>826.10</td>\n",
              "      <td>832.85</td>\n",
              "      <td>830.65</td>\n",
              "      <td>846.32</td>\n",
              "      <td>23730561</td>\n",
              "      <td>2.008377e+15</td>\n",
              "      <td>415550.0</td>\n",
              "      <td>8905443.0</td>\n",
              "      <td>0.3753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>2020-05-20</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>830.65</td>\n",
              "      <td>836.45</td>\n",
              "      <td>864.00</td>\n",
              "      <td>832.20</td>\n",
              "      <td>863.50</td>\n",
              "      <td>857.10</td>\n",
              "      <td>844.42</td>\n",
              "      <td>20007413</td>\n",
              "      <td>1.689474e+15</td>\n",
              "      <td>359835.0</td>\n",
              "      <td>8748975.0</td>\n",
              "      <td>0.4373</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>857.10</td>\n",
              "      <td>861.45</td>\n",
              "      <td>884.00</td>\n",
              "      <td>852.30</td>\n",
              "      <td>860.40</td>\n",
              "      <td>859.55</td>\n",
              "      <td>870.64</td>\n",
              "      <td>24239683</td>\n",
              "      <td>2.110407e+15</td>\n",
              "      <td>416994.0</td>\n",
              "      <td>10837256.0</td>\n",
              "      <td>0.4471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-22</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>859.55</td>\n",
              "      <td>850.00</td>\n",
              "      <td>870.30</td>\n",
              "      <td>833.05</td>\n",
              "      <td>842.65</td>\n",
              "      <td>838.85</td>\n",
              "      <td>844.52</td>\n",
              "      <td>21025849</td>\n",
              "      <td>1.775681e+15</td>\n",
              "      <td>382888.0</td>\n",
              "      <td>5893652.0</td>\n",
              "      <td>0.2803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-26</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>838.85</td>\n",
              "      <td>857.00</td>\n",
              "      <td>871.75</td>\n",
              "      <td>848.75</td>\n",
              "      <td>858.00</td>\n",
              "      <td>852.40</td>\n",
              "      <td>860.62</td>\n",
              "      <td>19002589</td>\n",
              "      <td>1.635402e+15</td>\n",
              "      <td>303415.0</td>\n",
              "      <td>7852814.0</td>\n",
              "      <td>0.4132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-27</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>852.40</td>\n",
              "      <td>859.90</td>\n",
              "      <td>909.80</td>\n",
              "      <td>857.15</td>\n",
              "      <td>901.40</td>\n",
              "      <td>903.65</td>\n",
              "      <td>881.85</td>\n",
              "      <td>28013227</td>\n",
              "      <td>2.470358e+15</td>\n",
              "      <td>388895.0</td>\n",
              "      <td>11070917.0</td>\n",
              "      <td>0.3952</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-28</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>903.65</td>\n",
              "      <td>920.00</td>\n",
              "      <td>950.00</td>\n",
              "      <td>913.95</td>\n",
              "      <td>947.50</td>\n",
              "      <td>945.25</td>\n",
              "      <td>938.36</td>\n",
              "      <td>37744926</td>\n",
              "      <td>3.541845e+15</td>\n",
              "      <td>631552.0</td>\n",
              "      <td>15665889.0</td>\n",
              "      <td>0.4150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-29</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>945.25</td>\n",
              "      <td>944.00</td>\n",
              "      <td>955.00</td>\n",
              "      <td>923.45</td>\n",
              "      <td>947.10</td>\n",
              "      <td>951.65</td>\n",
              "      <td>937.44</td>\n",
              "      <td>26512600</td>\n",
              "      <td>2.485397e+15</td>\n",
              "      <td>352639.0</td>\n",
              "      <td>10530145.0</td>\n",
              "      <td>0.3972</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  Date    Symbol  ... Deliverable Volume  %Deliverble\n",
              "Date                              ...                                \n",
              "2020-05-15  2020-05-15  HDFCBANK  ...          4280446.0       0.3516\n",
              "2020-05-18  2020-05-18  HDFCBANK  ...         10660724.0       0.4570\n",
              "2020-05-19  2020-05-19  HDFCBANK  ...          8905443.0       0.3753\n",
              "2020-05-20  2020-05-20  HDFCBANK  ...          8748975.0       0.4373\n",
              "2020-05-21  2020-05-21  HDFCBANK  ...         10837256.0       0.4471\n",
              "2020-05-22  2020-05-22  HDFCBANK  ...          5893652.0       0.2803\n",
              "2020-05-26  2020-05-26  HDFCBANK  ...          7852814.0       0.4132\n",
              "2020-05-27  2020-05-27  HDFCBANK  ...         11070917.0       0.3952\n",
              "2020-05-28  2020-05-28  HDFCBANK  ...         15665889.0       0.4150\n",
              "2020-05-29  2020-05-29  HDFCBANK  ...         10530145.0       0.3972\n",
              "\n",
              "[10 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m70K3weD6f3E",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df['Date'] = pd.to_datetime(df['Date'])"
      ],
      "execution_count": 64,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QPADgwH56jfN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "lag_features = [\"High\", \"Low\", \"Volume\", \"Turnover\", \"Trades\"]\n",
        "\n",
        "win3, win7, win30 = 3,7,30\n"
      ],
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ejWL-cCA6jq9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "outputId": "7d5131aa-7937-4f1a-de72-efc40afa263a"
      },
      "source": [
        "#df.VWAP.tail(100).plot(figsize=(10,10))\n",
        "#plt.grid(True)\n",
        "\n",
        "df_rolled_3d = df[lag_features].rolling(window=win3, min_periods=0)\n",
        "df_rolled_7d = df[lag_features].rolling(window=win7, min_periods=0)\n",
        "df_rolled_30d = df[lag_features].rolling(window=win30, min_periods=0)\n",
        "\n",
        "\n",
        "\n",
        "df_mean_3d = df_rolled_3d.mean().shift(1).astype(np.float32)\n",
        "df_mean_7d = df_rolled_7d.mean().shift(1).astype(np.float32)\n",
        "df_mean_30d = df_rolled_30d.mean().shift(1).astype(np.float32)\n",
        "\n",
        "df_std_3d = df_rolled_3d.std().shift(1).astype(np.float32)\n",
        "df_std_7d = df_rolled_7d.std().shift(1).astype(np.float32)\n",
        "df_std_30d = df_rolled_30d.std().shift(1).astype(np.float32)\n",
        "\n",
        "#df_std_30d.plot(figsize=(10,10))\n",
        "\n",
        "\n",
        "for feature in lag_features:\n",
        "    df[f\"{feature}_mean_lag{win3}\"] = df_mean_3d[feature]\n",
        "    df[f\"{feature}_mean_lag{win7}\"] = df_mean_7d[feature]\n",
        "    df[f\"{feature}_mean_lag{win30}\"] = df_mean_30d[feature]\n",
        "    \n",
        "    df[f\"{feature}_std_lag{win3}\"] = df_std_3d[feature]\n",
        "    df[f\"{feature}_std_lag{win7}\"] = df_std_7d[feature]\n",
        "    df[f\"{feature}_std_lag{win30}\"] = df_std_30d[feature]\n",
        "\n",
        "\n",
        "df.fillna(df.mean(), inplace=True)\n",
        "df.set_index(\"Date\", drop=False, inplace=True)\n",
        "df.tail()"
      ],
      "execution_count": 66,
      "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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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Series</th>\n",
              "      <th>Prev Close</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Last</th>\n",
              "      <th>Close</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Turnover</th>\n",
              "      <th>Trades</th>\n",
              "      <th>Deliverable Volume</th>\n",
              "      <th>%Deliverble</th>\n",
              "      <th>High_mean_lag3</th>\n",
              "      <th>High_mean_lag7</th>\n",
              "      <th>High_mean_lag30</th>\n",
              "      <th>High_std_lag3</th>\n",
              "      <th>High_std_lag7</th>\n",
              "      <th>High_std_lag30</th>\n",
              "      <th>Low_mean_lag3</th>\n",
              "      <th>Low_mean_lag7</th>\n",
              "      <th>Low_mean_lag30</th>\n",
              "      <th>Low_std_lag3</th>\n",
              "      <th>Low_std_lag7</th>\n",
              "      <th>Low_std_lag30</th>\n",
              "      <th>Volume_mean_lag3</th>\n",
              "      <th>Volume_mean_lag7</th>\n",
              "      <th>Volume_mean_lag30</th>\n",
              "      <th>Volume_std_lag3</th>\n",
              "      <th>Volume_std_lag7</th>\n",
              "      <th>Volume_std_lag30</th>\n",
              "      <th>Turnover_mean_lag3</th>\n",
              "      <th>Turnover_mean_lag7</th>\n",
              "      <th>Turnover_mean_lag30</th>\n",
              "      <th>Turnover_std_lag3</th>\n",
              "      <th>Turnover_std_lag7</th>\n",
              "      <th>Turnover_std_lag30</th>\n",
              "      <th>Trades_mean_lag3</th>\n",
              "      <th>Trades_mean_lag7</th>\n",
              "      <th>Trades_mean_lag30</th>\n",
              "      <th>Trades_std_lag3</th>\n",
              "      <th>Trades_std_lag7</th>\n",
              "      <th>Trades_std_lag30</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-05-22</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>859.55</td>\n",
              "      <td>850.0</td>\n",
              "      <td>870.30</td>\n",
              "      <td>833.05</td>\n",
              "      <td>842.65</td>\n",
              "      <td>838.85</td>\n",
              "      <td>844.52</td>\n",
              "      <td>21025849</td>\n",
              "      <td>1.775681e+15</td>\n",
              "      <td>382888.0</td>\n",
              "      <td>5893652.0</td>\n",
              "      <td>0.2803</td>\n",
              "      <td>871.766663</td>\n",
              "      <td>895.242859</td>\n",
              "      <td>933.340027</td>\n",
              "      <td>10.722095</td>\n",
              "      <td>32.623196</td>\n",
              "      <td>34.955719</td>\n",
              "      <td>836.866638</td>\n",
              "      <td>861.285706</td>\n",
              "      <td>894.311646</td>\n",
              "      <td>13.709243</td>\n",
              "      <td>35.997379</td>\n",
              "      <td>38.313305</td>\n",
              "      <td>22659220.0</td>\n",
              "      <td>20775740.0</td>\n",
              "      <td>20553228.0</td>\n",
              "      <td>2310596.75</td>\n",
              "      <td>4178373.00</td>\n",
              "      <td>6202577.5</td>\n",
              "      <td>1.936086e+15</td>\n",
              "      <td>1.817698e+15</td>\n",
              "      <td>1.870241e+15</td>\n",
              "      <td>2.195808e+14</td>\n",
              "      <td>3.611859e+14</td>\n",
              "      <td>5.555840e+14</td>\n",
              "      <td>397459.65625</td>\n",
              "      <td>395285.71875</td>\n",
              "      <td>381707.37500</td>\n",
              "      <td>32591.916016</td>\n",
              "      <td>76942.398438</td>\n",
              "      <td>101612.656250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-26</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>838.85</td>\n",
              "      <td>857.0</td>\n",
              "      <td>871.75</td>\n",
              "      <td>848.75</td>\n",
              "      <td>858.00</td>\n",
              "      <td>852.40</td>\n",
              "      <td>860.62</td>\n",
              "      <td>19002589</td>\n",
              "      <td>1.635402e+15</td>\n",
              "      <td>303415.0</td>\n",
              "      <td>7852814.0</td>\n",
              "      <td>0.4132</td>\n",
              "      <td>872.766663</td>\n",
              "      <td>882.428589</td>\n",
              "      <td>932.106689</td>\n",
              "      <td>10.225621</td>\n",
              "      <td>16.657602</td>\n",
              "      <td>36.523727</td>\n",
              "      <td>839.183350</td>\n",
              "      <td>848.564270</td>\n",
              "      <td>893.901672</td>\n",
              "      <td>11.367314</td>\n",
              "      <td>24.969660</td>\n",
              "      <td>38.916389</td>\n",
              "      <td>21757648.0</td>\n",
              "      <td>20611782.0</td>\n",
              "      <td>20247202.0</td>\n",
              "      <td>2208998.75</td>\n",
              "      <td>4136691.50</td>\n",
              "      <td>5930379.5</td>\n",
              "      <td>1.858521e+15</td>\n",
              "      <td>1.774095e+15</td>\n",
              "      <td>1.841673e+15</td>\n",
              "      <td>2.223581e+14</td>\n",
              "      <td>3.420314e+14</td>\n",
              "      <td>5.367398e+14</td>\n",
              "      <td>386572.34375</td>\n",
              "      <td>393391.43750</td>\n",
              "      <td>378630.37500</td>\n",
              "      <td>28757.060547</td>\n",
              "      <td>77080.734375</td>\n",
              "      <td>100069.921875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-27</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>852.40</td>\n",
              "      <td>859.9</td>\n",
              "      <td>909.80</td>\n",
              "      <td>857.15</td>\n",
              "      <td>901.40</td>\n",
              "      <td>903.65</td>\n",
              "      <td>881.85</td>\n",
              "      <td>28013227</td>\n",
              "      <td>2.470358e+15</td>\n",
              "      <td>388895.0</td>\n",
              "      <td>11070917.0</td>\n",
              "      <td>0.3952</td>\n",
              "      <td>875.349976</td>\n",
              "      <td>876.821411</td>\n",
              "      <td>929.664978</td>\n",
              "      <td>7.526121</td>\n",
              "      <td>11.124143</td>\n",
              "      <td>38.048668</td>\n",
              "      <td>844.700012</td>\n",
              "      <td>842.671448</td>\n",
              "      <td>893.323303</td>\n",
              "      <td>10.244144</td>\n",
              "      <td>17.228558</td>\n",
              "      <td>39.468792</td>\n",
              "      <td>21422708.0</td>\n",
              "      <td>20501088.0</td>\n",
              "      <td>19943626.0</td>\n",
              "      <td>2641005.50</td>\n",
              "      <td>4172947.00</td>\n",
              "      <td>5744188.5</td>\n",
              "      <td>1.840497e+15</td>\n",
              "      <td>1.753502e+15</td>\n",
              "      <td>1.811661e+15</td>\n",
              "      <td>2.440457e+14</td>\n",
              "      <td>3.459650e+14</td>\n",
              "      <td>5.215484e+14</td>\n",
              "      <td>367765.65625</td>\n",
              "      <td>384733.15625</td>\n",
              "      <td>371976.90625</td>\n",
              "      <td>58280.023438</td>\n",
              "      <td>84020.960938</td>\n",
              "      <td>98131.242188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-28</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>903.65</td>\n",
              "      <td>920.0</td>\n",
              "      <td>950.00</td>\n",
              "      <td>913.95</td>\n",
              "      <td>947.50</td>\n",
              "      <td>945.25</td>\n",
              "      <td>938.36</td>\n",
              "      <td>37744926</td>\n",
              "      <td>3.541845e+15</td>\n",
              "      <td>631552.0</td>\n",
              "      <td>15665889.0</td>\n",
              "      <td>0.4150</td>\n",
              "      <td>883.950012</td>\n",
              "      <td>879.307129</td>\n",
              "      <td>928.961670</td>\n",
              "      <td>22.398493</td>\n",
              "      <td>16.042248</td>\n",
              "      <td>38.219685</td>\n",
              "      <td>846.316650</td>\n",
              "      <td>840.121399</td>\n",
              "      <td>892.228333</td>\n",
              "      <td>12.232880</td>\n",
              "      <td>12.246865</td>\n",
              "      <td>40.016064</td>\n",
              "      <td>22680556.0</td>\n",
              "      <td>22763712.0</td>\n",
              "      <td>20136434.0</td>\n",
              "      <td>4727731.00</td>\n",
              "      <td>3048250.75</td>\n",
              "      <td>5917990.0</td>\n",
              "      <td>1.960481e+15</td>\n",
              "      <td>1.952485e+15</td>\n",
              "      <td>1.826328e+15</td>\n",
              "      <td>4.471029e+14</td>\n",
              "      <td>2.880589e+14</td>\n",
              "      <td>5.339499e+14</td>\n",
              "      <td>358399.34375</td>\n",
              "      <td>400218.28125</td>\n",
              "      <td>371009.71875</td>\n",
              "      <td>47712.457031</td>\n",
              "      <td>70511.421875</td>\n",
              "      <td>97805.359375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-29</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>945.25</td>\n",
              "      <td>944.0</td>\n",
              "      <td>955.00</td>\n",
              "      <td>923.45</td>\n",
              "      <td>947.10</td>\n",
              "      <td>951.65</td>\n",
              "      <td>937.44</td>\n",
              "      <td>26512600</td>\n",
              "      <td>2.485397e+15</td>\n",
              "      <td>352639.0</td>\n",
              "      <td>10530145.0</td>\n",
              "      <td>0.3972</td>\n",
              "      <td>910.516663</td>\n",
              "      <td>888.164307</td>\n",
              "      <td>929.071655</td>\n",
              "      <td>39.129921</td>\n",
              "      <td>31.403008</td>\n",
              "      <td>38.277203</td>\n",
              "      <td>873.283325</td>\n",
              "      <td>851.928589</td>\n",
              "      <td>893.153320</td>\n",
              "      <td>35.467918</td>\n",
              "      <td>29.712215</td>\n",
              "      <td>40.192253</td>\n",
              "      <td>28253580.0</td>\n",
              "      <td>24823464.0</td>\n",
              "      <td>20825288.0</td>\n",
              "      <td>9373480.00</td>\n",
              "      <td>6457203.00</td>\n",
              "      <td>6700830.0</td>\n",
              "      <td>2.549202e+15</td>\n",
              "      <td>2.175935e+15</td>\n",
              "      <td>1.892707e+15</td>\n",
              "      <td>9.556636e+14</td>\n",
              "      <td>6.675562e+14</td>\n",
              "      <td>6.159572e+14</td>\n",
              "      <td>441287.34375</td>\n",
              "      <td>414161.28125</td>\n",
              "      <td>379089.87500</td>\n",
              "      <td>170226.875000</td>\n",
              "      <td>103361.148438</td>\n",
              "      <td>108755.562500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 Date    Symbol  ... Trades_std_lag7  Trades_std_lag30\n",
              "Date                             ...                                  \n",
              "2020-05-22 2020-05-22  HDFCBANK  ...    76942.398438     101612.656250\n",
              "2020-05-26 2020-05-26  HDFCBANK  ...    77080.734375     100069.921875\n",
              "2020-05-27 2020-05-27  HDFCBANK  ...    84020.960938      98131.242188\n",
              "2020-05-28 2020-05-28  HDFCBANK  ...    70511.421875      97805.359375\n",
              "2020-05-29 2020-05-29  HDFCBANK  ...   103361.148438     108755.562500\n",
              "\n",
              "[5 rows x 45 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oagPLpbqnVTm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "outputId": "6b010d67-d218-4ef5-f55d-6e527ab8a791"
      },
      "source": [
        "df.Date = pd.to_datetime(df.Date, format=\"%Y-%m-%d\")\n",
        "df[\"month\"] = df.Date.dt.month\n",
        "df[\"week\"] = df.Date.dt.week\n",
        "df[\"day\"] = df.Date.dt.day\n",
        "df[\"day_of_week\"] = df.Date.dt.dayofweek\n",
        "df.head()"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Series</th>\n",
              "      <th>Prev Close</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Last</th>\n",
              "      <th>Close</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Turnover</th>\n",
              "      <th>Trades</th>\n",
              "      <th>Deliverable Volume</th>\n",
              "      <th>%Deliverble</th>\n",
              "      <th>High_mean_lag3</th>\n",
              "      <th>High_mean_lag7</th>\n",
              "      <th>High_mean_lag30</th>\n",
              "      <th>High_std_lag3</th>\n",
              "      <th>High_std_lag7</th>\n",
              "      <th>High_std_lag30</th>\n",
              "      <th>Low_mean_lag3</th>\n",
              "      <th>Low_mean_lag7</th>\n",
              "      <th>Low_mean_lag30</th>\n",
              "      <th>Low_std_lag3</th>\n",
              "      <th>Low_std_lag7</th>\n",
              "      <th>Low_std_lag30</th>\n",
              "      <th>Volume_mean_lag3</th>\n",
              "      <th>Volume_mean_lag7</th>\n",
              "      <th>Volume_mean_lag30</th>\n",
              "      <th>Volume_std_lag3</th>\n",
              "      <th>Volume_std_lag7</th>\n",
              "      <th>Volume_std_lag30</th>\n",
              "      <th>Turnover_mean_lag3</th>\n",
              "      <th>Turnover_mean_lag7</th>\n",
              "      <th>Turnover_mean_lag30</th>\n",
              "      <th>Turnover_std_lag3</th>\n",
              "      <th>Turnover_std_lag7</th>\n",
              "      <th>Turnover_std_lag30</th>\n",
              "      <th>Trades_mean_lag3</th>\n",
              "      <th>Trades_mean_lag7</th>\n",
              "      <th>Trades_mean_lag30</th>\n",
              "      <th>Trades_std_lag3</th>\n",
              "      <th>Trades_std_lag7</th>\n",
              "      <th>Trades_std_lag30</th>\n",
              "      <th>month</th>\n",
              "      <th>week</th>\n",
              "      <th>day</th>\n",
              "      <th>day_of_week</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2000-01-03</th>\n",
              "      <td>2000-01-03</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>157.40</td>\n",
              "      <td>166.00</td>\n",
              "      <td>170.00</td>\n",
              "      <td>166.00</td>\n",
              "      <td>170.00</td>\n",
              "      <td>170.00</td>\n",
              "      <td>169.52</td>\n",
              "      <td>33259</td>\n",
              "      <td>5.638122e+11</td>\n",
              "      <td>66527.159101</td>\n",
              "      <td>1.062489e+06</td>\n",
              "      <td>0.603802</td>\n",
              "      <td>1007.148315</td>\n",
              "      <td>1006.866577</td>\n",
              "      <td>1005.181213</td>\n",
              "      <td>11.310165</td>\n",
              "      <td>17.871513</td>\n",
              "      <td>39.045536</td>\n",
              "      <td>981.329834</td>\n",
              "      <td>981.059814</td>\n",
              "      <td>979.431702</td>\n",
              "      <td>11.595297</td>\n",
              "      <td>18.211773</td>\n",
              "      <td>39.399689</td>\n",
              "      <td>1.619865e+06</td>\n",
              "      <td>1.610543e+06</td>\n",
              "      <td>1.567187e+06</td>\n",
              "      <td>548848.625000</td>\n",
              "      <td>675456.312500</td>\n",
              "      <td>876143.312500</td>\n",
              "      <td>1.843575e+14</td>\n",
              "      <td>1.835394e+14</td>\n",
              "      <td>1.796116e+14</td>\n",
              "      <td>6.434157e+13</td>\n",
              "      <td>7.962755e+13</td>\n",
              "      <td>1.033992e+14</td>\n",
              "      <td>66165.625</td>\n",
              "      <td>65843.203125</td>\n",
              "      <td>64076.777344</td>\n",
              "      <td>16987.296875</td>\n",
              "      <td>20617.759766</td>\n",
              "      <td>25384.982422</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-04</th>\n",
              "      <td>2000-01-04</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>170.00</td>\n",
              "      <td>182.00</td>\n",
              "      <td>183.45</td>\n",
              "      <td>171.00</td>\n",
              "      <td>174.00</td>\n",
              "      <td>173.80</td>\n",
              "      <td>174.99</td>\n",
              "      <td>168710</td>\n",
              "      <td>2.952261e+12</td>\n",
              "      <td>66527.159101</td>\n",
              "      <td>1.062489e+06</td>\n",
              "      <td>0.603802</td>\n",
              "      <td>170.000000</td>\n",
              "      <td>170.000000</td>\n",
              "      <td>170.000000</td>\n",
              "      <td>11.310165</td>\n",
              "      <td>17.871513</td>\n",
              "      <td>39.045536</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>11.595297</td>\n",
              "      <td>18.211773</td>\n",
              "      <td>39.399689</td>\n",
              "      <td>3.325900e+04</td>\n",
              "      <td>3.325900e+04</td>\n",
              "      <td>3.325900e+04</td>\n",
              "      <td>548848.625000</td>\n",
              "      <td>675456.312500</td>\n",
              "      <td>876143.312500</td>\n",
              "      <td>5.638122e+11</td>\n",
              "      <td>5.638122e+11</td>\n",
              "      <td>5.638122e+11</td>\n",
              "      <td>6.434157e+13</td>\n",
              "      <td>7.962755e+13</td>\n",
              "      <td>1.033992e+14</td>\n",
              "      <td>66165.625</td>\n",
              "      <td>65843.203125</td>\n",
              "      <td>64076.777344</td>\n",
              "      <td>16987.296875</td>\n",
              "      <td>20617.759766</td>\n",
              "      <td>25384.982422</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-05</th>\n",
              "      <td>2000-01-05</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>173.80</td>\n",
              "      <td>170.00</td>\n",
              "      <td>173.90</td>\n",
              "      <td>165.00</td>\n",
              "      <td>168.00</td>\n",
              "      <td>166.95</td>\n",
              "      <td>169.20</td>\n",
              "      <td>159820</td>\n",
              "      <td>2.704094e+12</td>\n",
              "      <td>66527.159101</td>\n",
              "      <td>1.062489e+06</td>\n",
              "      <td>0.603802</td>\n",
              "      <td>176.725006</td>\n",
              "      <td>176.725006</td>\n",
              "      <td>176.725006</td>\n",
              "      <td>9.510586</td>\n",
              "      <td>9.510586</td>\n",
              "      <td>9.510586</td>\n",
              "      <td>168.500000</td>\n",
              "      <td>168.500000</td>\n",
              "      <td>168.500000</td>\n",
              "      <td>3.535534</td>\n",
              "      <td>3.535534</td>\n",
              "      <td>3.535534</td>\n",
              "      <td>1.009845e+05</td>\n",
              "      <td>1.009845e+05</td>\n",
              "      <td>1.009845e+05</td>\n",
              "      <td>95778.320312</td>\n",
              "      <td>95778.320312</td>\n",
              "      <td>95778.320312</td>\n",
              "      <td>1.758037e+12</td>\n",
              "      <td>1.758037e+12</td>\n",
              "      <td>1.758037e+12</td>\n",
              "      <td>1.688889e+12</td>\n",
              "      <td>1.688889e+12</td>\n",
              "      <td>1.688889e+12</td>\n",
              "      <td>66165.625</td>\n",
              "      <td>65843.203125</td>\n",
              "      <td>64076.777344</td>\n",
              "      <td>16987.296875</td>\n",
              "      <td>20617.759766</td>\n",
              "      <td>25384.982422</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-06</th>\n",
              "      <td>2000-01-06</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>166.95</td>\n",
              "      <td>168.00</td>\n",
              "      <td>170.00</td>\n",
              "      <td>165.30</td>\n",
              "      <td>168.95</td>\n",
              "      <td>168.30</td>\n",
              "      <td>168.44</td>\n",
              "      <td>85026</td>\n",
              "      <td>1.432166e+12</td>\n",
              "      <td>66527.159101</td>\n",
              "      <td>1.062489e+06</td>\n",
              "      <td>0.603802</td>\n",
              "      <td>175.783340</td>\n",
              "      <td>175.783340</td>\n",
              "      <td>175.783340</td>\n",
              "      <td>6.919959</td>\n",
              "      <td>6.919959</td>\n",
              "      <td>6.919959</td>\n",
              "      <td>167.333328</td>\n",
              "      <td>167.333328</td>\n",
              "      <td>167.333328</td>\n",
              "      <td>3.214550</td>\n",
              "      <td>3.214550</td>\n",
              "      <td>3.214550</td>\n",
              "      <td>1.205963e+05</td>\n",
              "      <td>1.205963e+05</td>\n",
              "      <td>1.205963e+05</td>\n",
              "      <td>75766.851562</td>\n",
              "      <td>75766.851562</td>\n",
              "      <td>75766.851562</td>\n",
              "      <td>2.073389e+12</td>\n",
              "      <td>2.073389e+12</td>\n",
              "      <td>2.073389e+12</td>\n",
              "      <td>1.313207e+12</td>\n",
              "      <td>1.313207e+12</td>\n",
              "      <td>1.313207e+12</td>\n",
              "      <td>66165.625</td>\n",
              "      <td>65843.203125</td>\n",
              "      <td>64076.777344</td>\n",
              "      <td>16987.296875</td>\n",
              "      <td>20617.759766</td>\n",
              "      <td>25384.982422</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000-01-07</th>\n",
              "      <td>2000-01-07</td>\n",
              "      <td>HDFCBANK</td>\n",
              "      <td>EQ</td>\n",
              "      <td>168.30</td>\n",
              "      <td>162.15</td>\n",
              "      <td>171.00</td>\n",
              "      <td>162.15</td>\n",
              "      <td>170.75</td>\n",
              "      <td>168.35</td>\n",
              "      <td>166.79</td>\n",
              "      <td>85144</td>\n",
              "      <td>1.420158e+12</td>\n",
              "      <td>66527.159101</td>\n",
              "      <td>1.062489e+06</td>\n",
              "      <td>0.603802</td>\n",
              "      <td>175.783340</td>\n",
              "      <td>174.337494</td>\n",
              "      <td>174.337494</td>\n",
              "      <td>6.919959</td>\n",
              "      <td>6.347096</td>\n",
              "      <td>6.347096</td>\n",
              "      <td>167.100006</td>\n",
              "      <td>166.824997</td>\n",
              "      <td>166.824997</td>\n",
              "      <td>3.380828</td>\n",
              "      <td>2.814694</td>\n",
              "      <td>2.814694</td>\n",
              "      <td>1.378520e+05</td>\n",
              "      <td>1.117038e+05</td>\n",
              "      <td>1.117038e+05</td>\n",
              "      <td>45964.089844</td>\n",
              "      <td>64369.164062</td>\n",
              "      <td>64369.164062</td>\n",
              "      <td>2.362840e+12</td>\n",
              "      <td>1.913083e+12</td>\n",
              "      <td>1.913083e+12</td>\n",
              "      <td>8.154833e+11</td>\n",
              "      <td>1.119137e+12</td>\n",
              "      <td>1.119137e+12</td>\n",
              "      <td>66165.625</td>\n",
              "      <td>65843.203125</td>\n",
              "      <td>64076.777344</td>\n",
              "      <td>16987.296875</td>\n",
              "      <td>20617.759766</td>\n",
              "      <td>25384.982422</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 Date    Symbol Series  ...  week  day  day_of_week\n",
              "Date                                    ...                        \n",
              "2000-01-03 2000-01-03  HDFCBANK     EQ  ...     1    3            0\n",
              "2000-01-04 2000-01-04  HDFCBANK     EQ  ...     1    4            1\n",
              "2000-01-05 2000-01-05  HDFCBANK     EQ  ...     1    5            2\n",
              "2000-01-06 2000-01-06  HDFCBANK     EQ  ...     1    6            3\n",
              "2000-01-07 2000-01-07  HDFCBANK     EQ  ...     1    7            4\n",
              "\n",
              "[5 rows x 49 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xvL3picjoSDh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bcmDFcNooR9k",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8MQxt9KmmJcW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "exogenous_features = [\"High_mean_lag3\", \"High_std_lag3\", \"Low_mean_lag3\", \"Low_std_lag3\",\n",
        "                      \"Volume_mean_lag3\", \"Volume_std_lag3\", \"Turnover_mean_lag3\",\n",
        "                      \"Turnover_std_lag3\", \"Trades_mean_lag3\", \"Trades_std_lag3\",\n",
        "                      \"High_mean_lag7\", \"High_std_lag7\", \"Low_mean_lag7\", \"Low_std_lag7\",\n",
        "                      \"Volume_mean_lag7\", \"Volume_std_lag7\", \"Turnover_mean_lag7\",\n",
        "                      \"Turnover_std_lag7\", \"Trades_mean_lag7\", \"Trades_std_lag7\",\n",
        "                      \"High_mean_lag30\", \"High_std_lag30\", \"Low_mean_lag30\", \"Low_std_lag30\",\n",
        "                      \"Volume_mean_lag30\", \"Volume_std_lag30\", \"Turnover_mean_lag30\",\n",
        "                      \"Turnover_std_lag30\", \"Trades_mean_lag30\", \"Trades_std_lag30\",\n",
        "                      \"month\", \"week\", \"day\", \"day_of_week\"]\n",
        "\n",
        "\n",
        "df_train = df[df.Date < \"2020\"]\n",
        "df_valid = df[df.Date >= \"2020\"]"
      ],
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OsEggpIUn36O",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "outputId": "e58a1a93-2ee5-4c24-f233-c27a65f27035"
      },
      "source": [
        "model = auto_arima(df_train.VWAP, exogenous=df_train[exogenous_features], trace=True, error_action=\"ignore\", suppress_warnings=True)\n",
        "model.fit(df_train.VWAP, exogenous=df_train[exogenous_features])\n",
        "\n",
        "forecast = model.predict(n_periods=len(df_valid), exogenous=df_valid[exogenous_features])\n",
        "df_valid[\"Forecast_ARIMAX\"] = forecast"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Performing stepwise search to minimize aic\n",
            "Fit ARIMA(2,0,2)x(0,0,0,0) [intercept=True]; AIC=51028.798, BIC=51289.277, Time=21.770 seconds\n",
            "Fit ARIMA(0,0,0)x(0,0,0,0) [intercept=True]; AIC=51631.993, BIC=51866.424, Time=17.188 seconds\n",
            "Fit ARIMA(1,0,0)x(0,0,0,0) [intercept=True]; AIC=51115.337, BIC=51356.281, Time=17.668 seconds\n",
            "Fit ARIMA(0,0,1)x(0,0,0,0) [intercept=True]; AIC=51039.487, BIC=51280.430, Time=18.337 seconds\n",
            "Fit ARIMA(0,0,0)x(0,0,0,0) [intercept=False]; AIC=88995.601, BIC=89223.520, Time=16.710 seconds\n",
            "Fit ARIMA(1,0,2)x(0,0,0,0) [intercept=True]; AIC=51044.921, BIC=51298.889, Time=21.332 seconds\n",
            "Fit ARIMA(2,0,1)x(0,0,0,0) [intercept=True]; AIC=51030.705, BIC=51284.672, Time=19.434 seconds\n",
            "Fit ARIMA(3,0,2)x(0,0,0,0) [intercept=True]; AIC=51028.062, BIC=51295.053, Time=22.402 seconds\n",
            "Fit ARIMA(3,0,1)x(0,0,0,0) [intercept=True]; AIC=51034.108, BIC=51294.588, Time=21.803 seconds\n",
            "Fit ARIMA(4,0,2)x(0,0,0,0) [intercept=True]; AIC=51029.782, BIC=51303.286, Time=23.159 seconds\n",
            "Fit ARIMA(3,0,3)x(0,0,0,0) [intercept=True]; AIC=51029.417, BIC=51302.921, Time=23.082 seconds\n",
            "Fit ARIMA(2,0,3)x(0,0,0,0) [intercept=True]; AIC=51027.655, BIC=51294.646, Time=23.040 seconds\n",
            "Fit ARIMA(1,0,3)x(0,0,0,0) [intercept=True]; AIC=51030.419, BIC=51290.899, Time=22.073 seconds\n",
            "Fit ARIMA(2,0,4)x(0,0,0,0) [intercept=True]; AIC=51029.209, BIC=51302.712, Time=26.409 seconds\n",
            "Fit ARIMA(1,0,4)x(0,0,0,0) [intercept=True]; AIC=51027.771, BIC=51294.762, Time=25.579 seconds\n",
            "Fit ARIMA(3,0,4)x(0,0,0,0) [intercept=True]; AIC=51031.082, BIC=51311.097, Time=26.833 seconds\n",
            "Total fit time: 346.856 seconds\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tsa/base/tsa_model.py:583: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`.\n",
            "  ValueWarning)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WNnd049BoPIm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "outputId": "0c3192bb-bb9c-4456-98b7-8f7e2aa79c0b"
      },
      "source": [
        "df_valid.Forecast_ARIMAX.plot(figsize = (10,10), label = 'Predicted')\n",
        "df[df.index >= \"2020\"].VWAP.plot(figsize = (10,10), label = 'Original')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "atuKBdRhqTP5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.metrics import mean_squared_error as mse\n"
      ],
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e70wiMTrrF9Z",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}