MSc_Dissertation_ARIMA(ver_3).ipynb

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    "colab": {
      "name": "MSc Dissertation - ARIMA(ver 3).ipynb",
      "provenance": [],
      "collapsed_sections": []
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      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KV6Glpx7GZ7Y"
      },
      "source": [
        "## Import Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gABE0OdQgtVS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "162f1871-7489-41ff-ccbe-bff35c2bb498"
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      "source": [
        "import numpy as np \n",
        "import pandas as pd \n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "sns.set_style(\"darkgrid\")\n",
        "\n",
        "from statsmodels.tsa.arima_model import ARIMA\n",
        "from statsmodels.tsa.stattools import adfuller\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import mean_squared_error"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ndV-sEkzta-p"
      },
      "source": [
        "plt.rcParams['figure.figsize'] = (12,6)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xd3KcOIHGnPr"
      },
      "source": [
        "## Import Data"
      ]
    },
    {
      "cell_type": "code",
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          "base_uri": "https://localhost:8080/",
          "height": 206
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        "id": "C6b4Gqmmk1Or",
        "outputId": "e925393d-5433-4c75-8450-c4d52a8b9067"
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      "source": [
        "df = pd.read_csv('/content/drive/MyDrive/data/ADBL_data.csv')\n",
        "df['Date'] = pd.to_datetime(df.Date)\n",
        "# df = df[df['Date'] >= '2015-01-01']\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date   Open   High    Low  Close\n",
              "0 2012-01-01  115.0  115.0  113.0  114.0\n",
              "1 2012-01-02  114.0  118.0  115.0  118.0\n",
              "2 2012-01-03  118.0  116.0  114.0  115.0\n",
              "3 2012-01-04  115.0  115.0  113.0  114.0\n",
              "4 2012-01-05  114.0  114.0  112.0  113.0"
            ],
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              "      <th>Date</th>\n",
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              "      <th>Close</th>\n",
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              "      <th>0</th>\n",
              "      <td>2012-01-01</td>\n",
              "      <td>115.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2012-01-02</td>\n",
              "      <td>114.0</td>\n",
              "      <td>118.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>118.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2012-01-03</td>\n",
              "      <td>118.0</td>\n",
              "      <td>116.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>115.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2012-01-04</td>\n",
              "      <td>115.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>114.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012-01-05</td>\n",
              "      <td>114.0</td>\n",
              "      <td>114.0</td>\n",
              "      <td>112.0</td>\n",
              "      <td>113.0</td>\n",
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          "metadata": {},
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o-wUxT0uGtdq"
      },
      "source": [
        "## Time Series chart of ADBL"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
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        "id": "CK-w6ZwDmgTM",
        "outputId": "a460d0cf-fc30-4e0f-ab2f-7f660b0b7d9d"
      },
      "source": [
        "plt.plot(df[\"Date\"], df[\"Close\"])\n",
        "plt.title(\"ADBL Stock Trend\")\n",
        "plt.xlabel(\"Year\")\n",
        "plt.ylabel(\"Price\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
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        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "GBwFp0O1Kkun",
        "outputId": "16998d75-674d-45b1-b4b8-2e94787f2cf7"
      },
      "source": [
        "df = df[['Date', 'Close']]\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date  Close\n",
              "0 2012-01-01  114.0\n",
              "1 2012-01-02  118.0\n",
              "2 2012-01-03  115.0\n",
              "3 2012-01-04  114.0\n",
              "4 2012-01-05  113.0"
            ],
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6476aea2-d11b-41b7-a784-429ffe18aaab button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6476aea2-d11b-41b7-a784-429ffe18aaab');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N2c9k0XKKaQS"
      },
      "source": [
        "# Test for Stationarity"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "rijEfBm7s7l2",
        "outputId": "1ff95df3-540d-4633-947a-ae3c1f0cec61"
      },
      "source": [
        "df['returns'] = df.Close.pct_change() * 100\n",
        "df.dropna(inplace=True)\n",
        "df.reset_index(inplace=True)\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   index       Date  Close   returns\n",
              "0      1 2012-01-02  118.0  3.508772\n",
              "1      2 2012-01-03  115.0 -2.542373\n",
              "2      3 2012-01-04  114.0 -0.869565\n",
              "3      4 2012-01-05  113.0 -0.877193\n",
              "4      5 2012-01-08  114.0  0.884956"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-20104d40-4332-4da7-b806-85cf2e096951\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>index</th>\n",
              "      <th>Date</th>\n",
              "      <th>Close</th>\n",
              "      <th>returns</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>2012-01-02</td>\n",
              "      <td>118.0</td>\n",
              "      <td>3.508772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2012-01-03</td>\n",
              "      <td>115.0</td>\n",
              "      <td>-2.542373</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2012-01-04</td>\n",
              "      <td>114.0</td>\n",
              "      <td>-0.869565</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>2012-01-05</td>\n",
              "      <td>113.0</td>\n",
              "      <td>-0.877193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>2012-01-08</td>\n",
              "      <td>114.0</td>\n",
              "      <td>0.884956</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-20104d40-4332-4da7-b806-85cf2e096951')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-20104d40-4332-4da7-b806-85cf2e096951 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-20104d40-4332-4da7-b806-85cf2e096951');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R_chi_JjxFBQ"
      },
      "source": [
        "## Rolling mean and standard deviation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "id": "OJoN62bVw7kV",
        "outputId": "98615b24-f546-4aad-b2a2-1c3c3192f0f1"
      },
      "source": [
        "# High level overview of Closing price to see if it is stationary or not\n",
        "\n",
        "rolling_mean = df['Close'].rolling(12).mean()\n",
        "rolling_std = df['Close'].rolling(12).std()\n",
        "\n",
        "plt.title('Rolling Mean & Standard Deviation')\n",
        "plt.plot(df['Date'], df['Close'], label='Actual')\n",
        "plt.plot(df['Date'], rolling_mean, label='Rolling Mean')\n",
        "plt.plot(df['Date'], rolling_std, label='Rolling Std')\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Price')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sSKgaTFusBnS"
      },
      "source": [
        "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "qqAyoPtZsKOg",
        "outputId": "85a18709-fb7d-4977-f847-800e5ccef932"
      },
      "source": [
        "# Autocorrelation Function (ACF) plot without any differencing\n",
        "plot_acf(df.Close)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z47tFpZIw09w"
      },
      "source": [
        "## ADF Test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GKKkh65Ud76u"
      },
      "source": [
        "**Hypothesis Testing**\n",
        "\n",
        "Check whether the target variable is stationary or not\n",
        "\n",
        "Ho - It is non stationary (Null Hypothesis)\n",
        "\n",
        "H1 - It is stationary (Alternate Hypothesis)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DTMDU4dRthwt",
        "outputId": "e495ed07-9627-4f66-a0fb-433897f28fc5"
      },
      "source": [
        "result = adfuller(df['Close'])\n",
        "\n",
        "print(f'ADF Statistic: {result[0]}, p-value: {result[1]}')\n",
        "print('H1: The series is stationary' if result[1] <= 0.05 else 'H0: The series is non stationary')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ADF Statistic: -1.6781735495148635, p-value: 0.4423917477805401\n",
            "H0: The series is non stationary\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GVEd5AICLjue",
        "outputId": "71043907-c041-4d86-ab8d-99e97d1485b6"
      },
      "source": [
        "# Testing the series for stationarity with differencing of 1\n",
        "result = adfuller(df['Close'].diff().dropna())\n",
        "\n",
        "print(f'ADF Statistic: {result[0]}, p-value: {result[1]}')\n",
        "print('H1: The series is stationary' if result[1] <= 0.05 else 'H0: The series is non stationary')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ADF Statistic: -32.694218028296994, p-value: 0.0\n",
            "H1: The series is stationary\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ly9k3mqsfG3C"
      },
      "source": [
        "Identifying d: the number of times that the raw observations are differenced"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hex3pTO1f65A",
        "outputId": "37a769b1-e52f-44d9-d8b1-7a92d2683c48"
      },
      "source": [
        "# The series was stationary with differencing of 1\n",
        "d = 1\n",
        "print(f'Degree of differencing: {d}')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Degree of differencing: 1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l7I5VLSag8P2"
      },
      "source": [
        "Identifying p : the number of lag observations"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "oDJSUnSbhV3s",
        "outputId": "da8bbe69-4041-4cf8-8a5d-07c4d2c94d95"
      },
      "source": [
        "# Partial Autocorrelation Function (PACF)\n",
        "diff = df.Close.diff().dropna()\n",
        "\n",
        "plot_pacf(diff)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ibnJxSPXj02A"
      },
      "source": [
        "*Here lag 1 stands out and is well above the significance line.* Hence, **p** is **1**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hTfgDEvtptMb"
      },
      "source": [
        "p = 1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UcNWEMrZi8vL"
      },
      "source": [
        "Identifying q: the size of the moving average window"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "wKUxYHTgi18w",
        "outputId": "d453d99f-1c42-481e-e9c0-32e7872266bf"
      },
      "source": [
        "# Autocorrelation Function (ACF)\n",
        "diff = df.Close.diff().dropna()\n",
        "\n",
        "plot_acf(diff)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DfPDzQ0Dkruv"
      },
      "source": [
        "*Here lag 1 stands out and is well above the significance line.* Hence, **q** is **1**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hp9uZEOlpvt7"
      },
      "source": [
        "q = 1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1lY-8PF-i6A4",
        "outputId": "ba7e3805-0bcc-44fd-9faf-353a01daec14"
      },
      "source": [
        "print(f'ARIMA order is ({p}, {d}, {q})')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ARIMA order is (1, 1, 1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "egAg_u4g7WNr"
      },
      "source": [
        "## Train/Test Split"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AKN8L5327b2I",
        "outputId": "c323a428-5ed4-4ea7-80ea-87a125b32e02"
      },
      "source": [
        "# Split Train and Test set into 70/30 percent\n",
        "X_train, X_test = train_test_split(df.Close, test_size=0.30, shuffle=False)\n",
        "print(X_train.shape, X_test.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(856,) (367,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yYyCZtAqpzv3"
      },
      "source": [
        "## Fit ARIMA Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BJJplPgIqqyj"
      },
      "source": [
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "WJg8CIp9phAl",
        "outputId": "3c638096-cda3-41ed-b57e-5541088e135a"
      },
      "source": [
        "# ARIMA Model\n",
        "model = ARIMA(X_train, order=(p, d, q))\n",
        "result = model.fit(disp=0)\n",
        "result.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>ARIMA Model Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>      <td>D.Close</td>     <th>  No. Observations:  </th>    <td>855</td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>          <td>ARIMA(1, 1, 1)</td>  <th>  Log Likelihood     </th> <td>-3706.261</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Method:</th>             <td>css-mle</td>     <th>  S.D. of innovations</th>  <td>18.465</td>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>          <td>Thu, 24 Jun 2021</td> <th>  AIC                </th> <td>7420.522</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>              <td>18:43:29</td>     <th>  BIC                </th> <td>7439.526</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Sample:</th>                <td>1</td>        <th>  HQIC               </th> <td>7427.799</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th></th>                       <td> </td>        <th>                     </th>     <td> </td>    \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "        <td></td>           <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>const</th>         <td>   -0.2875</td> <td>    0.698</td> <td>   -0.412</td> <td> 0.680</td> <td>   -1.655</td> <td>    1.080</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>ar.L1.D.Close</th> <td>    0.3136</td> <td>    0.344</td> <td>    0.912</td> <td> 0.362</td> <td>   -0.360</td> <td>    0.987</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>ma.L1.D.Close</th> <td>   -0.2413</td> <td>    0.351</td> <td>   -0.688</td> <td> 0.492</td> <td>   -0.929</td> <td>    0.446</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<caption>Roots</caption>\n",
              "<tr>\n",
              "    <td></td>   <th>            Real</th>  <th>         Imaginary</th> <th>         Modulus</th>  <th>        Frequency</th>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>AR.1</th> <td>           3.1891</td> <td>          +0.0000j</td> <td>           3.1891</td> <td>           0.0000</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>MA.1</th> <td>           4.1446</td> <td>          +0.0000j</td> <td>           4.1446</td> <td>           0.0000</td>\n",
              "</tr>\n",
              "</table>"
            ],
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                             ARIMA Model Results                              \n",
              "==============================================================================\n",
              "Dep. Variable:                D.Close   No. Observations:                  855\n",
              "Model:                 ARIMA(1, 1, 1)   Log Likelihood               -3706.261\n",
              "Method:                       css-mle   S.D. of innovations             18.465\n",
              "Date:                Thu, 24 Jun 2021   AIC                           7420.522\n",
              "Time:                        18:43:29   BIC                           7439.526\n",
              "Sample:                             1   HQIC                          7427.799\n",
              "                                                                              \n",
              "=================================================================================\n",
              "                    coef    std err          z      P>|z|      [0.025      0.975]\n",
              "---------------------------------------------------------------------------------\n",
              "const            -0.2875      0.698     -0.412      0.680      -1.655       1.080\n",
              "ar.L1.D.Close     0.3136      0.344      0.912      0.362      -0.360       0.987\n",
              "ma.L1.D.Close    -0.2413      0.351     -0.688      0.492      -0.929       0.446\n",
              "                                    Roots                                    \n",
              "=============================================================================\n",
              "                  Real          Imaginary           Modulus         Frequency\n",
              "-----------------------------------------------------------------------------\n",
              "AR.1            3.1891           +0.0000j            3.1891            0.0000\n",
              "MA.1            4.1446           +0.0000j            4.1446            0.0000\n",
              "-----------------------------------------------------------------------------\n",
              "\"\"\""
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "LocM2DIXtX9D",
        "outputId": "89c03732-a395-4379-c218-71c2b01747cc"
      },
      "source": [
        "# Plotting residual errors\n",
        "residuals = pd.DataFrame(result.resid)\n",
        "\n",
        "plt.plot(residuals)\n",
        "plt.show()\n",
        "\n",
        "# The residual mean is centered around 0"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 763
        },
        "id": "ZLkyWSBWVLxG",
        "outputId": "e8d3c42f-0160-4bad-a697-9378fa5b665f"
      },
      "source": [
        "# ACF and PACF plots of the residuals\n",
        "plot_acf(residuals)\n",
        "plot_pacf(residuals)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "FCnNG2KS15fX",
        "outputId": "5a66806a-4fce-4c66-b387-ffa1c753b561"
      },
      "source": [
        "# Predict Train set\n",
        "result.plot_predict(\n",
        "    start=1,\n",
        "    end=30,\n",
        "    dynamic=False,\n",
        ");"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e0wdZuQn-K5-"
      },
      "source": [
        "yhat_train = result.predict(start=1)\n",
        "returns_train = df.returns[1:X_train.shape[0]]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T7okNylD25fX",
        "outputId": "a8e1801c-6c29-45b4-e93a-527526e2fff7"
      },
      "source": [
        "trainScore = mean_squared_error(returns_train, yhat_train, squared=False)\n",
        "print(\"Train Score: %.2f RMSE\" % (trainScore))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Score: 2.78 RMSE\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "haaxGlsvAckn"
      },
      "source": [
        "## Forecasting Test set"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I1NZr3jE_fp5"
      },
      "source": [
        "model = ARIMA(X_train, order=(p, d, q))\n",
        "result = model.fit(disp=0)\n",
        "\n",
        "yhat_test, se, conf = result.forecast(X_test.shape[0])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AP6qBLVrAiQs"
      },
      "source": [
        "test_date = df.Date[X_train.shape[0]:]\n",
        "yhat_test = pd.Series(yhat_test)\n",
        "lower = pd.Series(conf[:, 0])\n",
        "upper = pd.Series(conf[:, 1])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GZm8_hO02cX9"
      },
      "source": [
        "returns_test = df.returns[-X_test.shape[0]:]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7tsQKLTmFpOi",
        "outputId": "07b0dd97-74b9-4250-841e-d5e6eb88d209"
      },
      "source": [
        "testScore = mean_squared_error(X_test, yhat_test, squared=False)\n",
        "print(\"Test Score: %.2f RMSE\" % (testScore))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test Score: 95.04 RMSE\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "lMHh3RAgAs1T",
        "outputId": "6c430172-2722-4ebb-f524-08b79e7cf8fe"
      },
      "source": [
        "plt.title(\"Forecast vs Actual\")\n",
        "plt.plot(test_date, X_test, label=\"Actual\")\n",
        "plt.plot(test_date, yhat_test, label=\"Forecast\")\n",
        "plt.fill_between(test_date, lower, upper, color=\"k\", alpha=0.2)\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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x4vE4npfZxQ7I1hSrqoLP58Pn81NcXEQgkNu9F9JDnXnmSRx66OHZr++88z4qK/t1Y4sy/v73/+G88y4kGNz3pe0kOAshhBCi17MsKxuKU6kkiUQC00xj2w6WZZFKpXAcG0XJrD2saWrbUmtqdoJdYWHhbkeKZSR55/z+AH/4wx/3+HGOY6Np+y+S/v3v/8vpp58twVkIIYQQBy/P83Acp211CbstGKeJRqPE4zFM08SyLBzHAdo39MisNOHz+VBVDVVVUVVFyie6ybp1a/jtb3+NYaTp128AP/lJZhfAG2+8hiFDhvLZZ8s4+eRTOProcTzxxKOkUikKCgq44Yabqazsx9atW/jVrx4gEmlB01TuueeXFBUVc9ttPyEWi2LbNj/4wY/46ldPIpVK8fOf30p9fT2u6/Dd736f5uZmGhsbuOaaH1JQUMjvfvfEPl2PBGchhBBCHHDt6xK3r0ecCcYm8XiMWCxKNBrDts3s+dtWnQC/34/P5yMQCBAMBne5SUdflLt2FnlrXuzS54wPu4jE0At2eY5pGvznf14OQGVlP+688z4efPA+rrrqOo4+eizPPPMUzz77ND/60TUAWJbNY489iW3b3Hjjj7nzzgcoLCxk/vw3+dOfnuLWW3/GXXf9jMsu+y5TppyMYRh4noeu69x//6/Izc0jEonwwx9+l8mTp7Bo0buUlpbxq1/9NtPmeJy8vDz+9re/8sgjT1BYWLjP/dDp4Hzbbbcxf/58SkpKePXVVwGIRCJcf/31VFVVMWDAAGbMmEFBQQGe53HfffexYMECgsEgv/jFLxg1ahQAs2bN4vHHHwfgRz/6ERdcsOu/BCGEEEL0Lu2T7CzLzI4YO45LKpUkGo0Si0Wz6xIDXwi9mVDk9/vJy8tB0/K77yLEHvtyqUZ73fjRR48F4LTTzuTee3+e/f5JJ00FYMuWzWzcuIFbb70BANd1KCoqJplM0tjYwJQpJwMQCAQAsG2bJ554jCVLFqMoKg0NDTQ3N3H44UN59NEZ/P73jzBp0lcZM2Zcl19jp4PzhRdeyGWXXcYtt9ySPTZz5kwmTpzIFVdcwcyZM5k5cyY33XQTCxcuZOPGjcydO5clS5Zw55138vzzzxOJRHj00Ud58cUXURSFCy+8kKlTp1JQUNDlFyaEEEKI/cNxHNLpNKZp4DhuWzC2icfjRKOtxOPxtuXYto0Ct9cVZ0aL/btdl1jsvcTQC3Y7OtwTbKs59hg8+DB++9vHs99znMwa1zsyd+7/EYlEeOqpZ9F1nYsvPhfTNDnkkMH88Y/P8t57/+bJJx/n2GOP4//9vx90aZs7HZyPO+44tm7d2uHYm2++yV/+8hcApk+fzre//W1uuukm3nzzTaZPn46iKIwdO5ZoNEp9fT0ffPABkyZNyg6VT5o0ibfffptzzjmnCy9JCCGEELvjOA6pVArXdfA8D9d18TwPz6Ptz8yxZDJAY2NrdoJdLNbaNlpMh13sQMHn0/H7A1JPLADIzc0jHA6zbNkSjjpqDPPmzeGoo8Zud97AgYfQ2hphxYrPOPLI0di2zebNGxg2bDhlZeUsXDifE088KVvaE4/HKSoqQtd1PvnkI2prawBobGwgHM7njDPOJi8vzKuvzgYgJyeHZDJxYEs1dqSpqYny8nIAysrKaGpqAqCuro7KysrseZWVldTV1W13vKKigrq6ut2+jqYpFBbm7OC4usPjfZX0R0fSHxnSDx1Jf3Qk/bG9g6VPTNNsGxXeVi5hGGlaW6NEo1FSqSRf3mkus42zl/3a80DXtbbRYg1d1ykqClNRUXKAr6bnUFWVcHjfV2foapmNVA70CL7Cl/du+XIbbrnlp8yY8RDpdJp+/fpz883/haZlNoNR1UybNc3PHXfcw6OP/pZEIo7jOEyffjHDh4/kzjvv5Ze/vJennvoDuq5z330PctZZZ3PTTdfxne9cysiRIxk8+FA0TWXDhnU8+ugMVDWz2+JNN/0XmqYyffpF3HjjNZSWlvHYYzM7XoGy44y5M102OVBRlP12y8VxPCKR5HbHCwtzdni8r5L+6Ej6I0P6oSPpj46kP7bXU/okE3xTGEZmlA28Dts4t398cdUJ17UxTYtkMoltWx0m1LWHX78/s0lHMBjuVDvC4SCxWLrtOcAwXAwjvb8uu8f7Yn/0JEVFOo7j7f7ELqRpdHjNV16Zs10bDjtsKL/97R86HHMcj1/96pHs5+3n/frXv/vCOTau69K//8DtHg/whz88vd2x8vJKnnnmuS+9lsuFF36NCy/8WvbrL/K87TNmWdnO/2/sU3AuKSmhvr6e8vJy6uvrKS4uBjIjybW1tdnzamtrqaiooKKigg8++CB7vK6ujgkTJuxLE4QQQohep33b5vbl1QzDaNuII1MO0draiuPYwLZSiPYQrKoKme2bM6N2mWOZ9YhVVUFRVPLycvfrurhC9FX79L9q6tSpzJ49myuuuILZs2dzyimnZI8/++yzTJs2jSVLlhAOhykvL2fy5Mn85je/obW1FYB33nmHG264Yd+vQgghhOhB2oNxOp0ilUplSybaN+mIxWI4jpMdDVZVpW29YQ1d1wiHw2hfvgcuhOh2nQ7ON9xwAx988AEtLS2ceOKJ/PjHP+aKK67guuuu44UXXqB///7MmDEDgClTprBgwQJOO+00QqEQ999/PwCFhYVceeWVXHzxxQBcddVVXVKoLYQQQhxIXw7GyWQSy7IwTRPTNIjH4x2CsaZlNuLQNBVN02XynBC9lOJ9cRZAD2VZjtQ4d4L0R0fSHxnSDx1Jf3Qk/bG9wsIcWloSHYJxPB5vK6UwMQyTRCLRIRj7fHp2xFhVM0uuHSzBuKfW9HaXntofRUV5lJT0P6BL/Gmast/qqh3Hxu/3Ewjsv4mYnudRV7eZysrBHY7vtxpnIYQQorcyTZNUKpndwrk9GPv9GrW1jdsF4/ZRY1XVZMRY9Di27ZBOJwgGc2V97E7wPI9EIoqu+/focRKchRBCHJRs2yadTpFMpojHY6TTaWzbbFt1IoVtm20T7sDn82WDsa7nkJ+fLzXGoleJx1NAM4lE6wF7zfZ1vPcH13XRNB2fb/9FVV33U1RUtmeP2U9tEUIIIfYr13WzE+8SiTipVBLTtLCszPrF6XSq7TwPv789GGfC8a62cw4Gg1hWz7sVL8SueB7EYqkD+pr7s2yltTXCwIGHMGjQ4N2ffABJcBZCCNFjtdcZJ5NJkslk28oUBoZhfmFbZxVNU9B1X1spRabGODc3t7ubL4Q4yEhwFkII0W3at33OfCTbVqXIrEwRjcawbZP23e2+OAFP0zSKioqkllMIcUBJcBZCCLFfGYZBKpVs2/DDaFvL2CAWi5JIJAAPz8ss2aZpatuybdouyymEEKI7SHAWQgixT75Ya2zbNpaV2egjFosRiUQ6TMLLjBZnwrHP56e4uFhGjYUQvYYEZyGEELtl2zapVGaTD8dxcRybRCJBS0szsVgsW2usKB6KoqBpGrruk1FjIcRBRYKzEEIIgGxtseM42LaDbVu0tLTQ0tJMKpUEFDIrT2WWn/L5dAKBoNQaCyH6DAnOQgjRh2Q2+bDbwrFFItHCxo1VtLS0YJrty0opHdY3DgYDlJSUdmu7hRCiJ5DgLIQQBxnP89qCcWYDkHg8TnNz83b1xqCQlxfAsjxCoRDhcF53N10IIXo0Cc5CCNGLGYZBMpkgkUjQ3NxIJBLFti0y5RSZ8glFgUAguMN64/25gYEQQhxsJDgLIUQP5nkepmmSSiWzI8eGkW6rR7ZwXRtFUb8UjuVHuxBC7A/y01UIIbqJ67qYpkkymSAej7ftjpfAsiwsy8ayLDzPaTtbQVUV/P4Auq4TDAbJyclBVdVuvQYhhOhLJDgLIcR+ZlkWiUS8bcS4kXg8gWGYeJ7TVm+cCcU+nw9N09E0jVAoSG6uBGMhhOhJJDgLIUQXcBwnW2vc2tqKYRiYpoFpmqTTKTwPVFUhGAwRCAQIhUISioUQopeR4CyEEJ3keR6pVIpUKpXdIS+VStHaGiEajeJ5mc0/MiPHGpqm4ff7yc3N7e6mCyGE6AISnIUQ4ksyNcYWjmNj2zbJZJKmpiaam5twHAdQUBQPVVXbwnFAto4WQog+QIKzEKJPc12XdDpNIpEgEmmhsbGBVCqZrT1uFwwGyc/PR9O0bmytEEKI7iTBWQhx0Pvi5LyqKpu6uqa2GmQTx7HbtpEGv99HMBiSXfKEEELskARnIcRBob3+OLMRSBOxWBTTNDusXqGqCkVFYUzTadtKOigT9IQQQnSaBGchRK/SvnpFKpXGskzS6TSpVIrm5mYsK7OddCDgx+/PfHx59YpwOIiiyE55Qggh9pwEZyFEj2MYBqlUEsdxsW0bx7ExTYtIpJmWlhZc1wUyI8iapqHr+g63kxZCCCG6kgRnIUS38TwP286sXJFKJWlpaaGhoZ5kMgEobcu7QWbXPJVAIEBhYaGUVwghhOgWEpyFEAdMOp0mFovR1NRIc3MT6XQa8LKT83RdJydHJucJIYTomSQ4CyG6XDKZJJFIkEolSafTpNNp4vEYqVQSULK1x7IxiBBCiN5EgrMQYq9lds/LbBSSThs0NzdRX1+PYWQm32maiqbpsoOeEEKIg4IEZyHEbjmOg2maxONxmpoaicWiJBIJXNfJbhTieeD364RCOYTDed3dZCGEEKLLSXAWQnRgGAaxWIzGxgZaWyOk0+m2TUI82sssgsEABQUFMklPCCFEn9IlwflPf/oTzz//PIqicMQRR/DAAw9QX1/PDTfcQCQSYdSoUTz44IP4/X5M0+Tmm29m+fLlFBYW8vDDDzNw4MCuaIYQYg9YlkUymcCy7Ox6yA0N9cTjsbbR48wuevn5+RKQhRBCCLogONfV1fHnP/+Z119/nWAwyLXXXstrr73GggUL+O53v8u0adP4+c9/zgsvvMA3v/lNnn/+efLz83njjTd47bXXeOihh5gxY0ZXXIsQ4gtcN7MGcjIJsVi0rdwiE5abm5uIRFpoX/INMitaBINBWdFCCCGE2IkuGXF2HId0Oo2u66TTacrKynj//ff59a9/DcAFF1zAo48+yje/+U3+9a9/cfXVVwNwxhlncPfdd7et1ap0RVOE6LNc1yWZTBKNtlJXV0tLSwvgkZcXIh7ftlOepmkEAn6Ki0vk/50QQgixB/Y5OFdUVHD55Zdz8sknEwgEmDRpEqNGjSI/Px9dzzx9ZWUldXV1QGaEul+/fpkX13XC4TAtLS0UFxfva1OE6DMMwyAajdLY2NC2zFsa2zbb3oSq5OSEKC4uRlEUwuEggYBsMS2EEELsq30Ozq2trbz55pu8+eabhMNhrr32Wt5+++2uaFuWpikUFubs4Li6w+N9lfRHRwdDf7iui2EYWJaFZVkkEgmqq6uJRCIABIMBcnP9FBTkZN+ofpmqqoTDwQPZ7B5N+qMj6Y/tSZ90JP3RkfTHNvuzLxwnSH5+qMf9Ht/n4Pzuu+8ycODA7Ijx6aefzieffEI0GsW2bXRdp7a2loqKCiAzQl1TU0NlZSW2bROLxSgqKtrlaziORySS3O54YWHODo/3VdIfHfXW/jBNk2g0SkNDPfX1tdi2k13uTVUhFMohFApnz7cssCwbsHf4fOFwkFhMRpzbSX90JP2xPemTjqQ/OpL+2GZ/9kU8niYaTXXL7/GysvBOv7fPwbl///4sWbKEVCpFMBjkvffeY/To0Rx//PHMmTOHadOmMWvWLKZOnQrA1KlTmTVrFuPGjWPOnDl85StfkTpL0Sd5nkciESeRSGIYaVKpFPF4jNbWCJ4HgUCAcDgfTdO6u6lCCCGEoAuC85gxYzjjjDO44IIL0HWdkSNH8vWvf52TTjqJ66+/nhkzZjBy5EguueQSAC6++GJuuukmTjvtNAoKCnj44Yf3+SKE6C1c1yUWi9LU1ER1dTWGkUJRFFRVRdd96Louk/aEEEKIHkrx2tei6sEsy5FSjU6Q/uiou/vDNE1aW1tpamokmUyQTKYwzTSel5kYm5ubi8/n2+/tkNuKHUl/dCT9sT3pk46kPzqS/thmf/ZFa2uEgQMP4fDDh+yX59+V/VqqIYTIsG0b0zSJxaJUV1fR0tKcLeJew9kAACAASURBVLnQdZ1QKEheXq6MJgshhBC9lARnIfZSPB6nubmJ2toaEokknufQfv8mJydHSi6EEEKIg4wEZyE6wbIsTNPEti2i0ShVVVuJx+Nomkpubh6FhQWyLbUQQghxkJPgLMQOeJ5HPB6jsbGRrVu3YlkGnkd2BDkvL4+ysrJubqUQQgghDiQJzqLP8zwP0zSxLBPTNInH42zduoVUKtk2iS+P/PydTxQQQgghRN8gwVn0WfF4vG1EeQum2T4rWEFVFXJz88jNlRFlIYQQQmwjwVn0Ce01yqZpkEwmqaraSjQaRdc18vLChMN53d1EIYQQQvRwEpzFQcs0TWpra9iyZTOxWBTP81CUzAS+3NxcqVEWQgghxB6R4CwOGpZlYRgGhmG0LRHXQiyWJjc3l5KS0u5unhBCCCF6OQnOotdqX/mipqaGmppqHMdu+46C3++nsrKEQMDs1jYKIYQQ4uAhwVn0Kq7rYpomkUgLGzduIJGIo+s+wuEwmqZ1OFfWVRZCCCFEV5LgLHo013VpaWmhurqKeDxGKpXCa9ueLy8vj9JSqVMWQgghxIEhwVn0SOl0mvr6OjZt2oRhpAmFggQCQUKhkGxjLYQQQohuIcFZdDvXdYlEWojH48TjcRKJONFoK4qikp+fL5uPCCGEEKJHkOAsuo1hGNTX17Fx40ZM00DTVHw+H36/n5KSUhlZFkIIIUSPIsFZHDDtG5Ck0wZNTY1UVW0FkFFlIYQQQvQKEpzFfuU4Do2NjWzcuJ5EIg4oeJ6Hz6dTVFQkK18IIYQQoteQ4Cz2C8uyqK+vY/369RhGmry8PNmERAghhBC9mgRn0SUSiQStrRGi0SixWJR4PI7rulKGIYQQQoiDhgRnsU/i8RgbN26ktrYGVVXx+/34/X4KCwulDEMIIYQQBxUJzmKPWZZFMplg06ZN1NfXEQj4KS2VVTCEEEIIcXCT4Cx2y/M8Wlqa2bp1C9FoDNNMAwo+n08CsxBCCNFH/PqTJBU5Kt8aHuizv/slOItdikRaWLt2DZFICzk5OYRCQcLhvO5ulhBCCCEOINfzWN3isLLZoTykcvpgf3c3qVtIcBYdeJ6HYRikUkk2bdpEY2MDOTk5lJWVd3fThBBCCNFNWg0Px4M8n8Lzawz656lM7INz/yU4CwBaWyNs2rSRlpYWbNtCUTIT/crKyrq7aUIIIYToZs2GB8C3RgR4fYPJE8tSDC4J0teysyx70Mclk0mWL/+Mjz76gFgsSjgcprS0jJKSEsLhvvbfQQghhBA70px2AajMUbl6TAhdUXj4g2g3t+rAkxHnPsi2bUzTbNugZC2aplNSIpP8hBBCCLFjzenMiHNJUCXHp3DGYD8vrDWIWx55vr6THyQ4H+QMw6CurpZoNEoqlSSZTOI4Np4HiqJQWFiEpmnd3UwhhBBC9GDNaZeABqG25Ng/L1O0UJNwGFbYd+Jk37nSPsayLBobG1i9+nMcxyEYDKDrPsLhsARlIYQQQuyR5rRHSVDN3p3ul9MenF2GFXZnyw4sCc4HkebmZtas2UhzcxOpVBLPg4KCAnw+X3c3TQghhBC9WIvhUhTcVpJRElLwqZng3Jd0SXCORqP87Gc/Y/Xq1SiKwv33389hhx3G9ddfT1VVFQMGDGDGjBkUFBTgeR733XcfCxYsIBgM8otf/IJRo0Z1RTP6LMMwWLt2Da2tDTiOSjAYpKSktLubJYQQQoiDRFPaY1DetjvWqqLQP6xR28eCc5esqnHffffx1a9+lX/+85+8/PLLDBkyhJkzZzJx4kTmzp3LxIkTmTlzJgALFy5k48aNzJ07l3vuuYc777yzK5rQZzU0NLBo0bs0NtZTUVFBfn4+fn/fXJRcCCGEEF2vJe0SMz3KcjpOAhwQ1lnW5HDvBwliZt8I0PscnGOxGB9++CEXX3wxAH6/n/z8fN58802mT58OwPTp05k3bx5A9riiKIwdO5ZoNEp9ff2+NqNPMQyD5uYmli//jE8//YRQKERhYZGsiiGEEEKILvdujQXAseUdSz/75WZGoDdGXVZHnAPeru6wz6UaW7dupbi4mNtuu41Vq1YxatQofvrTn9LU1ER5eWa3ubKyMpqamgCoq6ujsrIy+/jKykrq6uqy5+6IpikUFubs4Li6w+MHI8/zqK6uZt26dSSTSQD8fh+HHz4oG5hVVSUcDnZnM3sU6Y8M6YeOpD86kv7YnvRJR9IfHfWV/mhJO7y2NsWwIh//rrE5stTH0IqOmWvaMAgHVP60NE692bX94jhB8vNDPS7n7XNwtm2bFStWcPvttzNmzBjuvffebFlGO0VR9mk01HE8IpHkdscLC3N2ePxgY5omq1d/Tk1NNYWFBYRC2zYmiceN7OfhcJBYLN0dTeyRpD8ypB86kv7oSPpje9InHUl/dNRX+uP5z9O8ucUCUijAJUP92113OBxkcrnCnFyVdY0msVjXrdoVj6eJRlPdkvPKyna+Adw+B+fKykoqKysZM2YMAGeeeSYzZ86kpKSE+vp6ysvLqa+vp7i4GICKigpqa2uzj6+traWiomJfm3HQisWiLFu2FNM0djkqL4QQQgjRFQzH490ai/HlOqce4qckqFAU3Hl176A8lXWtfaNUY59rnMvKyqisrGT9+vUAvPfeewwZMoSpU6cye/ZsAGbPns0pp5wCkD3ueR6ffvop4XBYAuEXeJ6HYRjEYlGqqrbywQfvoygKRUXF3d00IYQQQvQBi2otUjaccoiPoYXaLkMzwKCwSlPaI2F5B6iF3adLlqO7/fbbufHGG7Esi0GDBvHAAw/gui7XXXcdL7zwAv3792fGjBkATJkyhQULFnDaaacRCoW4//77u6IJvVY02kpTUxOxWIxEIk4qlcLzPBRFwfM8CguL0HVZblsIIYQQ+5/neczfajEgV2VoQedKLwaFM+f9aUWabw4P7DZo92ZdkshGjhzJSy+9tN3xZ555ZrtjiqJwxx13dMXL9lqe55FIJGhpaebzz1fh8/myH8XFxbI6hhBCCCG6xYaoy+aYy7dGBDqdR0YWaZw6yMfCKos/r/S4dlzPmtDXlWQo8wCybZtNmzZSU1ODYaRQFJWiIhlRFkIIIUTPMH+rSUCDiZWd33VYUxUuHR6kKKjy/BqDJQ02Y8q2ZZsVTTZ/WZXmp8flkufv3YODB+9Yeg9jmiZLlixm06YNBIMBSkvLKCkpkdAshBBCiB4hbnl8WGfzlUofQX3PA+4pg3xU5qg8tzqN5W6rd/68xaEh5fFJg9WVze0WEpwPAMMw+PTTT4jHY5SUlOLzdf5dnBBCCCHEgfDvagvLhZMG7l1O0VWFbwwP0JDyeGOzmT1en8rsKvhhnd0l7exOEpz3s3Q6zeLFH2MYaQoLi7q7OUIIIYQQHWyJOSyut3hlvcGIIi072W9vjCrRGVum89oGk5Z0JjDXJzN/rmp2iBi9e2tuCc77USqVYsmSxViWSX5+QXc3RwghhBCig9qEy30fJnlsaZqgpvC9Ufu++9/XhwVwPHhhrYHnedSnXEYVZ8L4/200d/Ponk0KbLuYbdtEIhGqqrbQ1NSIz+eT0CyEEEKIHsfzPP68Mo1fhR+MCnJ4we7XbO6MshyVMwf7eXWDyfhym5QNo0t1SkIq87danDrIT1lO7xy77Z2t7qHS6TQffvg+S5YsJpFIUFxcIqFZCCGEED1SY9pjdcRh2mEBjq3wden6y2cd6qc4oPD0isw23eUhlXMP86MpMHu90WWvc6BJcO4itm3z2WdLsG2b0tJScnNzZT1mIYQQQvRYG6OZbbKHF+19TfPOBDSFS44IkGybD1iek9m2+9RD/Cyqtdkc7Z1bdEtw7gKe57FmzWqi0ZiMMAshhBCiV9gYddAVGJi3f+Lg+HKdEUUamgKlocxrnHmon1xfpv65KeUSN3vXNt0SnLtATU01W7duobi4uLubIoQQQgjRKRujLgPDKrq6f+6QK4rCD0YHuWZsCF/ba+ToCtMODbCi2eG2dxP8YVlqv7z2/iLBeR/F43FWrVohW2ULIYQQotdwPY9NUYfD8ru+TOOLCgIqo0o6rkVx8iAfh+WrlIdUVrU4VMV7T9mGBOd94DgOK1cuJxgMyg6AQvQQ61sdFtVaNKZ691qhQgjRlVY228zfauJ6HsubbH7zSYq0A0MK9m9w3hGfqvDTCbncMj6ErsC/tlgsa7SZuSxFc7pn/+yWtLcXPM+jqamJ1atXYRiGlGgI0UO8XWXyzMpts7X756ocVapx8kB/tr5OCCH6mnerLZ5ekcYD/rHepNX0KAwoXDw0wITK7ouCYb/K5AE+5m+1+HeNhe3C8mab740KMbiHbrIswXkPxeMxVq1aQUtLhPz8fAnNQvQgb1dZDMhVuXxUkNURh2WNNm9utvig1uZHR4c4JLzj8FyfdMn1KeT6OpZbrYnYfNpgc97hAQKalGIJIXof2/V4fo3B4QUqR5XofNpoc8GQAMf307N1x93p0iMCtBoeW+IOlx8Z5H8/N3jk0xQnVypcMaDnTRyU4LwHXNdl2bIluK5LeXl5dzdHiD7Fcj0+qrM5tlzH3xZiY6bLc6sN8v0KUwb4WR91uWRYgMH5GoPzNU47xM+WmMNDnyS5/8MkOTocP8Dm2BKF4UUaiqLQnHb5+XsJPODQfJXjK32MKdN5cY3BB3WZdZQUFAzHoyJHZXiRRv9cFa0H/MIRQvRtnzXZaAqMLN55nFvWaBOzPL57aJAxZTrnHB44gC3cPV1VuPLoIK4HmqrwX8dpPLfa4K0qi6nNJkOHdHcLO5LgvAfq6mpJJlOUlpZ2d1OE6HPerbb4yyqD+VtVrh4TYn2ry59Wpom1LWW0vtVBASZUdPyxNiiscddXclnV7PBZk817VQZvbfI4JJzZ2WpD1MHxYOogH+taHf7nc4O/rTZQFTj3MD8bow7/3NRxi9iwT2F8hc6ESp0hBRrqHkwMTloeOT4J3UKIvZeyPf738zTv1mTe3J86yMfXjwhst0iB7Xq8ucWiwK8wuuTA1zJ3lqIotN/U82kK3x4Z5KslaYYV+7u3YTsgwbmTXNdl3bp15Ofnd3dThOiTVjY7hHTYHHO5/b0kcctjYJ7Kj8eEeHxpinWtLhcN9e9w56vCgMpX+ql8pZ8PfyjAvLUx5mwymflZZker8eU63xgexPU8Xttg0pByOf/wACUhlaq4Q10yxQVDAxwS1tjQ6vBpo82/qy3e2moR9ikMDKuEfQqftzhYrsfIYp0pA3yMKNZwPGhIZia7vF9r8/pGk8PyVaYM9HNchS4lIEIImtMu79dYHFvho2I3W1GvbrF5anma5rTHtEP9JG2PeVssDAcKAgpFAYWY6dFseGyMOmyOuXxzeKDX3SUrCtAjVyuT4NxJzc3NpNMpwuG87m6KEH2O63msanEYW6Zz0kA/Ty9PM7m/j/OH+PGpCleNCVGbcPlKv93PJgnoCicO8DO5v48lDTbv19qcNyQzqqEqCud+6TbmgDyN+ydt+39fkZMJ4Gnb49MGmxXNNtUJl+q4y/AijYCmsLjB5uN6m/KQgulCxNhWpze2VKcu5fKnFWn+thq+PSLIhMoeOgtGCNHlkpbHpphDc9qjOe2yJeaytMnGduG1jSbfGxXkmPKOPxNczyNieMRNj4c+SVEaVLh1fA5DCjVczyNhebxdbaEA7T9twn6FkqDC5UcGOaG//IzpKhKcO8F1XTZsWEdeXm53N0WIPsH1PFI2GI6H6UBVwiFueRxZnCmNuPeEjv8XD83XOHQP1yJVFYVx5T7Gle/dL5SgrvCVfr4dhvVvOh4f19ssrLLQVLhwiA+fBnk+hRFtW9uuiTj8bbXBs6vSDAyrFAZUcvR9G11Z3+qQtD2OKNSydeDdLW17PPhxkiOLdS4e1rNqK4U40N6uMvnbaoP0F5YtLg4oTBngY0KFj7+tTvPEsjTnHe4yrkynX65KxPB4ekWaFc0OhQGFHF3hvybkktdW8qW2bTLyzeEQ1KHV9Mj3Kfh6yM+Ag40E506oqtpKa2srZWVl3d0UIQ4661sd/rY6zagSnTMH+1lUazF7XWa5pC9SgJHFPbdG74t82s5DdbsjinQuH6Vw16IkP38vM3HxyqNDjNjFJJ+d8TyPuZstXlhj4AF+FUYUa/TP1dgYdVgbcRhepHHB0MAev8HYF67n8eJag80xl80xE1XJbLfb/gbB9TwW1WbWls31KQS/8Iu+OKhyQj+d/nm94+9ciN3xPI8X1hpU5qpcMCRAaUilONAx4F53TA6/X5Ji1jqTWetMSoIKKdvDduHIYo0VzQ7fHhHIhuZ2iqKQ11YOXBKUwLw/SXDejXg8xurVqyguLurupghx0LFdjz+tSNOUdlnXarK8yWZdq8uwQo0zBusEdQhoCn4VSkKZUdmDyYA8jctGBGhKeSxusHl4cYrLRgSY1N/X6QmHnufxv58b/GurxbHlOpP6+/isyWZZo82yRof+uSontJWlPPBhkon9fEwZ4OPQfDVbP1ibcPnHBgPHhUPCKkMLMyP4ezJq7Xoe9cnMrefmtEdVwuGjOpsWw2PKAB8p2+P1jSZvbTGZMtDPoLDKaxtMqhMu/XJVDMfDct22a4KP623e3GJy87E5HLYXGzQ0JF3yA4rUkIseoyntkbBg+hDfdjvptcvRFW48NofmtMtnTTZLGx08z+NrRwQpDynUJF367aYGWuxfEpx3wfM8Vq5cQSgUQtOkq4Toam9szgSnq8eEWBOxmbPJ4rB8lZ8cE0LvZRNZ9taJAzLDRGcM9vP7pSmeWWnw6gaTyf19TOrvozCg8NJak6WNNv1yVb52RICSL0yAfHWDyb+2Wpx2iI9LhgVQFYWjS3UYDo7rZScEJYZ6zFpn8F6NxTvVFoeEVY4s1inKdZm3IUnM9Aj7FT6qz8zS1xQ47RA/Fw3173aCzmeNNn/9PE1DattdAk2BUSUaFw/zMb5cR1MVTh/sMGeTyZxNJh5QmaPyw6OCHFuub/dGIWK4/OLDJI8uSXHDMSEG7MHIc23C5c5FCQ7JU7l6bAjDhly/ss+lMELsi02xTH3G4PDu/y0XB1VOHODnxAEdj/fPlTsw3U3S4C5YlkUsFqWk5MAuP2e7HhujLo7nMaxwz5a6EqK3aEy5/GO9ydgynbFlOqNLNMI+lQmVep8JzV+U41O4blyIT+pt3q62eHm9ySvrTSpzVWoSLiOLNZY2ZiYdFvgVBuSpqAp81uQwsZ/O14ZtvxTVF2fR5/oULhsR5KKhAd6vtVi41eKNzSaOZ+JT4cZjMhON4qbHulaHD+os/rnJJG55XDDET8FORvtrEg6/X5qiJKTyHyP9lOeoFAdVigLKdn+Ph+Zr/PCoEBcMcalPZq5pZzP9CwMqPx4b4uHFKX7xYZJLhwc5LD/TBg9oTnsowGEFWoeNa+qSLn9ckUJTYH3U5YaFiUxfKJlb3RMqfYwr0wl2IkRvjjosbbIZlJdZu9uvtd0B0ZCfy6LTPM9jdcRhTYuDpsCgPBkx7s0kOO+G4Si8tNYgZXt8/YjAfvmF7noeW+Muq5odVjbbrI44GG0TB0J65t3pUaU6+X6FY8pl+SrR+3mex/98nlkK7hvDMxPGdFXhzEN73pqdB5KuKkyo9DGh0kdD0uXfNRaLai3OP9zPuYcHqEu6fNpgUxV3qE64tBoe5x3u56xDdz8q3C6kK5w80M/JAzN9rQX9xGJGdm3pPL/CmDKdo0s1igImczebfFJvcdahfgr8KkVBheKgSkCD+Vst3q6y8GsKPzkm1OlSmvIclfJO3G4ekKfxX8fl8MSyFE+vSO/wnLBf4cdjQrSkXRZUWaxodlAV+N6oIH4VahIuBYHMm48P6iyeWp5GV6AiNzMZ87zD/TvcPOLzFpuHPk6xs33LdAV8Wibgxy2Pa8eGDmj9uOgdkpbHMyvTfNx2J2dQniqT9no5Cc678OHmVn690kerldn8IGJ4TB/ipzbhsiaSWRvxzEP9mduie6Eu6TJ7ncHK5syKAZC5dTmxn4+RRRoembVr10Qcnl9jAPCvLZlRmHy/vGMVvdfH9ZnavUuGdSw7ENuU5ahMHxJg+pBtK1FU5KicMbhr31zk+FScHWzIoigKFw8LMLm/j6dXpHhxrbn9OWTKMc49PLDf6s+Lgyo3H5vD8mYHw9kWYwv8CpYLTy1Pc/+Hycy5AYXph/uZPMCXbc+4LzzXhUP9rGt1WNLgUJ1w2BpzeWJZmh8eFcTzMptKpGwoCiu8sdEkz69w5/E5bI27RAwP0/EwHNrqsTN/thgeDU02i2otCc592LpWB8vxOKJo213i9a0OM5elaDE8JlTofFBnM1j+jfR6Epx34YWlteToHv85JocNrS4vrDVY3JB51+hTM8tRPbEsxa3jcxjUiZolyIy01SZdljY6/N9GE9fzGFumM6JIZ0SxRvGXQsT4isys/FbDZXXE4em2XxLXjg3RT2qdRC80d5PJC2sNBuWpnDJI1hbt6SpzVW4dn5MJji60tE3+i5oeR5Vqe1R7vLc0VdnpAMWt43NY2mjTP1dlRPGuS9tURWFYoc6wwsxz1SZc7l6U4NefpL50ZmZ0+/zDMyUqOytTaffbxUk+bbD52jCvR27YIPavhOXxm0+SGA4MyFP5xhEBNsVcXlprUBRQuHl8DkMKNI4ptzpV3yx6NgnOu/DLc4bzzjsLKSnUGVYIY8p0VjXbDAxrDA6rxEyP+z5M8quPk1w9JsQRRTvuzqTtoSvwfxtN3qu1aGybQHNovsoVo3M6dcuyIKByXIVKSVDld0tSPPBhkh+PDZGrK7QY3k5n6ArRk1TFM3dPxpTqXD462CdrmXsjRVEoalviane7mh1o5Tkqpx6yd6Pwlbkq90zMpTbp4lMzZSwhXWF9UuGdTSlOGti5N3ZjynSWrTKoSbiyfF4ftLDKxHAydzTe3GzxUNsbsWPLdf5jZDBbBtU+ECZ6N0lbu6DGa6iMLyWsFuIpGoWKxhH5Gq7qw037CKt+7jpa47HPHP641OSi4Xk0pRX65aoMyMssWv7U8hQNKS+7m8/oEo2zBuuMLtX36hb14QWZmr/fLk4xY3EKVQHTgXsn5hIOb3++7Xo4Hjusi/Y8j3drbGw3M+q9u1EVIfbV39cYhHT47pFBWeFA9AglIZWSUMeffYeVB5lQ0vl/n5nRcIMljbYE5z6mJuEwb7PFiCKNsw8NcNIAP6tabDRF4ehSTe5AHIQkOO9C0YKbmFL97m7POx9AA9ZCyvOTwk+KAGnPz0lqgEB+kBR+/P4geUE/XkLHTfnwFB1X0XFVPfO56sNTNFxFx1N1XKXtHDVznqOFcFUfBaqfe0fo/PdKm6Tnp8n18fcVJkc0O4wuUrMlHEsbbZ5ekSZpeRyarzKsUOeIIo2hhRoBFZ5fYzBviwXAK+tNTh7kozbhUhV3cTz4yTEhCdOiy9QlXZY3OVw4xE+eX36ZiINHcVBlcFjl0wabsw6V3RF3xHY94pZHgV85oGEyZrq8U22xJeYyZaCP4Tu5M7w3ljTY/PdnKXRN4Wttu2Lm+JTttssWBxcJzrvQfOrvWb7wRQrz81A8B8VzUV0L1bNQXRvVNds+N2mIpbGtNP2DNqZpYJhpFDtNv6CF3zMpcg00J4qasFBcG9XLfLR/rng2qufsvlFfcGr7J34yJXkbwdyg4SiZID7W1fiWqqPm+EiaGqkaDbNGxyITxL/j6lyZHySck8viiI+WTX5GaX4Cfh9VaZ3IsgBD+uWwpMVH/8JcivMywd1V/bhK25+qH1sL4mhBUGSkRezcoloLBXa5m54QvdWYMp1/rDeJmq5M3v6S9a0OTy1PUZf0KAsp3DAuh7L9WPKzNuJQFXf4vMXh43obx4OQBh/U2Yyv0LEdGFqoMSBPzW7Yk7Q9fGpmneT+eZm7xjtbwcpxPV7dYPDyOpNBYZWrx4S2m58kDl5dFpwdx+Giiy6ioqKCJ554gi1btnDDDTcQiUQYNWoUDz74IH6/H9M0ufnmm1m+fDmFhYU8/PDDDBw4sKua0aW8QD7NoSEo+SWdfszmL33dvEcv6KJ4Tls4tzNhve1z1bXQ3HQmrLsWmmuiuBaaa6E4aWwzRY5us6EpSU3MxLEsSgMuY4s9dGwCnk3AtUmbFmnLwrFtBvgMwmoUPZVisJ5CVc3M81lu5l9GGtgAYwEiu2++2zZq3h6sLcWHiR/Nn4OjBXDVQNvouR9H9WfO1QI4aghHC7Qd+//s3Xl0nOV5N/7vs848s0ijdWRb3uQFs9mGBBLXTggimF8izJLA2zRtWlz40SalLoHSrOXkkALNAuH9nbzJgWYhfRPyppAAeUMSCE7AIWwNAbMvxsirNJoZafbtWe7fH8/MSGPJtmwtM7K+n3N0ZD2z3c9laeaae677usvHy4m5rXhgKwZs2Tt639XLNUDik9Vc4AiBpwdMnNQyfgEs0YlgfbuKn+8u4aWYjY0L58bv+J6UjR+9UYBHkeDXJAQ193tgzPeQR8JK3+Ga8h2Z5Qg89E4JD/WXENIlfHSljl/vKeHWP+awvkPFpSt0BCd4k1GwBBJFgbDvyLPTjhDVxaAFS+Ch/hIGMg5eiLmL+H0q8IFud6fMdkPGL94p4Vf9JTR7pOp1ALc7jF+Tyt1SzOqxhX53F82VIQWntSnQZAm/2VvCYwcySBYF3tPl1jAfyw6bNPdNW+L8n//5n1ixYgUymQwA4Otf/zquuOIK9PX14cYbb8R9992Hj3/847j33nvR1NSE3/zmN3jooYfw9a9/HXfcccd0DWNuk2QISYYtazi2uWdXMOiFlC6gSwi8k3QgB2W8cYQ/6IHDDUPYgF3E84N57E/kcWariXfiGUTSRWQLRagw4YGJdt2C4pSg2Hks8xXRbdjo8trwyyaKJRMvR3MwUMK7vSZUOw/ZTJUTfzf5l50SFKcIWViHGcnR2bIHlmLAlj0QdtHz1wAAIABJREFU5cTaljUISYOkGygKHbbirU3Kx3y3ZQOW4h1N6ivXk7TRpF3xwpF1CM6oH7enBywM5QUuXsHZZjoxLQ66m768ELWwceHc+D3/v7tLOJhxqjOvWdPtEHFomixLOXQaMpYE3RaJh1vQnjEFXopZOCuswhbAN/6Ux66kjQ1dKv7iJHeR3KmtKn72dhFPDph4J+m2pOxpVuBVJfzhoImnBkzsTtooOUDLmC3TJcldUO9V3IR+T9rGSzEbzR4JrV4JWdPd8r3FK+GCpRp6F+to0qSanskfWenBlh4dqgTsSzsoOgJtXhnNugRFluAIgWhe4EDGxr60g91JG88Mmnj8gAldBnRFQsYUODOsY0NYxvoOlTXM89C0JM6Dg4N47LHH8Pd///e4++67IYTA008/jdtuuw0AcOmll+Kb3/wmPv7xj+O3v/0trrnmGgDABRdcgJtuuglCsIXPdJIlCStCx5/kCUkBVB/Wd/uwvvxhwMKF7nfLcdvpVd6N5yy3vdjPIyaGhtyn27BPQrwgYDnubf7XKYEjbtrizpwXq8m0+92E7BShOEU36a5eblaTb8UxoTh5KHYeil2CLEqjJTSOCdVMQS3lyrevlNWYx52oC8jlhLuSdJeTdsVbnQEXslZN0m25knh74EhjE3etXOIympTXlr9U7sPjvlrMkrcTNn6+u4hUSeC9CzTYQiCeF9WPMjt8Mta2K3AEsL5DrenbK4TAvnKv24qSLTBccG//TMTC8iYZZ4VZHUYnJklyN455asCEaYuG3+QiknOwM2ahb7le0yvcEQI5002Cs6ZAvOAgbsrYPVzCS3ELrw7b+PPVHuzPuBt1+VSp3P9a4LVhG8mSwHNDKhzh7kB51anemvKsJU0Krj3Dh5fjFr61M4/bn89DgtutZTDnYKFfxsaFGhb4ZbydtFFp3W05wAtRC0IARRtQZeDcxRqKlsBwUcARwLb1Xpx+lH0VtHInnyUT9FOWJQlhn4SwT8aZnaPx2Jt2sH1fCQUL+NAyHeu6/UinJ96Qh0580/Iqdsstt+CGG25ANutubToyMoKmpiaoqnv3XV1diEQiAIBIJIIFCxa4D66qCAaDGBkZQWtr62HvX1EkhEK+CY7LEx6fLqWSikDAi2DQO2OPMZ1kWZ6VsbY0j/67CcBftxr4awADGQvPD5awc8jEaZ0yOnwK/s+rWRQVDe3BI/2qeQGMbwkiAFjlr+oxIVCwBAxNhu0I3PNKFmct8WBN2/gZHlmW4TjO+IerlMPYRciWm3hLlYTcdktgHKuIn748jGIhhw69hEWGgy7DRqfHRpNmQbaLEGYBwsxDdYrQhAnFzgGlEmzLhBclyHYeqpWHhAnGMAkCMhzFC0cZnSEX1X97YKs+OOpo3bkYO5uueOEoHghZBZIa2scsOhWS4l5X8SLj6DiYl7E3I+NnuyzIqo6gx4v73rIgICOoS2gzFISDCt6Im3ih3Mf8R68XsaJFhQS33WKm5O5iNxGPAnQFFPzdmUE0N9V/Jm62/k7mCsZjvOONyYYlMh7bn8Segowzujx4NVbC0weK+Ngpfvi0xinfsB2B/7MzCVUGLlwTQNBbm0Q2H3L9ynPpwbSF259N4buvFKBI7gxs0RbwqRIMTcKiJhXvb1Hxf99yk+G/Pt2P81dO/Bq9IQisW+TDW8MW3hg28dawiQ3dXvyPU3yH7cXtCLdDVbIoIEtA0ywtXj+9CTh9kb/6M/9mRs1kLGzbi6YmY0bzvOMx5cT5d7/7HVpbW3HaaafhmWeemY4xjWPbAolEbtzxUMg34fHpUiqVkMkU4PHMjXeWwaC3ru+CAwDeF5bxvrA7e/HmiJtk7YsX0HQMv2pCCLyVsLGsSampHUsUHdz9agGvD9v41DoDliPwi10F/OadPP6fpTraDRmtXgndAcWt1ztKPHKmjt/tB/pTHpzSquDdYRVBj4yiLfCDXQU8m7XQt0zHK1kHu5I20sNuYrg6pECTgddHRmdDALcmTpIARwABzf1IT5YEWjQHzYqJJtVCm2Yi7LURkE0s9BSxbySDDt1CT9DBAo8FFWNm2+1CebbchOSUYFsl6DCRKxQBu4QWJQavKNTOxAu3/v14bKv8FxUBeAFLLiflQoXIq7D9GkyosCUVKUtFqqjAguYm47oKLWhA130wFS9M2YCjeOHRPVBVzU34Exqc1NiZ+NGZeruS+EvajM+y1/vvpNEwHuMdb0yWeAQ8CvD7/hzaVRu3PZ1zyxciJVy4XMcZnWp1xnOy/jTkdoRo9kgIedyygmaPhCZdOu4+6D9+o4CXoiauOMUL1TSRNs0jXr8SjyCAfz3LwGvDNjoNGe1GpYyidhzvC/vhVSX4VOmocezxAT0+BR/qdpP3bKZ41PFX0vz08T3VTRn/ZkbNZCwymQJSqfyM5nmH09ExQX/fsiknzn/605/w29/+Fjt27ECxWEQmk8HNN9+MVCoFy7KgqioGBwcRDocBAOFwGAMDA+jq6oJlWUin02hpaZnqMGbQ8S2KIKClvAhspDA+hlnTfYE59Ik/lnfwi3dKeOKgibPCKq4+zQtJkvBcxMT/fr2Iki3QZkj41ot5tHkltHgkBHUJD+4efQYNahI+f7YP/oDAO0kbQ3kHPc0KOsb0as2ZArf9KYc9aQctHgnPRy38+M0iVocURHIORsrbq1+43H0TIITAUF7ghaiF3+0vwatI6F2soTugwBbuNr15q1Kq4ralWuiX4QggbQrkLQ/ylsDrBYE/JB2UnNEEO28J2IPuQhavIiFVEgjqEk5pdbddH8w6OJB1ULQBXQZK5QlsTQY+uETHxT16bRyFGC1tERaCPgW5dLbcucXCSN7Ez9/KIFso4H1hgQVeC+0eG02yWU283fKXQrW8RSovUK0sVG0WFlocE3I5cZccE4pZhFLIu8n+FOrWLdk7poTFTaYr7Rmd8veay2sWjFbKZyoz8aOtHiuLVw3bD5F33MvKt6vUs7OOnaZCUyS8t0vDEwdNHMg6KNkCf7XGg1/vKeGulwsIahI2LtRw/hLtiK0+HSHwyB4T/Skbfxya+G9JAhDQJYR0CT3NCtZ1qDi5RYGmSHhzxMKP3ygiknOfLLoDMlaUF7ntTTnYvs/E+Us0bDqOWmxZko664RYXANOJbMqJ8/XXX4/rr78eAPDMM8/ge9/7Hm677TZs27YNDz/8MPr6+nD//fejt7cXANDb24v7778fZ5xxBh5++GG8973vbdj6Zk3T0NLSilQqiaamQz+8oqNp8UiQAAwXa0sVBrMObvnvLLoDCq4708BIQeB3+0t4KW5jIOted2Wzgv+OWDiQcd9pHsw6WNYk46pTfQhoEv6/nTnsTjq4pEfHhT0eFG2BkYJbf/29V/K45dkcFDmPxJjH7mmWcXZYQ8kW2L7PRMYU+Md1Bta2K9ifcfDfEQsvRC0sDsq48lQda1pH/zykcu3bBUt1XLD06LuUbThKy7WcJbAnZWNlswJTAK/FLbwUt2E6Ai0eGUM5By/GbcgAFvhlbFqoIeyTsT/jVLcW/nW/u0J8V8LGJ9d6qy2wSg7wSlzBSFEG4IHHo6FY9CJrCrwxYmNXwoauAFefbmB5uR4wU/6aLpJjjkm8SzWz4m7deg6KXUnuD6lrt4tu4u6UahL2SocZzU7DW4qOq4lXnNJxl8VU2LJe7uLiqU3MJbXc5cVbXYw6PnEvL0RVjNGuMWPr1xW9/KbAqPZsZ1eYE8+Fy3U8OWCiP+Xg/z3Ni/d0aXj/Ig2vDtt4fL+JR/aW8IeDJk5vV7C8WcGmhVrNLHTRFvjR6wU8OWAhoLlv0C9f6UG23GkiURRIFt31BMmSu4bg6fICNo8CnNKq4s2EBUOVcE63BiGAPWkHv9tv4jd73Znld3WquGwl+00THQ9JCDFtU6qVxLnSju7Tn/40kskkTj75ZHz961+HrusoFou44YYb8Nprr6G5uRnf+MY3sHjx4iPer2nadSnVAIBcLoenn34STU1N0LT612ceSSN+fHT9jgxOb1dxxSluDVS65ODf/5hDsihQsN2yhwNZGwULWN2i4PQ2FWvbVXT6JPxsVwmD5US6JyRj85LRmdWSLfBsxF29fejCw7cSFn6zx4ThUXBKSEKXT8arwxaeHbSwL+Pe35oWBZeu9GBF89yeYXxm0MTdr7ozWX9zihd/jFj474iJwmHasiwOyDi5VcEHl+gn5KxQJWFXyrPehybdsmPC75VRyGbHXD56m0p5jGIXIIlyu8dyUu4m/ZXrFae82BQAHEkZsxHSBBsgVTY/GlPecuhsfHVBaTWpr7RuPPRyA5ZilDvEqNWSmEZ83qi3qcbkmUETRVvg/YvGv8k+kLHxo9fd2eBkye0d3OqV4E4zAKmSg5wFXNSj46KeySW3pu2+KX4hZmFn1ILlAJ87y1fT/cJ03EVuAU065m3T+TtSi/EYNZOxSCYT6O5egp6eFTNy/0dypFKNaU2cZ0o9E2cAGBg4iJdffgmdnZ0z/lhT0Yh/zP/2bBZ+VcKnz/Qhawp8/bkcIjkHnz7TwL60g1/3l+DTJHxyrXHMT+ZHM1E8BrMONBnjttidy/pTNr61M4/hooAqAe/pUnF2l4YlQfccAwEvMpkCNFmCl9tcT//fSWVjpHKJi1uqMvFM+9ikvtKz3Z1VH7MRkmNVy2rcDZLM6iy8aueqHWgkx4QijlybetghQxotg1F02FJtYj1+Jl0f0099tPOLkDTY5X7s1iGXj+3pbiueObVB0mw8lwrhdqF4KW7VdKPRZGDTQg2rj3OHOyEEbDG+DG4qGvG1pZ4Yj1HzMXFmb6hJ6OpagIGBg8hmM/D7A/UezpzS6pExkHOQtwTueD6HgayDf1xvYFVIxaoQcG63NqulOl3+EydhrljWpOCL7/Hh4T0lvLdLw+JgbYIS9MiQSifeeTcMSYajeNzkUQvi6EubppFwyjPnpdFZ8zF90sfubjq62LTSS929nUd14BSyY5J6E5qZq16uiBJkuzjl2nVb9hxS4qKNKWGp1KXr1YWi9phSF7cXuwFbqW3bWOkwU9PacY5sjiRJEk5pU3HKUeqFj+d++f6YaOYwcZ4ESZKwbNly/OlPzzFxPkYtXgkvxx38z+fz2Jt28Mm1Rs3Ckkatb59rmnQZl69ie6R5R5KrPcIt9fiem45lxqgyAz428R6dTR9bwjJ+oyPVztUcG72sBM3KwFuMVjdEGjtbf7x165Xyl5ouLmPq1SubJTlyucRF8VQv1w0/mkyMJu1j69qlsb3c9fL9zm7PdSKqHybOkxQKtcAwDJRKReg6F1VM1uoWBY/tN/FOysZVp3mxvoO/ckRzlZBV2FBhK8asPabkmNW682pCPaYUxq07L4y5vDQ6C++UZ8sdN6mv1Kurdg6ymTxkMerx72JaLX2pJORSZTMkTzXxHlfeIutjSlyMMTuXauU3Q6N1646suzvLwt1dVlT/rUBI8rjLAJmJPNEMYRYzSbIsY+XKVXj55ZfQ3s7EebLe1anhf52rwnQAg58fEtExErIGU9Zgak2z8GBuvXqTX0EulT6kn/qY2XJR6eRSrC4qrexmOprcV0pcCtDNxLia90rt+lQ7wRyOI6k1iffhS1w8bgIOpZx4j35HOTnXvToKJVFNzO3qLH1lZ9RD71uHXW4r2eglM0THionzMWhv74DX60Uul4PP11g72TQyVZag8rmTiBpduV7d1rwo6bPw8ljuuV5Z8Fkzo24XyyUubtIuCQeScAA41X9LwoZU/hlj/u1+WVDtAhQ7N5qwl1s/KnYBupmsJv2SsN3bwBn9d/nnqbIPm7R7q2UuY2fZa8tr3Lr4mln6cXXtGsaW0IztGEM0E5g4HwNFUXD66WvxyisvIRaLIRQKVbcVJyIiOiaSBEfxwlEadH2CEJDgIOjXkEnn3E4wwoZsF6CObc04Zha+Ui5Tm7SPvdysdpjRzNToLP3Y29tFyMeZtAtIh9Sl1ybWjqyXk3YDjuypTcjLmyhV2j6O3n7MfSgeqHozZFuqltDQ/MKs7xg1NTXj7LM3YHBwAG+99SYURebmKEREdOKRJLeEQ9HhKG4iawOA1jSz3WOEKJey5GsWoY52iCm3dnTyY8pf3Bn1al27nR/dQbVSDy9KUM0cjEJ+TAeaUnkR6vF15q0sQh3berHSunFshxh31nxMXbviPWQmvtLmsVJe46k5XpmJ54x6/TFxPg6KomDRom60tbXj2WefQbFYhMfDumciIqIpk6Rqt5hZIUR5Nt0sLyYtQLHyY3Y1re0Q49csmNl0zSLUsRsluYtZ89DsLGSztstMZTHr8SfqitsvXfFM0CFmdLbckfRDylv08SUu0qF16WM70GjlzZLmTv/12cLEeQq8Xi9OOeVUvPDCn9De3s7WakRERHONJEFIox1jjrat0JQ3/RBigvKWQzZROqRDjFxOzGsvN8ck9yZkpwhvMVaeqT+kBOY4O8Y4kMuz5vohJSxuwi5rHpQcpdq60VIMCFlzd0CVVHd31PIOqEJS3e4xEy4mLSf9sre8QFWB7BzfBk8zjYnzFLW3t2PRom5EIgNoaWmt93CIiIiokUmSO2OMWfykWtjVxNvtAlPb1nHsJkmKUyiXyLiJuXSYpF2xi9CcLDSrANkuVeveZceanoWlkopXm78NYPZ3DjwSJs7TYOXKVYjH48jnczAMdtsgIiKiBiIp5TKM6e3BftjZ9/JCUnfTJMvt1lKe+R5N2kdn3MduouR2drGRK1ow/d3TOt7pwMR5GmiahrVr1+LZZ5+BrutQFIaViIiI5ilJgSMpgKy7C0qPQzKZQLfaeJOR7KMyTZqamrFmzcmIx4dh28f7a0JEREREjYpTo9No0aJumKaJPXv6Yds2/H4fSzeIiIiIThBMnKeRJElYvrwHixcvQTwex969/YhGo+jo6Kj30IiIiIhoiliqMQNUVUU4HMa73nUWuroWIB6P13tIRERERDRFTJxnkCzLWLPmZIRCIYyMDNd7OEREREQ0BUycZ5iqqjjttLXw+wNIJpP1Hg4RERERHScmzrNA13WsXbseHo8HyWQSQhzfVptEREREVD9MnGeJx+PB+vVnoqmpGfF4DNFoDNlstt7DIiIiIqJJYleNWeQmz2egWCwikUjg4MH9iEajaGtrgyzzPQwRERFRI2PiXAcejwfhcBgdHR3Yvftt7Nu3F45jQ5JkCCGgqip0XYeu61BV/hcRERERNQJmZXUkyzJWrlyFFStWolQqoVgsoFAoIpvNIJ1OIZFIwHFstLS01nuoRERERPMeE+cGIEkSPB4PPB4PmpoAoBMAUCqV8MorLyMWi6GtrQ2SJNV1nERERETzGQtrG5jbjWMdFi5chGh0CLZt13tIRERERPMWE+cGpygK1qw5GatWrUE8HkM+n6/3kIiIiIjmJZZqzAGSJGHZsmUIBALYvXsXYrEoAAm6rqPJre0gIiIiohnGxHkOaW9vR3t7O0qlEtLpNPbt24toNIrW1lYoilLv4RERERGd0FiqMQfpuo62tjasXbsOK1euwvBwHMVisd7DIiIiIjqhTTlxHhgYwCc+8Ql8+MMfRl9fH37wgx8AABKJBLZu3YrNmzdj69atSCaTAAAhBP7t3/4N559/PrZs2YJXXnllqkOYt2RZxrJly3Hmme9GPp+vxpiIiIiIpt+UE2dFUfDZz34Wv/zlL/GTn/wE99xzD3bt2oW77roLGzZswCOPPIINGzbgrrvuAgDs2LED/f39eOSRR/DlL38ZX/rSl6Y6hHmvtbUNZ5/9XgQCQcRi7nbeqVQKlmXVe2hEREREJ4wpJ86dnZ049dRTAQCBQAA9PT2IRCLYvn07LrnkEgDAJZdcgkcffRQAqsclScL69euRSqUwNDQ01WHMe4Zh4N3vfjf+7M82Yd269ejsDCOVSiGV4iw0ERER0XSY1sWB+/fvx2uvvYZ169YhHo+js9PdyKOjowPxeBwAEIlE0NXVVb1NV1cXIpFI9bp0/CRJgmEYMAwDHR0dWLJkKV577RUMDQ1B01RomgZN06FpGmSZ5e1EREREx2LaEudsNott27bh85//PAKBQM1lkiRNadc7RZEQCvkmOC5PeHy+OjQeoZAP4fAmxONxZLNZZDJppNMZZLNZlEo2AIG2trYTNomWZRnBoLfew6g7xqEW41GL8RiPManFeNRiPEbNZCxs24umJqPh8rxpSZxN08S2bduwZcsWbN68GQDQ1taGoaEhdHZ2YmhoCK2trQCAcDiMwcHB6m0HBwcRDoePeP+2LZBI5MYdD4V8Ex6frw4XD03zIxTyIxRyZ/WFEDBNE/v378Pu3W/D7/fD52usX8zpEAx6kU4X6j2MumMcajEetRiP8RiTWoxHLcZj1EzGIpMpIJXK1yXP6+gIHvayKU81CiHwhS98AT09Pdi6dWv1eG9vLx544AEAwAMPPIDzzjuv5rgQAi+88AKCwSDLNGaZJLmbp/T0rMDZZ78HABCLxbilNxEREdERTHnG+bnnnsODDz6I1atX4+KLLwYAXHfddbj66qtx7bXX4r777sPChQtxxx13AADOOeccPP744zj//PNhGAZuueWWqQ6BpqCpqRlnn/1e7NnTj/7+3RDC7ZTi9XphGEa9h0dERETUMCQhhKj3II7GNG2WakzCVONRKBSQzWaRSiURj0cxMpJAc3MzPB7PNI5y9vDjNBfjUIvxqMV4jMeY1GI8ajEeo2YyFslkAt3dS9DTs2JG7v9IjlSqwS23qcrr9cLr9aKtrQ3Ll/cgFovhtddeRSaTQUtLywm7iJCIiIhoMpgJ0WG1t7fjve/dgCVLliIejyOVSsE0zXoPi4iIiKguOONMR6RpGlauXIWuri7s27cPIyPDSKWSEALw+30wjBOvGwcRERHRRJg406QEAkGcfPIpANz2g+l0Cm+++Qai0ShaWlqgqvxVIiIiohMbSzXomGmahtbWNpx99ntx8smnIJ1OY2RkGI7j1HtoRERERDOG04R03GRZxqJF3Whv70B//zs4cGA/Kk1aNE1FU1PzlHaMJCIiImokTJxpyjweD046aQ1WrVqNfD6PfD6PWGwI+/fvh9frRTB4+LYuRERERHMFE2eaNrIsw+/3w+/3o729HYsWdWPXrrcQjQ4hEAhyQxUiIiKa05g404wJBpuwfv2ZGBkZxptvvoFYLApJkiFJgGH4mEgTERHRnMLEmWaUJElobW3De96zAfl8HoVCHtlsFgMDBxGNRtHU1DRndyYkIiKi+YWJM80KSZLg8/ng8/nQ2tqG7u7FiEaj2LXrTaRSKTQ3N0PX9XoPk4iIiOiwmDhTXUiShM7OTrS1tWFoKIJdu3YhlUpBkiRIEuDz+eH1eus9TCIiIqIqJs5UV4qiYMGChQiHu1AoFFAo5JHL5bBv3x6WchAREVFDYeJMDUGW5ZpSjoULFyEajeKtt95EOp1GMBhkAk1ERER1xcSZGpIsywiHw+jo6EA0OoTdu3chHk8DAIRANckmIiIimi1MnKmhuQl0F8LhLliWVS7lyGPv3n5Eo0Pw+dy+0UREREQzjYkzzRmqqiIQCCIQCKKjowOJxAjefnsXotEoPB4PvF4PNE3nNt9EREQ0I5g405wkSRJaWlrxrnedhWQygYGBAaRSSYyMjMBxbKiqCr8/XO9hEhER0QmEiTPNaZIkIRRqQSjUAgBwHAe5XA4HDx5APD6EXK6I5uYQFEWp80iJiIhormPiTCcUWZYRCASwevVJ8HpPxquvvoW9e/fAtm3IsgRd16HrHm62QkRERMeMiTOdsLxeL3p6VqC7ezHS6TTy+RxSqRRGRoaRTCbh9/vZmYOIiIgmjYkznfB0XUdbWxuANgCAEALDw8N45523EYtFoeseBAIByLJc34ESERFRQ2PiTPOOJEloa2tDW1sbUqkk9uzZg1gsCiEcABIkSUIwGISmafUeKhERETUQJs40rzU1NeP009dCCIFSqYRisYBEIoH+/ndgmiYCgQC8Xm+9h0lEREQNgIkzEdxZaI/HA4/Hg6amZixa1I1YLIZ33nkb0WgUsixD0zRomgaPx8OyDiIionmIiTPRBBRFQTgcRmdnJ1KpJHI5d2FhNpvByMgIAIGmpmaWcxAREc0jTJyJjkCSJDQ3h9DcHMKCBQsBAMViEUNDEbzzzjswzSR8Ph88Hg97RRMREZ3gmDgTHSOPx4PFi5dg4cJFGB4exv79e5FKpWBZJiRJKifbzVAU/nkRERGdSPjKTnScFEVBR0cHOjo6AACmaaJYLCAajWLv3n5Ylg2/3w/DMOo8UiIiIpoOTJyJpkll8WAgEMTixUsQj8fR378bsVgUkiQDEFBVFYFAgLPRREREc1DdXr137NiBm2++GY7j4PLLL8fVV19dr6EQTTtVVauLC/P5PIrFAkqlEpLJJAYGDpRno30wDO5cSERENFfUJXG2bRs33XQTvv/97yMcDuOyyy5Db28vVq5cWY/hEM0YSZLg8/mqW3uHw13o6VmBeDyOvXv7q7PRuq5XZ6y5yJCIiKgx1SVxfvHFF7F06VIsXrwYANDX14ft27czcaZ5oTIbHQ6HkU6nkEqlkMmkkU67X5ZlwTC88Pn8kCSp3sMlIiKisrokzpFIBF1dXdWfw+EwXnzxxcNeX1EkhELjP9JWFHnC4/MV41FrLsTDHd/o34LjOBgeHkZ/fz+i0Sg0TYHP55/STLQsywgGufthBeNRi/EYjzGpxXjUYjxGzWQsbNuLpiaj4V7H58QKJdsWSCRy446HQr4Jj89XjEetuRoPVfVh5cpTsHBhDkNDEcRiUeRySViWCSEAXXcXIE5298Jg0It0ujDDo547GI9ajMd4jEktxqMW4zFqJmORyRSQSuXr8jre0RE87GV1SZzD4TAGBwerP0ciEYTD4XoMhahh+Xw+LFu2HMuWLQcAWJaFbDaDgYGDOHjwAIQAAoH999KpAAAgAElEQVQAvF7OfBAREc2GuiTOp59+Ovr7+7Fv3z6Ew2E89NBDuO222+oxFKI5Q1XV6i6GPT0rMTwcx969exCPxyGEgCRJkGUJgUCQW4ETERHNgLokzqqq4sYbb8RVV10F27bx0Y9+FKtWrarHUIjmJF3X0dW1AF1dC+A4DorFIkyzhEQigb179yKZTELX3S4dHo8Mx3EmXdpBREREE6tbjfM555yDc845p14PT3TCkGUZhmHAMAw0NTWju3sxkskEotEo8vkcbNtBKpWCbVsQwr3NsdZJExER0RxZHEhEkyfLMlpaWtHS0gpgdJGkbdsoFArI5/OIxYZw8ODB6m00TYWmafB6DbbAIyIiOgwmzkTzhKIo8Pv98Pv9aG9vx4oVq5BKpVAqFZHJZJDNZjA8HOeiQyIiosNg4kw0T2mahra2tppjxWKxuujQ3dVQgqqq0LTRnQ2JiIjmKybORFTl8XiwYMFCLFiwsLqbYS6XQzabRTqdQjKZgKKo8Pl80HWdZR1ERDSvMHEmogkFAkEEAqNN4IUQyGTSiEajiMdjGBkZgeM4kCQJQggoioJgMAhV5dMKERGdmPgKR0STIkkSgsEmBINN6OlZUdMGr1QykU6nsG/fXpimCV3X4PcHjnubcCIiokbExJmIjsvYNngA0N7ejqVLlyGVSmJgYACDgwM1M9JMpomIaK5j4kxE00aWZYRCLQiFWrB69UkoFArVGenh4TgGBwdgWRZ8PgM+n5810kRENKcwcSaiGVFpfwf4AQCdnZ1YuXIVEokEDh7cj1gsWr6mBEBA1z3w+/3clIWIiBoWE2cimjWqqqK9vR3t7e2wLKtaI10sljA0FEE0GoEQgGEY8Pl8nJEmIqKGwsSZiOpCVdVyBw53RjocDsM0TSQSCRw4sA/Dw8MQQsDNnSt10joCgQBnpYmIqC6YOBNRw9A0DR0dHejo6IBlWeUvE5ZlwTQtRKNDiEQG4TgOdF2DqmrlDVo0zk4TEdGMY+JMRA1pdEZ6dOvvjo4OrF59EhKJBEZGhpHPZ5HN5pDJZKrJNDt3EBHRTGHiTERzytg66QrbtpFKJRGJDGJwcBC2bUNR5OqMtK5rUBQ+3RER0dTwlYSI5jxFUdDS0oqWllasWnUSkskEMpkMcrkccrksMpkMTNOEoihQ1RBs2+GsNBERHTMmzkR0QlEUBa2tbWhtbasecxwH6XQK8Xgctp1HLBaFbVsQAtXaaL/fD6/Xe7i7JSIiYuJMRCc+WZbR3BxCc3MIoZAPiUQOlmWhVCrBNEvIZDI4cMDtLS1JMnw+HzweD7t3EBFRDSbORDQvjS4+9KG5OYRFi7qRy+UwMjKMgYGDSKVS1VlpADAML3c7JCKa55g4ExGV+Xw++Hw+LFrUDQDlNngm0uk0BgcPIhaLQggJHo8OTdPGJN9ERDQf8BmfiOgwKomxYRjo7OysbtASj8eQy2WRy+VRKhUghHvdQCDARJqI6ATGZ3giokkau0FLRWXhYTQaxcGDB2CaJiRJgqapUBQVmqZC1z11HDUREU0XJs5ERFMwduHhihUrkU6nkMlkkM/nkc1mkctlxyw6NOD1GqyTJiKao5g4ExFNE0mS0NTUjKam5prj+XweyWQCBw7sRzwegyTJEEJAliVomg6fz8e+0kREcwATZyKiGWYYBgzDQFfXAhSLRRQKeZRKJkyzhGQyiaGhQdi2A0CU66o1KIpS/WJbPCKixsDEmYhoFnk8Hng8ozXPCxcuwkknrUE6nUKhUEQmk0Yul0OpVESp5PaYtm0LgATD8MIwfEykiYjqhIkzEVGdjdZJA+FweNzlpZI7Mz04OIBYLArHcap10rIswe8PQNf12R42EdG8w8SZiKjB6bpe7eZh2zZM0y3zME0TyWQSBw8eQCqVhCwrMAwvNE2HoihchEhENM2YOBMRzSGVumev1wsAaG1tw7Jly5HNZpFMJjA0FEEul0OxWAQgIISbePv9PigKn/KJiKaCz6JERHOcJEkIBAIIBALVXQ+FENVdD6PRIUQig7Asa1yPacBb38ETEc0hTJyJiE5AkiRB13W0tbWhra0Nq1efhEwmXe0x7faZzmBoKIpMpgifjwsPiYiOZkqJ81e+8hX87ne/g6ZpWLJkCW699VY0NTUBAO68807cd999kGUZX/ziF/G+970PALBjxw7cfPPNcBwHl19+Oa6++uqpnwURER2RLMsT9pg2DAV79gwgEhlELBaFEA6A0YWHPp+/pgsIEdF8NqXEeePGjbj++uuhqiq+9rWv4c4778QNN9yAXbt24aGHHsJDDz2ESCSCrVu34uGHHwYA3HTTTfj+97+PcDiMyy67DL29vVi5cuW0nAwRER0bj8eDzs5OdHZ2wrZt5PN5WJYJ07SQzWYxOHgQsVgMgNuP2uPxQFX5YSURzU9TevbbtGlT9d/r16/Hr3/9awDA9u3b0dfXB13XsXjxYixduhQvvvgiAGDp0qVYvHgxAKCvrw/bt29n4kxE1AAURUEgEKj+3NHRgWXLliGfzyOVSiISGUAqlUGpNLrwUFFk+P1+6DpnpYnoxDdt0wY//elP8aEPfQgAEIlEsG7duupl4XAYkUgEANDV1VVzvJJQH4miSAiFfBMclyc8Pl8xHrUYDxfjUIvxqDWZeIRCPixY0IaTTuoBMLrwMJ/PIx6P4cCBA8hm05AkN/l2dz9U4fF45uRW4rIsIxjkoskKxqMW4zFqJmNh2140NRkN93x91MT5iiuuqH5MN9a1116LD37wgwCAb3/721AUBRdddNH0jxCAbQskErlxx0Mh34TH5yvGoxbj4WIcajEetaYWDw2trQvQ2roAuVwO6XQa+XwehYL7FY9HYdt2eZOWuTMrHQx6kU4X6j2MhsF41GI8Rs1kLDKZAlKpfF2erzs6goe97KiJ8913333Ey3/2s5/hsccew913311tth8OhzE4OFi9TiQSqe6GdbjjREQ0d/l8Pvh8tTNDjuMgk0ljeHikXCsdLb9OSBBCsL80Ec05U3q22rFjB77zne/ghz/8IQzDqB7v7e3F9ddfj61btyISiaC/vx9r166FEAL9/f3Yt28fwuEwHnroIdx2221TPgkiImo8Yzt5LFu2DMViEaZpwrJMlEomhofjGBqKwDRLkGUZhmFAUdwyD7bFI6JGNKXE+ctf/jJKpRK2bt0KAFi3bh1uuukmrFq1Ch/60Ifw4Q9/GIqi4MYbb6zWud1444246qqrYNs2PvrRj2LVqlVTPwsiImp4Ho+nprVdZ2cnTjppDTKZNBKJBIaH4+X+0lk4jg1AgqIo8Pv90DStfgMnIiqThBCi3oM4GtO0WeM8CYxHLcbDxTjUYjxqNWo8LMtCOp1CPB7H4OAgisU8AAmSBMiyAl3X4PUaM7L4kDWstRiPWozHqJmMRTKZQHf3EvT0rJiR+z+SKdU4ExERzTZVVdHS0oqWllasWLESuVwOhUIBlmUiny8gk0kjFnMXHyqKDMPwwePxVNfaEBHNBCbORETU0CTJ7crh9/trjlcWHyYSCQwODmBkZARCOKh8jqqqKss8iGhaMXEmIqI5aeziwyVLlkIIAdu2YZpmuR1eHJHIIJLJBCr10m6PaQW6rrObBxEdMz5rEBHRCUGSpOrmK4ZhoKWlFStXrpqwx3QqlYJpliBJMnw+A16vwTIPIjoqJs5ERHRCm6jHtBAC2WwGyWQSg4MDGB6OA5AACBQKXuTzJfh8/pouIERETJyJiGjekSQJgUAQgUAQixZ1V0s8LMuEz6dh795BDA0NIh6PQQhA09yZ7EqfaVXlyyfRfMS/fCIimvcURSm3tvMiFPJBlr3VTVvS6TSSyQTy+TyKxQLy+QKKRbcFl9frgWH4ZqQtHhE1HibOREREh1HZtKW9vb3meD6fRzqdRjQ6hGh0CLZtV7cTB0Q1oeYOiEQnFibOREREx8gwDBiGgc7OTjiOg2KxCMsyYVkWisUihoYiiMfjcBwHiiJD13XIslIt8+BCRKK5iYkzERHRFMiyDMMwABjVY11dC2DbNrLZDBKJBDKZDAqFPIrFIlKpFIQQUBSZCxCJ5hgmzkRERDNAUZRqn+mxbNtGJpPGyEiiugDRJZUTagU+n48JNVEDYuJMREQ0ixRFQXNzCM3NISxbtgylUgmlUgm2bcE0LWQyaQwODpQ7ekjQNHfhoiTJkCQJkiRBluXq98oXEc08Js5ERER1pOs6dF2v/tze3o5ly5bXdPRwW+VZcBwLlmXDtm1YlgXbdmDbFmzbAgAIAUgS4DgChuFlxw+iacbEmYiIqAEdrqPHRIQQ5UTaTaiz2SxiseiYjh9ApRSELfSIjh8TZyIiojlOkiRomgZN0wAAgUAA4XAYQohDOn6UEItFEYtFy7PUElTVLQORZWnC746jH/nBieYRJs5EREQnKEmS4PV6AXirxyoJdTabQTqdRi6Xg22Pln84jl392TRNJJMpJJMZAG4piKLIMAx38SLb6tF8w8SZiIhonhm75fjRhEI+DA9nYJomCoU8EokEotEIhofjcDd8cSmKAo/HA6/Xy4SaTlhMnImIiOiIZFmu1lw3N4ewdOkymKaJbDYD07RgWSYKhQKGh+MYHo5XZ6a9XgOqqkJRFHb+oBMCE2ciIiI6ZpqmIRRqqTm2fHkPLMttqZdIJDA8HEehUECxWIIQNoQAZFmCYfg4M01zEhNnIiIimjaqqiIUakEo1IJly5ZXj7vdPjJIJpMYGqqUegCVbh9uQm3A6zWYUFPDYuJMREREM05V1erGL0uWLIVpmigWC7Asd+OXYrGAaHQIw8PD1S3JNU2DoihQFBWqqrLcg+qOiTMRERHNurHt8yq6uxdXtyRPpVJIp9MolYooFotIJpOwbQuSJMPr9cIwDCbSNOuYOBMREVHDGLsl+ViO4yCXyyKdTpe7eozAcezyboljN3cxoChMb2hm8DeLiIiIGp4sy9UWegsWLITjOOUyDxO2bSGfzyMWiyEej8E0TQBuZw+31EOBrnvGzXATHSsmzkRERDTnyLIMXdeh6+7Ohk1NzQiHu8qbu2SRy+WqZR75vNt/OplMAgB0Xau2ymO5Bx0LJs5ERER0wnA3dwkgEAiMuyyfzyObzSIej2F4OF7dNREQACTIsgyfz90VkWgiTJyJiIhoXjAMA4ZhoL29vXrMcZzqZi7JZBLR6BDi8RgkSYYQYlyrPJrfmDgTERHRvDV2V8TW1jYsX96DUqk0rlVeLBbF8PAwikUPstkidF2v1k9XdkekEx8TZyIiIqIxxtZOVyxevAS2bUNVHezfH0Emk0GxWECxWEQ6nYZlmQAkeDxuZw9VZYp1IpqW/9Xvfe97+MpXvoKnnnoKra2tEELg5ptvxuOPPw6v14t///d/x6mnngoAuP/++/Htb38bAPDJT34Sl1566XQMgYiIiGhGua3yghCitjuHEAK5XA6ZTAbDw3FEo1FYVql8mVt3rSgKfD4Dus766blsyonzwMAA/vCHP2DhwoXVYzt27EB/fz8eeeQR7Ny5E1/60pdw7733IpFI4Jvf/CZ++tOfQpIkfOQjH0Fvby+am5unOgwiIiKiupAkCX6/H36/H+FwGCefDNi2DcuyYFluqcfIyEi1fhoY3VLcbZWnw+v1ssPHHDDlxPnWW2/FDTfcgE996lPVY9u3b8cll1wCSZKwfv16pFIpDA0N4dlnn8XGjRsRCrlNzTdu3Ijf//73uPDCC6c6DCIiIqKGUal/9ng88Pv9aG1tw4oVK1EqlZDLZWGaFizLRLFYRCIxgpGRETiOA0mS4PHoUBS1Wj/NhLpxTClxfvTRR9HZ2Yk1a9bUHI9EIujq6qr+3NXVhUgkMu54OBxGJBKZyhCIiIiI5oyJ6qeB5bBtG7lcFplMBiMjIygU8igWi8jlcrAsq3xbt//0+NvTbDlq4nzFFVcgFouNO37ttdfizjvvxPe+970ZGdhYiiIhFPJNcFye8Ph8xXjUYjxcjEMtxqMW4zEeY1KL8ag1k/FoawtOeDyfzyOdTiMed+un8/lM9TIhBBTF7T/t9XohSdKE9zETZFlGMOidkfu2bS+amoyG+907auJ89913T3j8jTfewP79+3HxxRcDAAYHB/GRj3wE9957L8LhMAYHB6vXHRwcRDgcRjgcxrPPPls9HolEcPbZZx91kLYtkEjkxh0PhXwTHp+vGI9ajIeLcajFeNRiPMZjTGoxHrXqFQ9dD2DBggAWLFharZ12v0ykUinEYlFEIgcBuMk04JaLaJoKwzCgKNPf5SMY9CKdLkz7/QJAJlNAKpWvS6w7OiZ+AwNMoVTjpJNOwlNPPVX9ube3F/fddx9aW1vR29uLH/7wh+jr68POnTsRDAbR2dmJTZs24fbbb69uefnEE0/guuuuO94hEBEREc07qqrWtLsLhVqwZMlS2LaNbDaDYrEE27ZQKBSRzWYQj8dhmm6XD13XoGlatQZ7JhLqE9mMROucc87B448/jvPPPx+GYeCWW24BAIRCIXzqU5/CZZddBgD4h3/4h+pCQSIiIiI6foqioKlpfKcyIUR1u/FEYgS5XBbFYhHZbB6mWYS73bgEr9cLj4fdPY5EEpX5/AZmmjZLNSaB8ajFeLgYh1qMRy3GYzzGpBbjUetEi4dlWchmM9Vyj2QyCcexq/2nhRDQdR2GYUDTavtXz2SpRjKZQHf3EvT0rJiR+z+SGSnVICIiIqK5TVVVNDeH0NwcwuLFSyCEqNZP27aFXC6P4eE44vEYkskEJGl0NtqyfDBNAa/XmNVFifXExJmIiIiIALizzJqmVWeXAwF3nRoAFAoF5PM5WJYNyzKh68CePQcxPDwMIUT1tooiQ5JkyLIMWZYgSfK42eq5iokzERERER2V1+uF1zvafi4U8qGtbWFND+pUKlXeNbFUTrAtmGYJqVSyXP4xugW5qmrwer1QFKWOZ3VsmDgTERER0XFTFAXBYBOCwSYsWLBwwuuYplnt+GGapfLixCxGRoZrNnipdPxwHGc2T2HSmDgTERER0YzSNA2hUMu442M7foyMDFc7fiiK1pA7JDJxJiIiIqK6kCQJPp8PPp8PHR0d9R7OUbFRHxERERHRJDBxJiIiIiKaBCbORERERESTwMSZiIiIiGgSmDgTEREREU0CE2ciIiIioklg4kxERERENAlMnImIiIiIJoGJMxERERHRJDBxJiIiIiKaBCbORERERESTwMSZiIiIiGgSmDgTEREREU2CJIQQ9R4EEREREVGj44wzEREREdEkMHEmIiIiIpoEJs5ERERERJPAxJmIiIiIaBKYOBMRERERTQITZyIiIiKiSZjVxHlgYACf+MQn8OEPfxh9fX34wQ9+AABIJBLYunUrNm/ejK1btyKZTAIA3n77bfz5n/85TjvtNHz3u9+tua+7774bfX19uPDCC3HdddehWCxO+Jj3338/Nm/ejM2bN+P++++vHv/lL3+JLVu2oK+vD1/72tdm6IyPrB7xuPLKK/Hud78bf/d3f1dz/Ic//CHOP/98nHTSSRgeHp6Bsz266YzHD37wA1x44YXo6+vD3XfffdjH3LFjBy644AKcf/75uOuuu6rH6xmPRorD5z//eVx00UXYsmULtm3bhmw2O/0nfBSNFI/Pfvaz6O3txcUXX4yLL74Yr7322vSf8FE0Ujw+/vGPV2OxadMmfOpTn5r+E56ERorJU089hUsvvRQXXnghPvOZz8CyrOk/4aOoRzw+97nPYcOGDbjwwgtrjv/qV79CX18f1qxZg5deeml6T3SSjjUeP//5z7FlyxZs2bIFH/vYx/D6669X7+tw/++HOlzu8Y1vfAPnnHMOzjjjjBk62yNrpFhceeWVuOiii9DX14cbb7wRtm3P0FlPMzGLIpGIePnll4UQQqTTabF582bx1ltvia985SvizjvvFEIIceedd4qvfvWrQgghYrGY2Llzp7j99tvFd77zner9DA4OinPPPVfk83khhBDbtm0TP/3pT8c93sjIiOjt7RUjIyMikUiI3t5ekUgkxPDwsDjnnHNEPB4XQgjxL//yL+LJJ5+c0XOfyGzHQwghnnzySbF9+3Zx9dVX1xx/5ZVXxL59+8S5555bjctsm654vPHGG6Kvr0/kcjlhmqb4m7/5G9Hf3z/u8SzLEuedd57Yu3evKBaLYsuWLeKtt94SQtQ3Ho0Uh3Q6Xb3eLbfcUn382dRI8fjMZz4jfvWrX830KR9RI8VjrGuuuUbcf//9M3HKR9UoMbFtW7z//e8Xu3fvFkIIcccdd4j/+q//munTH2e24yGEEM8++6x4+eWXRV9fX83xXbt2ibffflv81V/9lXjxxRdn4nSP6ljj8dxzz4lEIiGEEOKxxx4Tl112mRBi8n8Lh8s9hBDi+eefF5FIRKxfv37Gz3sijRSLyuuL4zjimmuuEb/4xS9m9uSnyazOOHd2duLUU08FAAQCAfT09CASiWD79u245JJLAACXXHIJHn30UQBAW1sb1q5dC1VVx92XbdsoFAqwLAuFQgGdnZ3jrvPEE09g48aNCIVCaG5uxsaNG/H73/8e+/btw9KlS9Ha2goA2LBhAx5++OGZOu3Dmu14AO65+v3+ccdPOeUUdHd3T9epHZfpisfbb7+NtWvXwjAMqKqKs846C4888si4x3vxxRexdOlSLF68GLquo6+vD9u3bwdQ33g0UhwCgQAAQAiBQqEwY+d8JI0Uj0bQiPHIZDJ4+umn8cEPfnAmTvmoGiUmiUQCmqZh+fLlAICNGzdOePuZNtvxAICzzjoLzc3N446vWLECPT0903l6x+xY43HmmWdWz2X9+vUYHBwEMPnnhsPlHpX7O9zr82xopFhUXl8sy4JpmpAkaWZPfprUrcZ5//79eO2117Bu3TrE4/HqL1JHRwfi8fgRbxsOh/G3f/u3OPfcc7Fp0yYEAgFs2rRp3PUikQi6urpqbheJRLB06VK888472L9/PyzLwvbt26u/DPUyG/GYS6YSj9WrV+O5557DyMgI8vk8duzYMeH/7+F+PxpJI8Thc5/7HDZu3Ijdu3fjE5/4xDSd2fFphHh84xvfwJYtW3DLLbegVCpN05kdn0aIBwA8+uij2LBhQ/WFsJ7qGZOWlhbYtl0tSfj1r389p19bJhuPueRY43Hffffh/e9/P4DJv2bMhdcWoDFiceWVV+LP/uzP4Pf7ccEFF0zbuc2k8VOXsyCbzWLbtm34/Oc/P+6JVpKko77rSCaT2L59O7Zv345gMIh/+qd/woMPPoiLL754Uo/f3NyML33pS/j0pz8NWZZxxhlnYO/evcd9PlNV73g0mqnGY8WKFbjqqqtw5ZVXwjAMrFmzBrI899bBNkocbr31Vti2jS9/+cv45S9/iY9+9KPHfB/ToRHicd1116GjowOmaeJf//Vfcdddd+Gaa6455nOZDo0Qj4pf/OIXuPzyy4/rttOp3jGRJAm33347br31VpRKJWzcuLGuzz31jkejOdZ4PP3007jvvvtwzz33zOYwZ0WjxOK73/0uisUi/vmf/xlPP/00Nm7cOK33PxNm/S/ANE1s27YNW7ZswebNmwG4HxMNDQ0BAIaGhqolFIfz5JNPoru7G62trdA0DZs3b8bzzz+PnTt3VheqbN++HeFwuObdcSQSQTgcBgD09vbi3nvvxU9+8hMsX74cy5Ytm5kTPorZjMdcMB3xAIDLL78cP/vZz/CjH/0Izc3NWLZsGQYGBqrx+PGPf3zE3496a7Q4KIqCvr6+unzsDDROPDo7OyFJEnRdx0c+8pG6LXZqlHgAwPDwMF566SV84AMfmN6TPEaNEpMzzjgD99xzD+677z6cddZZc/q1BZhcPOaCY43H66+/ji9+8Yv41re+hZaWFgA47P/7seQejaDRYuHxeHDeeefNmTxlVhNnIQS+8IUvoKenB1u3bq0e7+3txQMPPAAAeOCBB3Deeecd8X4WLlyInTt3Ip/PQwiBp556CitWrMC6devw4IMP4sEHH8R5552HTZs24YknnkAymUQymcQTTzxRLWGofAyRTCZxzz331GW2ZLbj0eimKx7A6P/vwYMH8cgjj2DLli1YsGBBNR5/8Rd/gdNPPx39/f3Yt28fSqUSHnroIfT29s7MyR2DRomDEAJ79uypjum3v/1tXWoVGyUeAKovLEIIPProo1i1atV0n+5RNVI8AODhhx/GBz7wAXg8nmk+08lrpJhUbl8qlfAf//Ef+NjHPjbdp3tUsx2PRnes8Th48CD+8R//EV/96ler9eoADvv/fiy5R701Siyy2Wz1+dSyLDz22GN1r4WfLEkIIWbrwf74xz/iL//yL7F69erqxz3XXXcd1q5di2uvvRYDAwNYuHAh7rjjDoRC/38799NqShyAcfxJspCkoyy8AccrsDp5AZayMEU2QrKx01lJo1jaKStrWcmCDVsvwgtAxgILxZzFLffWcW9zF8ef+n7ewNS3pp6a3/wCWq/XSiaT2u/3crlc8nq9Go/H8vl86nQ6Go/HcrvdikajMk1THo/n2zMHg4G63a4kqVgsXj8zV6vV67Uq5XJZiUTiThV+e0QPwzC0XC51PB4VCARkmqY+Pj7U7/fV6/W02Wz09vameDwu0zRftodhGNrtdnK73ddrkm6Zz+dqNps6n89KJpMqlUqS9NAez9LhcrnIMAwdDgfZtq1IJKJ6vX73c6zP0kOSstmsLMuSbdt6f39XvV6/+bPtT3qmHpKUyWSUz+evZx8f4ZmatFotzWYzXS4XpdNp5XK5e2W4ekSParWqxWIhy7IUDAZVqVSUSqU0nU7VaDS03W7l9/sVjUa/XXn30/63x+fnpyaTicLhsKRfX9yGw6Gkf78Lf/rb9mi32xqNRlqtVgqFQkqlUqpUKj+d4OpZWmw2GxUKBZ1OJ9m2rVgsplqtdvPyg2dz1+EMAAAAvKrXPT6uup0AAAA8SURBVOUPAAAA3BHDGQAAAHCA4QwAAAA4wHAGAAAAHGA4AwAAAA4wnAEAAAAHGM4AAACAAwxnAAAAwIEvdAa1R6Mz7a0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iBjyi-0gDBT7"
      },
      "source": [
        "Here, ARIMA model is used to forecast all of the test data based on the model fitted on training set.\n",
        "\n",
        "The forecasted price is not that great. However, the confidence interval covers the actual price."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ip5batSTEhcj"
      },
      "source": [
        "## Rolling Forecast on Test set"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SW1eD769EgiC"
      },
      "source": [
        "x_train = list(X_train)\n",
        "x_test = list(X_test)\n",
        "forecasts = list()\n",
        "for i in range(X_test.shape[0]):\n",
        "  model = ARIMA(x_train, order=(p, d, q))\n",
        "  result = model.fit(disp=0)\n",
        "  yhat = list(result.forecast()[0])[0]\n",
        "  forecasts.append(yhat)\n",
        "  x_train.append(x_test[i])\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HzfXoVzMF7s_",
        "outputId": "7da5f798-07ec-4a74-efde-dedcc446ceb0"
      },
      "source": [
        "testScore = mean_squared_error(x_test, forecasts, squared=False)\n",
        "print(\"Test Score: %.2f RMSE\" % (testScore))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test Score: 9.37 RMSE\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "GenZreo3KFN6",
        "outputId": "b412257e-b5dd-403e-98df-06cd517a9ff0"
      },
      "source": [
        "plt.title(\"Rolling Forecast vs Actual\")\n",
        "plt.plot(test_date, X_test, label=\"Actual\")\n",
        "plt.plot(test_date, forecasts, label=\"Rolling Forecast\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d4y-4yltKdip"
      },
      "source": [
        "Significant improve in RMSE of rolling forecasts."
      ]
    }
  ]
}