06_ARX_and_ARCH_models_volalitility_prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "zIM6MmlLrZ_T"
   },
   "outputs": [],
   "source": [
    "import datetime as dt\n",
    "import sys\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import plotly.graph_objects as go\n",
    "import seaborn as sns\n",
    "import yfinance as yf\n",
    "from arch import arch_model\n",
    "from arch.__future__ import reindexing\n",
    "from arch.unitroot import VarianceRatio\n",
    "from arch.univariate import ARX, GARCH\n",
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 467
    },
    "id": "Z14XWyF2riWu",
    "outputId": "c729f00e-1031-4ad7-882f-9db07748016b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "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>Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>17.516148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>17.006323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>16.714993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>16.906178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>16.787825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-27</th>\n",
       "      <td>23.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>23.040001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-01</th>\n",
       "      <td>23.219999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-02</th>\n",
       "      <td>23.180000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-03</th>\n",
       "      <td>23.040001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>937 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                Price\n",
       "Date                 \n",
       "2018-01-02  17.516148\n",
       "2018-01-03  17.006323\n",
       "2018-01-04  16.714993\n",
       "2018-01-05  16.906178\n",
       "2018-01-08  16.787825\n",
       "...               ...\n",
       "2021-08-27  23.600000\n",
       "2021-08-31  23.040001\n",
       "2021-09-01  23.219999\n",
       "2021-09-02  23.180000\n",
       "2021-09-03  23.040001\n",
       "\n",
       "[937 rows x 1 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = yf.download(\"KCHOL.IS\", period=\"max\", start=\"2018-01-03\")\n",
    "data.drop([\"Open\", \"High\", \"Low\", \"Close\", \"Volume\"], axis=1, inplace=True)\n",
    "data.rename(columns={\"Adj Close\": \"Price\"}, inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 545
    },
    "id": "Ajkn6BWLwo4T",
    "outputId": "5bc91440-0e99-4e05-a098-e1e51b0b1268"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(data)\n",
    "plot_pacf(data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 167
    },
    "id": "3J0wmPFtuBy4",
    "outputId": "2aa2454e-6e30-421d-feb2-4d77199454fc"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Variance-Ratio Test Results</caption>\n",
       "<tr>\n",
       "  <td>Test Statistic</td>     <td>0.318</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>P-value</td>            <td>0.751</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Lags</td>                   <td>2</td>\n",
       "</tr>\n",
       "</table><br/><br/>Computed with overlapping blocks (de-biased)"
      ],
      "text/plain": [
       "<class 'arch.unitroot.unitroot.VarianceRatio'>\n",
       "\"\"\"\n",
       "     Variance-Ratio Test Results     \n",
       "=====================================\n",
       "Test Statistic                  0.318\n",
       "P-value                         0.751\n",
       "Lags                                2\n",
       "-------------------------------------\n",
       "\n",
       "Computed with overlapping blocks (de-biased)\n",
       "\"\"\""
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "VarianceRatio(data)  # Price is unpredictable!!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "Vibrbqq9wAbF"
   },
   "outputs": [],
   "source": [
    "# Calculate returns and squared returns\n",
    "data[\"ret\"] = np.log(data.Price) - np.log(data.Price.shift(1))\n",
    "data[\"ret_sq\"] = data[\"ret\"] ** 2\n",
    "data.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 545
    },
    "id": "76D3s48GwwME",
    "outputId": "b2e593f0-9cb8-4066-80a5-eac3916fbab4"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(data[\"ret\"])\n",
    "plot_pacf(data[\"ret\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 545
    },
    "id": "MyyPCUD7w2xm",
    "outputId": "c420c81f-d5f6-48e4-d8be-d23dd2144fca"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(data[\"ret_sq\"])\n",
    "plot_pacf(data[\"ret_sq\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RwEWDchXwPE-",
    "outputId": "b9fca031-c472-4cfe-e20a-7d420764f013"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Variance-Ratio Test Results     \n",
      "=====================================\n",
      "Test Statistic                 -8.492\n",
      "P-value                         0.000\n",
      "Lags                                2\n",
      "-------------------------------------\n",
      "\n",
      "Computed with overlapping blocks (de-biased)\n",
      "     Variance-Ratio Test Results     \n",
      "=====================================\n",
      "Test Statistic                 -2.349\n",
      "P-value                         0.019\n",
      "Lags                                2\n",
      "-------------------------------------\n",
      "\n",
      "Computed with overlapping blocks (de-biased)\n"
     ]
    }
   ],
   "source": [
    "# But, returns and squared returns are predictable!!\n",
    "print(VarianceRatio(data[\"ret\"]))\n",
    "print(VarianceRatio(data[\"ret_sq\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "AsiQoHzRRiKy"
   },
   "outputs": [],
   "source": [
    "returns_sq = 10000 * data[\"ret_sq\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 757
    },
    "id": "03h0jAXD16JM",
    "outputId": "1f760abf-7aea-46e8-f7b3-d2ae58082f1a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                           AR - GARCH Model Results                           \n",
      "==============================================================================\n",
      "Dep. Variable:                 ret_sq   R-squared:                      -0.246\n",
      "Mean Model:                        AR   Adj. R-squared:                 -0.250\n",
      "Vol Model:                      GARCH   Log-Likelihood:               -3171.84\n",
      "Distribution:                  Normal   AIC:                           6357.68\n",
      "Method:            Maximum Likelihood   BIC:                           6391.40\n",
      "                                        No. Observations:                  914\n",
      "Date:                Sat, Sep 04 2021   Df Residuals:                      910\n",
      "Time:                        09:33:50   Df Model:                            4\n",
      "                                  Mean Model                                 \n",
      "=============================================================================\n",
      "                 coef    std err          t      P>|t|       95.0% Conf. Int.\n",
      "-----------------------------------------------------------------------------\n",
      "Const          1.3119      0.470      2.791  5.262e-03      [  0.390,  2.233]\n",
      "ret_sq[1]      0.5778  9.521e-02      6.069  1.286e-09      [  0.391,  0.764]\n",
      "ret_sq[5]  8.8125e-03  4.512e-02      0.195      0.845 [-7.962e-02,9.724e-02]\n",
      "ret_sq[22]     0.2523      0.124      2.042  4.114e-02    [1.015e-02,  0.494]\n",
      "                            Volatility Model                            \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "omega         26.6744      6.711      3.975  7.041e-05 [ 13.522, 39.827]\n",
      "alpha[1]       1.0000      0.441      2.268  2.331e-02 [  0.136,  1.864]\n",
      "beta[1]    3.4739e-10  5.160e-02  6.732e-09      1.000 [ -0.101,  0.101]\n",
      "========================================================================\n",
      "\n",
      "Covariance estimator: robust\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# AR - GARCH Model\n",
    "ar_garch = ARX(returns_sq, lags=[1, 5, 22])\n",
    "res_ar_garch = ar_garch.fit()\n",
    "ar_garch.volatility = GARCH(p=1, q=1)\n",
    "res_ar_garch = ar_garch.fit(update_freq=0, disp=\"off\")\n",
    "\n",
    "print(res_ar_garch.summary())\n",
    "res_ar_garch.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "id": "j8itzjgbAeu_",
    "outputId": "01e17e46-5bf3-40a6-a52c-601e8f9c6875"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Constant Mean - GJR-GARCH Model Results                       \n",
      "====================================================================================\n",
      "Dep. Variable:                       ret_sq   R-squared:                       0.000\n",
      "Mean Model:                   Constant Mean   Adj. R-squared:                  0.000\n",
      "Vol Model:                        GJR-GARCH   Log-Likelihood:               -2549.16\n",
      "Distribution:      Standardized Student's t   AIC:                           5110.33\n",
      "Method:                  Maximum Likelihood   BIC:                           5139.38\n",
      "                                              No. Observations:                  936\n",
      "Date:                      Sat, Sep 04 2021   Df Residuals:                      935\n",
      "Time:                              09:33:50   Df Model:                            1\n",
      "                               Mean Model                               \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "mu             1.3838      0.149      9.307  1.317e-20 [  1.092,  1.675]\n",
      "                               Volatility Model                              \n",
      "=============================================================================\n",
      "                 coef    std err          t      P>|t|       95.0% Conf. Int.\n",
      "-----------------------------------------------------------------------------\n",
      "omega         13.0117     65.175      0.200      0.842 [-1.147e+02,1.408e+02]\n",
      "alpha[1]       0.1249      0.559      0.223      0.823      [ -0.971,  1.221]\n",
      "gamma[1]       0.0105      8.144  1.287e-03      0.999      [-15.951, 15.972]\n",
      "beta[1]        0.8698  4.363e-02     19.936  1.976e-88      [  0.784,  0.955]\n",
      "                              Distribution                              \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "nu             2.0500      0.230      8.905  5.332e-19 [  1.599,  2.501]\n",
      "========================================================================\n",
      "\n",
      "Covariance estimator: robust\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# GRJ-GARCH model\n",
    "grja = arch_model(returns_sq, p=1, q=1, o=1, vol=\"GARCH\", dist=\"t\")\n",
    "res_grja = grja.fit(disp=\"off\")\n",
    "\n",
    "print(res_grja.summary())\n",
    "res_grja.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "id": "uUvjwd2iBm2R",
    "outputId": "a9ee051f-c704-4bde-8b5c-7d64a154506e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        Constant Mean - EGARCH Model Results                        \n",
      "====================================================================================\n",
      "Dep. Variable:                       ret_sq   R-squared:                       0.000\n",
      "Mean Model:                   Constant Mean   Adj. R-squared:                  0.000\n",
      "Vol Model:                           EGARCH   Log-Likelihood:               -2550.55\n",
      "Distribution:      Standardized Student's t   AIC:                           5113.10\n",
      "Method:                  Maximum Likelihood   BIC:                           5142.15\n",
      "                                              No. Observations:                  936\n",
      "Date:                      Sat, Sep 04 2021   Df Residuals:                      935\n",
      "Time:                              09:33:51   Df Model:                            1\n",
      "                               Mean Model                               \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "mu             1.3797      0.115     11.997  3.670e-33 [  1.154,  1.605]\n",
      "                            Volatility Model                            \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "omega          0.6158      0.368      1.674  9.422e-02 [ -0.105,  1.337]\n",
      "alpha[1]       0.5306      0.499      1.063      0.288 [ -0.447,  1.508]\n",
      "gamma[1]      -0.2473      0.404     -0.611      0.541 [ -1.040,  0.545]\n",
      "beta[1]        0.9412  3.492e-02     26.957 4.690e-160 [  0.873,  1.010]\n",
      "                              Distribution                              \n",
      "========================================================================\n",
      "                 coef    std err          t      P>|t|  95.0% Conf. Int.\n",
      "------------------------------------------------------------------------\n",
      "nu             2.0500  4.601e-02     44.554      0.000 [  1.960,  2.140]\n",
      "========================================================================\n",
      "\n",
      "Covariance estimator: robust\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# E-GARCH model\n",
    "egarch = arch_model(returns_sq, p=1, q=1, o=1, vol=\"EGARCH\", dist=\"t\")\n",
    "res_egarch = egarch.fit(disp=\"off\")\n",
    "\n",
    "print(res_egarch.summary())\n",
    "res_egarch.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 483
    },
    "id": "QO87Y9VG9LsD",
    "outputId": "3e4b9a5e-f94c-4c88-ccd9-8ed6ad22b806"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.plot(returns_sq, color=\"grey\", alpha=0.4, label=\"Price Returns\")\n",
    "plt.plot(res_ar_garch.conditional_volatility, color=\"blue\", label=\"AR-GARCH Volatility\")\n",
    "plt.plot(res_grja.conditional_volatility, color=\"red\", label=\"GRJ-GARCH Volatility\")\n",
    "plt.plot(res_egarch.conditional_volatility, color=\"green\", label=\"E-GARCH Volatility\")\n",
    "plt.legend(loc=\"upper right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cHJcN0q_CUOv",
    "outputId": "09391af6-7f53-4a60-91ad-dc757cc7a7db"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AR-GARCH BIC: 6391.404788823991\n",
      "GJR-GARCH BIC: 5139.376513570887\n",
      "EGARCH BIC: 5142.149799027916\n"
     ]
    }
   ],
   "source": [
    "print(f\"AR-GARCH BIC: {res_ar_garch.bic}\")\n",
    "print(f\"GJR-GARCH BIC: {res_grja.bic}\")\n",
    "print(f\"EGARCH BIC: {res_egarch.bic}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 81,
     "referenced_widgets": [
      "5fd4c0ced03e4dc2a64238a7503e942c",
      "8c656e5c885a43fa9005defb1d90ed27",
      "330d8452c3fb43cb8f783c1cd7f56eed",
      "0a28f281681343d08159e2f7d36f2d7c",
      "12571e4becb04e22a29cdc62d299acec",
      "d0b5c81980224f5482c018ea29aa6f2c",
      "dea8e52f41c9452ea0012cfe8dcf672f",
      "f82743d3b3b14da1a878035783ce88c9",
      "40fb43382ac44610a53231d1294eee6c",
      "37a0f50742434f42bdb6b63eeea2f2f2",
      "686e4eb0a57d4de28979cffff139a240",
      "26f6d21e84c9489a95e19ae8a8076217",
      "e8ca5b46c86f41709ee100eb1ead7dac",
      "4a4e2f43d2c849e8a988ec27af4dbe83",
      "91312b8f71fb4036b668401aafcceb6e",
      "08d4138e00734370977c65bb801b13ca",
      "27d04f51e6294774bab4787a7e287d06",
      "67dce49c9e0148fabe61b1b35d1d9164",
      "aff6284e0c8a4f0c84a74485a11ce9f1",
      "2a3c533d301b408bab07717de4be7894",
      "86914aa38ed3485fa4352646f7651a30",
      "2e21740c54af488ba7db7a353a386cb7"
     ]
    },
    "id": "uxVf_1O47Ytl",
    "outputId": "d8b8d3b8-7094-45a7-c18b-b484892cf3ae"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "29c65f2856834eeeadfd0ce5c7d4e1a7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/167 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc22a10a2d8049ab9104afd379acdfe6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/167 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Forecasting\n",
    "# Rolling window\n",
    "index = returns_sq.index\n",
    "start_loc = 0\n",
    "end_loc = np.where(index >= \"2020-12-31\")[0].min()\n",
    "forecasts = {}\n",
    "for i in tqdm(range(len(index) - end_loc + 1)):\n",
    "    res = grja.fit(first_obs=i, last_obs=i + end_loc, disp=\"off\")\n",
    "    temp = res.forecast(horizon=5, reindex=False).variance\n",
    "    fcast = temp.iloc[0]\n",
    "    forecasts[fcast.name] = fcast\n",
    "\n",
    "res_rolling = pd.DataFrame(forecasts).T\n",
    "\n",
    "# Recursive Rolling Window\n",
    "forecasts = {}\n",
    "for i in tqdm(range(len(index) - end_loc + 1)):\n",
    "    res = grja.fit(last_obs=i + end_loc, disp=\"off\")\n",
    "    temp = res.forecast(horizon=5, reindex=False).variance\n",
    "    fcast = temp.iloc[0]\n",
    "    forecasts[fcast.name] = fcast\n",
    "\n",
    "res_rec = pd.DataFrame(forecasts).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 483
    },
    "id": "b8PrYf4aHAOf",
    "outputId": "cc46a62b-5e00-4b0f-d61f-daff5d75823c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Fc845h6uuuoovv/wSgPT09GaDYVOysrJIT09n4cKFALFtsr8U5kREWuC27MpcoFyVORER2d348ePJy8vjySef5IknnuChhx5i3LhxjB49OjaIxh133MH777/P2LFjmThxIitXrsTtdnP99dczZcoUZs+ezYgRI5pdx1VXXcXYsWMZM2YM06dPZ9y4cbvNc+aZZ/Lvf/+7QRfHO++8k0WLFpGXl8eoUaOaPAcO7C6PvXr1Ijk5mRkzZlBYWLhXFbK+ffvyu9/9jmnTpnHooYcycuTI2GN33XUXjzzyCHl5eTz++OPccccdgF29GjhwIFOnTo21obKykrFjx+5xfY899hhXXXUVeXl5LFmypMlKmcfj4dlnn+Xqq69m3Lhx5Ofns2DBAsAOgHfeeSd5eXlMnz6dbdu2cfbZZ7No0SLGjh3Lv/71r9jr8fXXXzNlyhTy8/O58cYbY1XPSy65hHnz5sUGQGmNhx56iB/96Efk5+dTXV3dqi6be2IsK3EvhDtp0iQreuKniEg81JpkkqnjwwsfZebD58e7OSIi3d6qVasahAWRzqKqqoq0tDQAbr75ZoqKimLhNqqp97cxZrFlWZOaWqbOmRMRaYZlgQe7MheuUjdLERER2XevvvoqN910E8FgkEGDBvHoo4/u9zIV5kREmhGoDeLBPjndqlI3SxEREdl3Z555ZoNusG1B58yJiDTDV+n/7pcaVeZEREQksSjMiYg0I1Dl++6XalXmREREJLHsMcwZYwYaY943xqw0xqwwxlwRmZ5jjHnbGLMm8jM7Mt0YY+40xqw1xiwzxkyot6zzI/OvMcZoJAERSWj+qu8qc45ahTkRERFJLK2pzAWB/7MsaxQwFbjMGDMKuAZ417Ks4cC7kd8BjgGGR26XAPeCHf6AG4BDgCnADdEAKCKSiOpX5hx16mYpIiIiiWWPYc6yrCLLsr6M3K8EVgH9gZOAxyKzPQacHLl/EvAvy/YZkGWM6QvMBd62LKvUsqxdwNvAvLZ8MiIibSlQ/V1lzlmnypyIiNicTif5+fmMGTOGE044gbKyshbnv+CCC3j22WcBmDVrFtFLbx177LF7/Nu2Mn369L2a/4MPPuD4449v0zZcddVVjB49mquuuqpNl7uvHn30UbZu3Rr7/eKLL2blypVxbNHe26tz5owxg4HxwEKgt2VZRZGHtgG9I/f7A/UvS18YmdbcdBGRhBSs/q4y5/IrzImIiC05OZklS5awfPlycnJyuOeee/ZpOa+99hpZWVlt27hmRC+YHU8PPPAAy5Yt429/+1ur5g8Gg+3ansZh7p///CejRo1q13W2tVaHOWNMGvAccKVlWRX1H7PsK4+3ydXHjTGXGGMWGWMW7dy5sy0WKSKyTwI131Xm3H51sxQRkd1NmzaNLVu2ALBkyRKmTp1KXl4ep5xyCrt27WrxbwcPHkxxcTEFBQWMHDmSH/3oR4wePZo5c+ZQW1sLwBdffEFeXh75+flcddVVjBkzZrflXHbZZbz00ksAnHLKKfzwhz8E4OGHH+Y3v/kNQOxi1R988AGzZs3i9NNPZ8SIEZx99tnYu/LwxhtvMGLECCZMmMD//ve/2PJLS0s5+eSTycvLY+rUqSxbtgyAsWPHUlZWhmVZ9OjRg3/9618AnHfeebz99tsN2njiiSdSVVXFxIkTefrppykoKODII48kLy+Po446ik2bNgF2FfPHP/4xhxxyCL/61a9Yt24d8+bNY+LEicyYMYPVq1cDsH37dk455RTGjRvHuHHjYmH15JNPZuLEiYwePZoHHngAgFAoxAUXXMCYMWMYO3Yst912G88++yyLFi3i7LPPJj8/n9ra2gZV07S0NH7zm98wbtw4pk6dyvbt2wFYt24dU6dOZezYsVx33XWx7RovrQpzxhg3dpB7wrKs6Cu7PdJ9ksjPHZHpW4CB9f58QGRac9MbsCzrAcuyJlmWNalnz55781xERNpUKFKZC2PwBFSZExFJOFdeCbNmte3tyitbvfpQKMS7777LiSeeCNgh5i9/+QvLli1j7Nix3Hjjja1e1po1a7jssstYsWIFWVlZPPfccwBceOGF3H///SxZsgSn09nk386YMYP58+cDsGXLllhXwfnz53P44YfvNv9XX33F7bffzsqVK1m/fj2ffPIJdXV1/OhHP+Lll19m8eLFbNu2LTb/DTfcwPjx41m2bBl//vOfOe+88wA49NBD+eSTT1ixYgVDhw6NteHTTz/drVvnSy+9FKtonnnmmfz85z/n/PPPZ9myZZx99tlcfvnlsXkLCwtZsGABt956K5dccgl33XUXixcv5pZbbuGnP/0pAJdffjkzZ85k6dKlfPnll4wePRqwA+zixYtZtGgRd955JyUlJSxZsoQtW7awfPlyvv76ay688EJOP/10Jk2axBNPPMGSJUtITk5u0N7q6mqmTp3K0qVLOfzww3nwwQcBuOKKK7jiiiv4+uuvGTBgQGte2nbVmtEsDfAQsMqyrFvrPfQSEB2R8nzgxXrTz4uMajkVKI90x3wTmGOMyY4MfDInMk1EJCGFauwwV2Ey8YRUmRMREVttbS35+fn06dOH7du3M3v2bMrLyykrK2PmzJkAnH/++Xz00UetXuaQIUPIz88HYOLEiRQUFFBWVkZlZSXTpk0D4Kyzzmryb6NhbuXKlYwaNYrevXtTVFTUZKgCmDJlCgMGDMDhcJCfn09BQQGrV69myJAhDB8+HGMM55xzTmz+jz/+mHPPPReAI488kpKSEioqKpgxYwYfffQRH330ET/5yU/4+uuv2bJlC9nZ2aSmprb4fD/99NPY8zn33HP5+OOPY4+dccYZOJ1OqqqqWLBgAWeccQb5+flceumlFBXZZ3m99957/OQnPwHscxgzMzMBuPPOO2PVtM2bN7NmzRqGDh3K+vXr+fnPf84bb7xBRkbGHl8Pj8cTO2cw+npE233GGWcAzb8eHcnVinkOBc4FvjbGLIlMuxa4GfivMeYiYCPwvchjrwHHAmuBGuBCAMuySo0xfwC+iMz3e8uyStviSYiItIdQrd3NstKVjTeoypyISMK5/fa4rDZaYaqpqWHu3Lncc889nH/+/l11KykpKXbf6XTGulm2Rv/+/SkrK+ONN97g8MMPp7S0lP/+97+kpaWRnp6+x3Xt67lphx9+OPfccw+bNm3iT3/6E88//zzPPvssM2bM2KflRUWDYDgcJisriyVLlrTq7z744APeeecdPv30U1JSUpg1axZ1dXVkZ2ezdOlS3nzzTe677z7++9//8vDDD7e4LLfbjV3T2r9t1N5aM5rlx5ZlGcuy8izLyo/cXrMsq8SyrKMsyxpuWdbR0WAWGcXyMsuyhlmWNdayrEX1lvWwZVkHRm6PtOcTExHZX9HKXLU7G29YYU5ERBpKSUnhzjvv5O9//zupqalkZ2fHuho+/vjjsSrdvsrKyiI9PZ2FCxcC8NRTTzU779SpU7n99ts5/PDDmTFjBrfccstehaoRI0ZQUFDAunXrAHjyySdjj82YMYMnnngCsANTbm4uGRkZDBw4kOLi4lj167DDDuOWW25psmtnY9OnT489nyeeeKLJtmZkZDBkyBCeeeYZACzLYunSpQAcddRR3HvvvYDd3bW8vJzy8nKys7NJSUlh9erVfPbZZwAUFxcTDoc57bTT+OMf/8iXX34JQHp6OpWVla3eRmBv52gX2JZej46yV6NZioh0J6E6uzJXm5xNsqVuliIisrvx48eTl5fHk08+yWOPPcZVV11FXl4eS5Ys4frrr9/v5T/00EP86Ec/Ij8/n+rq6lh3wsZmzJhBMBjkwAMPZMKECZSWlu5VmPN6vTzwwAMcd9xxTJgwgV69esUe+93vfsfixYvJy8vjmmuu4bHHHos9dsghh3DQQQfF2rBlyxYOO+ywPa7vrrvu4pFHHiEvL4/HH3+cO+64o8n5nnjiCR566CHGjRvH6NGjefFF+8yuO+64g/fff5+xY8cyceJEVq5cybx58wgGg4wcOZJrrrmGqVOnAvZ5hLNmzSI/P59zzjmHm266CfhusJXoACitcfvtt3PrrbeSl5fH2rVrm309OoqJjl6TiCZNmmRFR5QREeloH1/2JIf94ywWDjydyZufg2AIh9PEu1kiIt3aqlWrGDlyZLyb0WGqqqpiIybefPPNFBUVNRt8pP3V1NSQnJyMMYannnqKJ598MhYw20JT729jzGLLsiY1NX9rzpkTEemWLJ9dmQumZ+PAomqXj7Rcb5xbJSIi3cmrr77KTTfdRDAYZNCgQTz66KPxblK3tnjxYn72s59hWRZZWVl7PPeuvSnMiYg0I1wbuTRBZjYAtcXVCnMiItKhzjzzTM4888x4N0MiZsyYETtvLxHonDkRkWZEK3Pk5AB2mBMRERFJFApzIiLNsOrsypyjh12Z8+3SICgiIokgkcd8ENlX+/K+VpgTEWmO367MuXtFwlypKnMiIvHm9XopKSlRoJMuxbIsSkpK8Hr37nQOnTMnItIcn12ZS+qdBYB/l8KciEi8DRgwgMLCQnbu3Bnvpoi0Ka/Xy4ABA/bqbxTmRESa4/cTwIU72x4SOlihbpYiIvHmdrsZMmRIvJshkhDUzVJEpDl+Hz6S8GSnAhAoV2VOREREEofCnIhIM4zfj98k4e1hh7lQpSpzIiIikjgU5kREmmECPgLGgzcnBYBwhSpzIiIikjgU5kREmuEI+Ak4kkjOtStzVpXCnIiIiCQOhTkRkWY4Aj6CxkNyD7syZ1Wrm6WIiIgkDoU5EZFmOIJ+As4kHB4XPjxQo8qciIiIJA6FORGRZjiDPoIODwA1JhVHrSpzIiIikjgU5kREmuEM+gg6kwCoc6TgqFVlTkRERBKHwpyISDOcIT8hp12Zq3Om4vQpzImIiEjiUJgTEWmGM+QjFKnM+ZypuHzqZikiIiKJQ2FORKQZrrCfkMuuzPndKbj9qsyJiIhI4lCYExFphjvkI+yyK3MBdyrugCpzIiIikjgU5kREmuEK+wlHKnPBpFSSgqrMiYiISOJQmBMRaYbb8hH22JW5UFIKSSGFOREREUkcCnMiIs1wh/1YkcpcyJuKN6xuliIiIpI4FOZERJrhsXxYkcqclZxCcliVOREREUkcCnMiIs1w48dy25U5KyWVVKqxwlacWyUiIiJiU5gTEWmCZUESPkiyK3OkpuIkTF2FP74NExEREYlQmBMRaULIH8JFCDx2Zc6kpgBQs1NdLUVERCQxKMyJiDTBVxmpwEUqc470VADqSjUIioiIiCQGhTkRkSb4qxuGOWdGJMyVqDInIiIiiUFhTkSkCYFKHwDGa3ezdKbb3Sx9pQpzIiIikhgU5kREmhCIVOZMpDLnzrIrc/4ydbMUERGRxKAwJyLShECVXZlzJNuVOXemXZkLlKkyJyIiIolBYU5EpAnRypzDa1fmknLsylywQpU5ERERSQwKcyIiTQhW25U5Z6Qy58mOhLlyVeZEREQkMSjMiYg0IVQT7WZpV+aSe9jdLMNVCnMiIiKSGBTmRESaEKyxu1lGK3PJuXZlLlylbpYiIiKSGBTmRESaEK3MOVPsylxKrl2ZQ5U5ERERSRAKcyIiTQjV2pU5V0rkOnNeN37cUKMwJyIiIolBYU5EpAnh2oaVOYAak4qpUTdLERERSQwKcyIiTYhW5typnti0OpOCo06VOREREUkMCnMiIk0I19mVOVfqd5W5OmcqzjpV5kRERCQxKMyJiDQhXGdX5jxp9SpzrlRcPlXmREREJDEozImINKWJylzAlYLLrzAnIiIiiUFhTkSkCWHf7pU5vycVd0DdLEVERCQxKMyJiDTFZ1fmPOnfVeaCnhSSgqrMiYiISGJQmBMRaUoTlblgUipJQVXmREREJDEozImINMXvI4gTh9sZmxT2puINqzInIiIiiUFhTkSkKT4/PpIaTAqnpJISropTg0REREQaUpgTEWmCCfgIGE/DiekZpFFFKBCOT6NERERE6lGYExFpgvH78ZuGlTkyM3BgUbVN1TkRERGJP4U5EZEmOJqozDmyMgGoLqqIR5NEREREGlCYExFpggn6CTgaVuZcORkA1GxTmBMREZH4U5gTEWmCM+Aj6GhYmfPk2mGudrvCnIiIiMSfwpyISBOcQR/BRpU5T087zPl2lMejSSIiIiINKMyJiDTBEfITdDaszCX3ssNcoESVOREREYk/hTkRkSY4gz6CzoaVuZS+9gAowVKFOREREYk/hTkRkSa4Qn7CjSpzqX3tylyoTGFORERE4k9hTkSkCa6Qj5CrYWUurU+afadM58yJiIhI/CnMiYg0wRn2E3I1rMw5PU4qSYNKVeZEREQk/hTmRESa4A77CDeqzAFUOTJxVinMiYiISPwpzImINMEV9mO5PbtNr3Fl4KpRmBMREZH4U5gTEWmCx/IRdu9emat1Z+Cp1TlzIiIiEn8KcyIiTXBbTVfmfEkZJPlUmRMREZH4U5gTEWmCx/JheXavzPmTM/EGFOZEREQk/hTmRESa4MEPnt0rc8GUDFKCCnMiIiISfwpzIiKNhAJhPASarMyFUjNIC+mcOREREYk/hTkRkUb81QH7jnf3MGelZ5BBJVYo3MGtEhEREWlIYU5EpBF/pQ8A00Q3S5OZAUD19qoObZOIiIhIYwpzIiKN+Kv8AJgmKnMmOxOAyi06b05ERETiS2FORKSRQFWkMpe0e2XOlW1X5mqKdN6ciIiIxJfCnIhII4HqSGUueffKnLuHHebqdqgyJyIiIvGlMCci0kiw2q7MOZqozHl72WHOt1NhTkREROJLYU5EpJFoN0tnyu6VOW9v+5w5f7HCnIiIiMSXwpyISCOhWrubpcO7e2UupY9dmQuW6pw5ERERiS+FORGRRqLdLJuqzKX2s8NceJcqcyIiIhJfCnMiIo1EK3PO5N0rc+l90gCwyhXmREREJL4U5kREGgnV2JU5V+rulTlXkpMK0jGVCnMiIiISXwpzIiKNtFSZA6hyZOCo0jlzIiIiEl8KcyIijYRr7cqcO233yhxAjSsDV40qcyIiIhJfCnMiIo2E6+zKnCul6cpcrTsDd63CnIiIiMSXwpyISCN7qsz5PBkk+RTmREREJL4U5kREGrF8dmXOndp0Zc6fnEmyX+fMiYiISHwpzImINGLV2ZU5T3rTlblASgYpQVXmREREJL4U5kREGrH8LVfmwmkZpIUU5kRERCS+9hjmjDEPG2N2GGOW15v2O2PMFmPMksjt2HqP/doYs9YY840xZm696fMi09YaY65p+6ciItJGIpW5pIymK3NWWgbpVGIFQx3ZKhEREZEGWlOZexSY18T02yzLyo/cXgMwxowCvg+MjvzNP4wxTmOME7gHOAYYBfwgMq+ISOLx+wnhwJnkavrxzEwAandWdWCjRERERBraY5izLOsjoLSVyzsJeMqyLJ9lWRuAtcCUyG2tZVnrLcvyA09F5hURSTjG78NP010sARxZGQBUbVVXSxEREYmf/Tln7mfGmGWRbpjZkWn9gc315imMTGtu+m6MMZcYYxYZYxbt3LlzP5onIrKPAn78NN3FEsCVY4e5mm0KcyIiIhI/+xrm7gWGAflAEfD3tmqQZVkPWJY1ybKsST179myrxYqItJrx+wiY5itz7h52mKvdpssTiIiISPw0c0JIyyzL2h69b4x5EHgl8usWYGC9WQdEptHCdBGRhOII+PE7mq/MeXra58z5dqoyJyIiIvGzT5U5Y0zfer+eAkRHunwJ+L4xJskYMwQYDnwOfAEMN8YMMcZ4sAdJeWnfmy0i0n5MwEewhcpccm+7MucvVpgTERGR+NljZc4Y8yQwC8g1xhQCNwCzjDH5gAUUAJcCWJa1whjzX2AlEAQusywrFFnOz4A3ASfwsGVZK9r6yYiItAVnwEeghcpcNMwFSxXmREREJH72GOYsy/pBE5MfamH+PwF/amL6a8Bre9U6EZE4cAT9BB3NV+bS+tlhLrxL58yJiIhI/OzPaJYiIl2SM+gj4Gy+MpfeNw0Aq1yVOREREYkfhTkRkUYcIT8hZ/OVOU+ykwrSoUJhTkREROJHYU5EpBFXyEeohcocQJUjA0e1wpyIiIjEj8KciEgjzpCfkKv5yhxAjTMDd7XOmRMREZH4UZgTEWnEHfYRcrVcmat1Z+CuVWVORERE4kdhTkSkEVfIj7WHylxdUiYen8KciIiIxI/CnIhII27LR8jdcmXO780g2a8wJyIiIvGjMCci0ogrvOfKXDAlg5SgzpkTERGR+FGYExFpxGP5CHtarsyFUjNIC6syJyIiIvGjMCci0ojb8oO75cpcOD2TNKsKKxjqoFaJiIiINKQwJyLSSBI+rD1U5sjKAqB2m7paioiISHwozImI1GOFLZLwQ1LLYc7ZMxuAio27OqJZIiIiIrtRmBMRqSdQE7DveFruZunpnQNA1abS9m6SiIiISJMU5kRE6vFV+u07e6jMefvalbnararMiYiISHwozImI1BOo8gFgklquzKX0t8NcXZHCnIiIiMSHwpyISD3+ykiY87ZcmUsfZHezDGxXN0sRERGJD4U5EZF6gjV2N0uHt+XKXOZguzIXKlZlTkREROJDYU5EpJ7WVubScr3U4oVSVeZEREQkPhTmRETqiVbmnMktV+aMgTJHDo5yVeZEREQkPhTmRETqCVbblTlH8h4uGg5UubJxVSnMiYiISHwozImI1BOqbV1lDqDam4O3Wt0sRUREJD4U5kRE6olW5pwpe67M1SVnk+xTZU5ERETiQ2FORKSeWGUuZc+VuUBqNql+hTkRERGJD4U5EZF6QjV2Zc7VispcKDOHzJC6WYqIiEh8KMyJiNQTqrMrc65WVOasrGzSqCZQE2jvZomIiIjsRmFORKQeqzZSmUvdc2XO0cO+cHh5gbpaioiISMdTmBMRqSccqcy5U/dcmXP1ygGgcqO6WoqIiEjHU5gTEanHqrMrc+60PVfmkvrYlbnqQlXmREREpOMpzImI1BOtzHnS9lyZS+5nh7naLarMiYiISMdTmBMRqc/X+spc6kC7m6V/uypzIiIi0vEU5kRE6rF8dmUuKWPPYS5jkF2ZC+xUmBMREZGOpzAnIlKP8UdGs/S69jhv5mA7zFnF6mYpIiIiHU9hTkSkHsvvp44kjMPscV5nkosK0jFlqsyJiIhIx1OYExGpx+H34WfPg59EVbqycVYozImIiEjHU5gTEanH+H34zZ7Pl4uqcufgqVY3SxEREel4CnMiIvWYgJ+AaX1lrtabjbdWlTkRERHpeApzIiL1mICPgKP1lTlfajYpPoU5ERER6XgKcyIi9TiCfoKO1lfmAuk5ZATUzVJEREQ6nsKciEg9zr2szFmZ2WRauwiH27FRIiIiIk1QmBMRqccR8hPai8ocOdl48VG5o7b9GiUiIiLSBIU5EZF6nEEfQWfrK3PO3BwAyjeoq6WIiIh0LIU5EZF6nCE/IWfrK3Oe3tkAVG3WICgiIiLSsRTmRETqcYV8BF2tr8wl9bUrczWFqsyJiIhIx1KYExGpxxXyE3a1vjKX0t+uzNUVqTInIiIiHUthTkSkHlfYR3gvKnPpB9hhLrBDYU5EREQ6lsKciEg9rvDeVeYyBtvdLEM71c1SREREOpbCnIhIPZ6wj7C79ZU5b68MwhisXarMiYiISMdSmBMRqcdl+bHce3GdOYeDCpOFo0xhTkRERDqWwpyISD0ey4flaX1lDqDCnYO7Ut0sRUREpGMpzImI1OPBT3gvw1xNUjZJNarMiYiISMdSmBMRibDCFkn4MJ696GYJ1Cbn4K1TmBMREZGOpTAnIhIR8odwYO11N8tAajbpfnWzFBERkY6lMCciEuGr8AFgkvauMhfKyCY9pMqciIiIdCyFORGRiECVHeZI2rvKnJWdQza7qK2x2qFVIiIiIk1TmBMRifBX+QFwePeuMufpnY2LEN8sqmyPZomIiIg0SWFORCQiVpnz7l1l7uB5QwD4+B/L2rpJIiIiIs1SmBMRiQhU25U5515W5tJPOZqgccGrrxAKtUfLRERERHanMCciEhGsjgyAspeVOTIzKRl9OLOqXuGDD9q+XSIiIiJNUZgTEYmIVeaS964yB5B93gmMYQVv3LuhrZslIiIi0iSFORGRiFCNXZlzJO9lZQ7wnHK8feeVV6ipactWiYiIiDRNYU5EJCJYY1fmXCl7X5njwAOpPmAEs30v8/LLbdwwERERkSYozImIROxPZQ4g+fTjmcUHPPeoLlEgIiIi7U9hTkQkIlRrV+bcqftQmQMcJ52AhwC89RbFxW3ZMhEREZHdKcyJiESEa+3KnDNl3ypzTJ9OMD2LY8Kv8MYbbdgwERERkSYozImIRITr9q8yh8uF87hjON68yhuvhduwZSIiIiK7U5gTEYmIVubcaftYmQPMiSfQ09rJjle/0AXERUREpF0pzImIREQrc/s0mmXUnDlYxjC14k0WL26jhomIiIg0QWFORCTKZ1fmPOn7XpmjRw+C+ZOYy5u8/nobtUtERESkCQpzIiIRsXPm9qObJYD7uLlM5TM+fnlXWzRLREREpEkKcyIiUX67MpeUvh/dLAHmzsVJmKzF7+oSBSIiItJuFOZERKJ8+zmaZdTUqQTTMpnDm7z9dhu0S0RERKQJCnMiIlF+H37cOJxm/5bjcuGcfRTHON7k9destmmbiIiISCMKcyIiEcbnw8f+nS8XW9a8uQwIb2bdq6sJ65JzIiIi0g4U5kREIkzAT8DsZxfLqLlzAZi8602+/LJtFikiIiJSn8KciEiE8fvwm7apzDFoEMHhI5jHG7pEgYiIiLQLhTkRkQgT9BNsq8oc4Dp2LrPMh7z3am2bLVNEREQkSmFORCTCEfDhd7RRZQ5g7ly8Vh1Jn8+ntLTtFisiIiICCnMiIjGOgJ+Qo+0qc8ycSdiTxGxLlygQERGRtqcwJyIS4Qz6CDjbsDKXkoKZMYNjHW/qvDkRERFpcwpzIiIRjlAbV+YAc8w8RoZXsOzVzbpEgYiIiLQphTkRkQhX0EewLStzELtEwfjit1i6tG0XLSIiIt2bwpyISIQz5CfkatvKHKNHE+rbn7moq6WIiIi0LYU5EZEIV9hHyNXGlTljcM6bw1znO7z5Wqhtly0iIiLdmsKciEiEK+wn3NaVOYC5c8kM7SL46ReUlbX94kVERKR72mOYM8Y8bIzZYYxZXm9ajjHmbWPMmsjP7Mh0Y4y50xiz1hizzBgzod7fnB+Zf40x5vz2eToiIvvOHfYRbuvKHMDRR2M5HMwOv6FLFIiIiEibaU1l7lFgXqNp1wDvWpY1HHg38jvAMcDwyO0S4F6wwx9wA3AIMAW4IRoARUQShSvsJ+xuh8pcjx4waTLHOt/kjTfafvEiIiLSPe0xzFmW9RFQ2mjyScBjkfuPASfXm/4vy/YZkGWM6QvMBd62LKvUsqxdwNvsHhBFROLKY/kIu9uhMgeYeXOZFPqcT1/bhWW1yypERESkm9nXc+Z6W5ZVFLm/Degdud8f2FxvvsLItOami4gkDLflx/K0T5hj7lwchBm97R2WLWufVYiIiEj3st8DoFiWZQFtdpzZGHOJMWaRMWbRzp0722qxIiJ75LF80B7dLAGmTCGckalLFIiIiEib2dcwtz3SfZLIzx2R6VuAgfXmGxCZ1tz03ViW9YBlWZMsy5rUs2fPfWyeiMje89COlTmXC8ec2RzvfpM3Xlc/SxEREdl/+xrmXgKiI1KeD7xYb/p5kVEtpwLlke6YbwJzjDHZkYFP5kSmiYgkhJA/hIsQeNqpMgcwdy59AoXs+mQlFRXttxoRERHpHlpzaYIngU+Bg40xhcaYi4CbgdnGmDXA0ZHfAV4D1gNrgQeBnwJYllUK/AH4InL7fWSaiEhC8Ff67DvedqrMAcydC8BRoTd55532W42IiIh0D649zWBZ1g+aeeioJua1gMuaWc7DwMN71ToRkQ7ir/KTDJj2rMwNHIg1YiTHrXmTp17/Jaee2n6rEhERka5vvwdAERHpCqKVOdOelTnAHDOPw6yPeP+1Wl2iQERERPaLwpyICBCs8QNgktqxMgcwdy5J4TqGbf2IFSvad1UiIiLStSnMiYjwXWXOkdy+lTkOP5xwkpd5vMEHH7TvqkRERKRrU5gTEaFeZc7bzpW55GTMzMOZZ95k3br2XZWIiIh0bQpzIiJAsNquzDnbuzIHmLlzGWmtomLF5nZfl4iIiHRdCnMiInxXmXO0d2UOYpco6LdS1ycQERGRfacwJyJCvcpcSvtX5hgxgpDDReaONRrRUkRERPaZwpyICBCqtStzzuQOqMw5nVRmH0C/QAElJe2/OhEREemaFOZERIBQjV2Zc6V2QGUOCPQbzCA2smFDh6xOREREuiCFORERIFxnV+ZcKR1QmQOcQwcxmAKFOREREdlnCnMiIkCotmMrc6mjB9OfrWxa4+uQ9YmIiEjXozAnIgJY0cpcB4W5pIMHA1D+9aYOWZ+IiIh0PQpzIiJAOFKZ86R1TDdLBg8GwL9mY8esT0RERLochTkREcDydWxljkGDAHBuLuiY9YmIiEiXozAnIgJYdR1cmevfn5Bxkl5SQCjUMasUERGRrkVhTkQEsPx2Zc6T3kGVOZeL6pyBDAhvZOvWjlmliIiIdC0KcyIiAJHKXFJ6B1XmgGB/XZ5ARERE9p3CnIgIYPw+ArhwujvuY9E1bDCDKWD9+g5bpYiIiHQhCnMiIgB+P346rioH0WvNbWHTWn+HrldERES6BoU5ERHsypzfdND5chHOYYNxYFG+orBD1ysiIiJdg8KciAhAwE/AdGxlLnp5guDago5dr4iIiHQJCnMiIoAj0PGVueiFw12FBR27XhEREekSFOZERABHwE/Q0cGVuQEDCBsHmWUbqavr2FWLiIhI56cwJyICOII+Ao4Orsy53dTkDGAQBWzc2LGrFhERkc5PYU5EBHAE41CZA0IDdK05ERER2TcKcyIigDPoI+js4Moc4D5wMIPYqDAnIiIie01hTkQEcAb9hOJQmUseOZgBFLJhTbDD1y0iIiKdm8KciAjgCvkIuTq+MmcGD8JFiLLlutaciIiI7B2FORERwBn2E3J2fGUuenmCwJqCjl+3iIiIdGoKcyIigDvkI+Tu+MpcNMw5t2wkHO741YuIiEjnpTAnIoJdmQvHoZslAwdiGcOAwAa2bu341YuIiEjnpTAnIgJ4wj7C7jh0s/R4qOs5kKGsZ+3ajl+9iIiIdF4KcyIigMvyE45HN0vADB3KMNaxZk1cVi8iIiKdlMKciAjgsXwQj8oc4Bk1TJU5ERER2WsKcyIigNvyE/bEpzLnOHAYfdnG5tXVcVm/iIiIdE4KcyIiQBI+8MSnMsfQoQD4Vq2Pz/pFRESkU1KYE5FuzwqFcROEOFXmGDYMAOfG9VhWfJogIiIinY/CnIh0e4Fqv30nKb6VuQH+dRQVxacJIiIi0vkozIlIt+er8Nl34lWZy8khkJbFMNZpEBQRERFpNYU5Een2/FV2Zc7hjVNlDggP1oiWIiIisncU5kSk2wtURSpzSXGqzAHuEUM5UNeaExERkb2gMCci3V70nLl4VuYcBw5jEAWsXxOKWxtERESkc1GYE5FuL1htV+YcyfGrzDF0KB4CVK4qjF8bREREpFNRmBORbi8RKnPRyxOY9et0eQIRERFpFYU5Een2QjUJUJmLhLl+devYvj1+zRAREZHOQ2FORLq9aGXOmRzHytyAAYRdbo1oKSIiIq2mMCci3V641q7MOVPiWJlzOgkOGKxrzYmIiEirKcyJSLcXrLErc66UOFbmANfBwxjGOlavjmszREREpJNQmBORbi8hKnOAY9hQDnKt51//gtrauDZFREREOgGFORHp9kK1dmXOnRbfMMewYaQHy6grKuXBB+PbFBEREUl8CnMi0u1ZdXZlLt7dLBk6FIAzJqzn5ptVnRMREZGWKcyJSLcXqkucyhzA5ceto6gIVedERESkRQpzIiKRypw7NTEqc6O965g1C1XnREREpEUKcyLS7YUjlTlPepwrc6mpdnXupZe44XpL1TkRERFpkcKciIgvQSpzANdcAwsXMqviJfLz4cUX490gERERSVQKcyIikTCXlBHnyhzABRfAwQfDtdcyeUKIpUvBsuLdKBEREUlECnMiIn4/IRy4kpzxbgm4XPCnP8HKlXzP9zglJbB1a7wbJSIiIolIYU5ExOfDRxLGxLshEaeeCpMmcdg7N5BEHUuXxrtBIiIikogU5kSk2zMBP34S4Hy5KGPg5pvxbt/EpdyvMCciIiJNUpgTkW7P+H34TQKcL1ffUUfB+PGc6X1RYU5ERESapDAnIt2eCfgJmgSqzEVNmsSY0FKWLtEIKCIiIrI7hTkR6fYcAR9+R4JV5gDGjSMjUErVt1t18XARERHZjcKciHR7jqCfoCMBK3N5eQCMsZaxfHmc2yIiIiIJR2FORLo9R9BHMBErc2PHAjCOpTpvTkRERHajMCci3Z4j6CfoTMDKXFYW1qBBTHAtU5gTERGR3SjMiUi35wr6CDoTsDIHmLw8JrkV5kRERGR3CnMi0u05Q35CiViZA8jLY1Ddar5ZWoelQS1FRESkHoU5Een2XCEfIVdiVuYYNw6nFaJfxSo2bYp3Y0RERCSRKMyJSLfnDPsJJWg3y+iIlnmoq6WIiIg0pDAnIt2eO+wj7E7QbpYHHoiVnEy+RrQUERGRRhTmRKTbc4X9hN0JWplzOjFjxjAleRmffx7vxoiIiEgiUZgTkW7PHfZhuRK0MgeQl8c4lvLKKxbvvx/vxoiIiEiiUJgTkW7PbfkJexK0MgeQl0dabTHTBm/j4ouhujreDRIREZFEoDAnIt2ex/JBop4zBzBuHAD3/XQZ69fDb38b5/aIiIhIQlCYE5FuLwkfViJX5saOBSDPWsqPfwy33w6ffRbfJomIiEj8KcyJSLdmhS08BMCTwJW5nBwYMACWLOEvf7Hv/vCH4PPFu2EiIiISTwpzItKthWr99p2kBK7MAcyZA88+S8am5dx/P6xaBX/4Q7wbJSIiIvGkMCci3ZqvMhLmErkyB3DzzZCZCRdeyDGzg5x3nj1pyZJ4N0xERETiRWFORLq1QJXdV9F4E7wy17Mn3HMPLFoEf/87t90Gubl2d8tAIN6NExERkXhQmBORbs1fZVfmTFKCV+YAzjgDTjsNrr+enG0ruece+OoruOWWeDdMRERE4kFhTkS6tU5TmQMwxq7OpafDD3/IaSeHOO00uPFGWL063o0TERGRjqYwJyLdWqDarsw5vJ2gMgfQuzfcdRcsXAi33cbdd0NKit3dMhSKd+NERESkIynMiUi3Fqy2K3OO5E5QmYv6/vfh5JPhuuvoU/4Nt98On34Kd98d74aJiIhIR1KYE5FuLVjTySpzYHe3vPfeWEnu3LNCzJsH114L69fHu3EiIiLSURTmRKRbi1bmnCmdqDIH0KcP3HknLFiAuetO7r8fnE649NJ4N0xEREQ6yn6FOWNMgTHma2PMEmPMosi0HGPM28aYNZGf2ZHpxhhzpzFmrTFmmTFmQls8ARGR/RG9aLgzuRNV5qLOPhuOPx5+8xsO8K3h2mvhnXdUnRMREeku2qIyd4RlWfmWZU2K/H4N8K5lWcOBdyO/AxwDDI/cLgHubYN1i4jsl1CNXZlzpXayyhzY3S3vvx+SkuCiizjtlDAAr70W53aJiIhIh2iPbpYnAY9F7j8GnFxv+r8s22dAljGmbzusX0Sk1WKVuc7WzTKqXz+47TaYP5/hb93D8OHw6qvxbpSIiIh0hP0NcxbwljFmsTHmksi03pZlFUXubwN6R+73BzbX+9vCyLQGjDGXGGMWGWMW7dy5cz+bJyLSsnBtpDKX0gm7WUadfz4ccwxccw3nHbqO99+Hmpp4N0pERETa2/6GucMsy5qA3YXyMmPM4fUftCzLwg58rWZZ1gOWZU2yLGtSz54997N5IrI/iraE+etZS6iri3dL2k+0Mtcpu1lGGQMPPAAuFz/96kf4fPDee/FulIiIiLS3/QpzlmVtifzcATwPTAG2R7tPRn7uiMy+BRhY788HRKaJSIJacv1z/OrJ8Sx6ZFm8m9JurDq7MudJ68SVOYABA+C3vyVn6fuMS/5WXS1FRES6gX0Oc8aYVGNMevQ+MAdYDrwEnB+Z7Xzgxcj9l4DzIqNaTgXK63XHFJEE5PjqSwDKXvwozi1pP+G6LlCZizr9dACuGPoyr74K1l71ixAREZHOZn8qc72Bj40xS4HPgVcty3oDuBmYbYxZAxwd+R3gNWA9sBZ4EPjpfqxbRDpA6qaVACQvWRDnlrSfLlOZAxg8GMaOZV7gZTZvhhUr4t0gERERaU+uff1Dy7LWA+OamF4CHNXEdAu4bF/XJyIdr1+ZHeaG7/iEYBBc+/yJkcB8dphzp3WByhzAiSfS5+abyaaUV1/NYcyYeDdIRERE2kt7XJpARLqAnZtqGRxaR6mrJwdYm1j1dmG8m9QuLJ/dzTIpvQtU5gBOOAETCvHjA17XeXMiIiJdnMKciDRp09vf4MBi8xH2KbCFz3wa5xa1E5+PMAZ3chcpO06eDL178/20l1mwAMrK4t0gERERaS8KcyLSpF2f2F0se115FrUmGeuTLnrenN+PHw8Op4l3S9qGwwHHH8+oja/jCPl59914N0hERETai8KciDQp9PUKgjjpc+Qo1udOoV/BJ/FuUrswfh8+usj5clEnnICruoJ5KfN58814N0ZERETai8KciDQpdeNKNnuHY7xJ1Iybzmj/VxR+WxPvZrW9gJ+A6SLny0UdfTR4vVzS9yXefFOXKBAREemqFOZEpEl9S1dS0msUAFnHTsdNkG//syjOrWp7Dr8Pv+lilbnUVDjqKA4vf5lNmyy++SbeDRIREZH2oDAnIrsp21bH4NBa/AfaYW7wD6YBUP1W1+tqaYJ+go4uVpkDOP54Moo3cDDfqKuliIhIF6UwJyK72fj2tzgJ4504GgB3nx5sTBlB1squNwiKM+Aj0NUqcwBz5gBwds+3FeZERES6KIU5EdlN6ceRkSxnjYpN2zl8OqPKF1Bd1bVOwDJBP0FnF6zMDR0KQ4dyctrbfPAB1NXFu0EiIiLS1hTmRGQ3gaUrCeGg78yDYtM8M6fTg1KWPr06ji1re86gj4CjC1bmAObMYcS2DwjUBvj443g3RkRERNqawpyI7CalYAWbkw7EmeqNTTvwR0cAsP3xt+LVrHbhDPoJdcXKHMDs2bhrKznUuVBdLUVERLoghTkR2U2fkpXs7DmqwbSUMUPZlDqSnp+/0qWGuneGfASdXbQyd+SR4HBw4UCdNyciItIVKcyJSAOVJX4GB9fgHzZqt8dKph3PlNoPWbO4Ig4tax/OkJ+Qq4uGuawsmDyZo8Nv8fXXUFgY7waJiIhIW1KYE5EGNr79LS5CeMaP3u2xfpccj4cAq+/sOl0t3SEf4a7azRJg9mz6FX5OJmX873/xboyIiIi0JYU5EWmgeL49kmXPmbtX5nqfMp1yZzaet17p6Ga1G2fYT8jdRStzALNnY8Jhzh/4Ps88E+/GiIiISFtSmBORBgJL7JEsBxx18O4PulwUjDiGidtfZVdxqOMb1w48YR9hVxeuzE2dCqmpnNP7bT75BLZujXeDREREpK0ozIlIA8kbVlDoGYorPbnJx1POPIGeFPPFPZ93cMvah8vyY3XlypzHA7NmkbfjbSwLdbUUERHpQhTmRKSBXsUr2ZG7exfLqKE/mUsQJ7X/fbkDW9V+PGEfYXcXrswBzJlD0qa1zD1wnbpaioiIdCEKcyISU1MeYEjgW3xDmw9zztxs1vY+jAO/eYVgsAMb107clg/L04UrcwAnnADA/w1+jvnzoagozu0RERGRNqEwJyIxG99Zg5sg7vzdR7Kszz/3BEaHvuaLZzd2UMvajwc/dPXK3JAhMHkyhxU9o66WIiIiXYjCnIjEFH9kj2SZe3jzlTmAYb84EYAttz7d7m1qV5aFl25QmQM44wySVyxi9rD16mopIiLSRSjMiUiMf8lKwhgGzh7R4nyp+cP5ttehjFv0EDXVVge1ru2FfJF+op4uXpkDOP10AP7f4Gf56CPYti3O7REREZH9pjAnIjHedSvY4h6MJytlj/OGL7yY4da3zL/54w5oWfvwV/rsO95uUJkbMgQmTWLGdrur5RNPxLtBIiIisr8U5kQkpufOlWzv0fL5clEH/eYMKk06PPRQO7eq/QSq/QCY7lCZA/je90hevoiTx23g4YfB6rxFVREREUFhTkQifNVBBvu/oXZIy+fLRTnSU/lmwlnMKPovm74ub+fWtY9oZc50h8ocxLpaXj3sWVauhC++iHN7REREZL8ozIkIABvfXYuHAO5xrQtzAH1/ezEp1LL8N0+2Y8vaT7Qy5/B2k8pcpKvlpA3/JTkZHnkk3g0SERGR/aEwJyIA7PzQHsky+7DWdbME6H/iRNamjWPgW//slF32AlXdrDIHcMYZuL5axI/nrOfJJ6G2Nt4NEhERkX2lMCciAPi+ssPcAXNaHsmyAWMoOflixvoW89UjS9qnYe0oWBOpzCV3k8ocwA9+AA4HP09/hPJyeP755me1LNi4EV57DUpKOq6JIiIi0joKcyICQNLaFRS6BpHcM22v/m7MTWdTTQplf7iznVrWfqKVOUd3qswNHAjHHMPgdx/iwEEBHn7YnhwIwLJl8K9/wS9/CUceCT16wODBcNxxcOmlcW21iIiINEFhTkQAyN2xkqKc1nexjEodkM3SCT/ksIJ/U7Bgazu0rP2Eau3KnLM7VeYALrkEU1TEH6e9yrvvwoQJkJYG48bB+efDvfdCdTWccQb84x9wySXwv//BqlXxbriIiIjUpzAnIgRqgwzyfUPN4NYPflLfsHt+iZMQa352Rxu3rH0Fq+3KnDOlG1XmAI49Fvr356Rt95OXB7m5cMUV8J//wMqVUFkJCxfC/ffDT34Cf/oTJCfDTTfFu+EiIiJSn8KciLDpg/V48eEau29hrvfUISwacgZTvrqPkg0Vbdy69hOrzHW3MOdywUUX4f3wTZa+WMBbb8Ff/2qfTjdypP0wfj+8+y5ccQW5M0fz6PQH+M9/YMOG7xZTXAxlZfF6EiIiIqIwJyLs+MAe/CRnxt53s4zKvfkqMqngyx8/0FbNanehGrsy50rpZt0sAS66CIyBf/7zu2klJfDvf8OZZ0LPnnD00fDAA1Bayqlf/oZ0RzV//as963//C0OH2rOEw/F5CiIiIt2dwpyIUPelHeYGzhm5z8sY9r2JLOlxJKPfuZ3acn9bNa1dhevsdrpSu1llDuCAA+CYY+Chh+Bvf4PDD4deveDcc+HDD+0T5l54wS6/PfccztJiHpj0AA8/bOfAM8+0B0hZvBieeCLeT0ZERKR7UpgTETxrVrDFOZC0vun7tRxz1VX0C2/hs7EXs+K51W3UuvbTrStzAD/+MWzbBr/6FZSXw7XX2ifLbd1qV+xOOglSU2H6dDjiCE5Z9zdcwToeftge8XL1KovJE8Nce62uVyciIhIPCnMiQo8dKynK3vcullF5V83ls0mXMX3z04w+fSSf58zl09+8QiiQmP3wwj67MudO64aVObCvOfD661BQAEuXwh/+AFOmgKOJr4brrsO1o4gPzn+Y116Dv/9wBUn5I3nNeyqFhRa3397RjRcRERGFOZFuLuQPMah2NdWD9m3wk/qMwzD1i7vxrdnMJ/P+wAEVy5n25xMoTBnORyffSuXmsv1vcBuyart5Zc4YmDcPBg3a87xHHAHTpzP5nZs5puoZmDoVCgrI/eRFbjzkNW66CXbsaP8mi4iIyHcU5kS6ucL5G0imDsc+jmTZlIwDe3Ho69eRW1nAZ794mrLkfhz+4v/hOKA/C8b9hC1vrWizde0Pq84Oc570blqZ2xvGwHXXwebN8L3vwYgR9oXnDj6Yq7f/En91gN/+Nt6NFBER6V4U5kS6ue3v24OfZB+6/90sG3Mlu5l66/cYVzGf5f/6ki+GnMmEZY/Qf+4Yvu51FKtuegErGGrz9baWFe1mmdpNK3N7a948OP10+yriH30EQ4bA3/9OUsG3PHX4P3jgAftadSIiItIxFOZEurmaxfs/kmVrjDl3PLPWP0zp0kJen3kT2cVrGHntKRSlDuPrq//drutuls+uzCVlqDLXKsbAM8/YVxNPTranHXsszJnDSUt+x3FTS7j4YliyJK6tFBER6TYU5kS6Ofe3Kyhy9CfzgMwOWV+/vFyO+eAasnet542Ln2Wn6cWov57Pxqc+7ZD11xetzHlS3R2+7i7DGLj1VkxFBc8MvZoeORYnn2xf0UBERETal8KcSDeXs20lW9pgJMu9lZrpYt6Dp9F72TsUOg7AecE5BHdVdmgbjN+HDw9Ol+nQ9XY5o0fD//0fyf95iM+OuZFt22DuXPtydSIiItJ+FOZEurFwMMygmlVUDWy7wU/2Vp+DMljz28fp6ytg5ewrOnblfj9+dL5cm7j5ZrjwQvr/80YWn34TW7fCrFkwcya8+y5YVusWEwzCU09BdfW+NaOurvXrEhER6ewU5kS6saLPNpJCLWZ0/MIcwFE3HMYLI35N3uJH2Hjrcx22XuP34Tc6X65NOBzw4INw9tmMfuJaNv3wd/zjlhrWroWjj4ZDD4U33thz0PrXP6pY8YM/cMWZ21oVysJh+OorO0vOmgUZGXDIIbBzZ1s8KRERkcSmMCfSjRW9Y18iIHN6x3ezrM8YOPzdG/jKNZnsqy6i5ouOuXSBCfgJGFXm2ozTCY8+Ct//Pu4/38hPbjqAjRfcwCN/2cGWLXDMMXbQeuWVpkOdZcGOm/7JH7ieS189gb/cUNPkanbuhCeegPPOg379YMIE+PWvwSou4a/HfsD2Zds5/HAoLGzfpysiIhJvCnOSGCwLfvELeP/9eLekW6lZZI9kecDc9h3JsjV69nNT8fCzVIVTqJp5LOEtRe2+TkdAlbk253LZ1yf46CM49FBcf/49F9wwiPVzfszTf/iW4mI44QSYOBFefrnhn777jsVJ2+6nOmcAE1nM8D+cy8svhgkEYP58+zJ3kyZBn15hfnvOeszz/+Pe3N+yadwJBPsO5MMVuVz54hGsSR5L9uZlHHoorFkTn80gIiLSEYyVwCcXTJo0yVq0aFG8myEdILyzBEevXGpSc0lZ+zX06RPvJnULnwy/gGHr36JPaGu8mxLzn6u+4sRbZlDe+yD6r/kQ0tPbbV2fDvo+vYu+Yqj/m3ZbR7e3ejXcdhs89hj4/YSPP5E3x/4/Ln/6UNauMzzxBJx1lj3rNdM/4uZPZxK4/2Gs8nI8v/oFt7mu4vmk73Ng9RLGmyXMSF/CCN9SvL4K+48cDvsC5uPHQ34+DB4MV15JsKqWebzJqtRJfPKJPVlERKQzMsYstixrUpOPKcxJItj+8uf0PvEQAEonzyXns9fsnTRpVyvTJlPjyWJS6dvxbkqMZcFdx77OT984ge1jj6b/Fy9CUvtUzz7vfwqZJes4uG5Zuyxf6tmxA+65x76VlBA+ZCrXVV7D7RtO4rPPICUFPht+DqclvUJy6VZITqbq/MtIe/ze2CKs1FTMuHF2aIvexoz57pp3UevXw1FHESou5TjzOut6T2f+fB0jEhGRzqmlMKe9ZUkIJZ+vA+A+12XkfPEmVTffHecWdX1WKMwB1auoHBDfwU8aMwZ+8tIx3Hbw/fT/+k22HX5G7OLebb6uoJ+QQ+fMdYheveDGG2HTJrjnHhzFO/nzypO5yn07p54Kt11Xwuk8S/jsc+1kZwxpD98JjzwC//0vfPstpqICPvnEDoQ/+hFMnrx7kAMYOhQ++ghn3968EppH782LmDsXyso6/FmLiIi0K4U5SQg1X9thrv/jf+FVx/F4fvsrwp993jYLT+DqczxtX7SZNKrjPpJlU9xuuGThRfxl0D/o8/nLbJv5PfD723w9rqCPoFPnzHWolBT46U/t7penncaNFb/gsIJ/k/T0Y3jxkfqLS7+b1+WCCy6AM86A4cP3rlo/cCC89x6uXj14zzMXx8rlTJgAV18NH39sXwJBRESks1OYk8Swbh1b6cuxZ6Sy488PURzOgWlT8Z94uj3u+D6yHv834QEDYcmStmtrFxEdyTJjWnxHsmxOZiZcuuQn3DzwHvosfImd006Al16Cioo2W4cj5FeYixeXyx6S8sgjeci6kGv4C1XjptvdJtvKgAHwzjt40pL4LGM2M/qu5bbbYMYM+zS71avbblUiIp2OzwfnnguffRbvlsh+UJiThJCybR1bk4fhdMIFv+rFfT9Zxk1cS90rb8OECViHzYDbb7e7aLWW30/lFb/BsXULtUccY59HIzFVX9gjWQ6YHf+RLJuTlQWXLv0pfx54LylffgwnnUQoK4eyMYcRvO53dpe7QGCfl+8K+Qi51M0ybpKS4IUXcI4fRy92kPbLS/f8N3tr2DB45x2STIDHluZTdeZFvHXjAiorLKZPt0fJFBHpjsJfLoF//5vg3GNh1ap4N0f2kQZAkYSww92fZX1mc/TmR2PTli6F3/ysnNEf38d5rv8wOmgPUhGeOAnHaafCaafBQQc1u8y6fzyM97KL+H/m7/za+hPu3jlkLPvEPndH+GzY2Qze8D69Q1sxJt6taVl5OTz2gI9NT39K7ldvc2T4bSaxCAcWfm86gcOOIPXEo2Hu3BbfE419kzKeXekHMHX7i+3Yetmj4mJ45hm4+GK7j217+OYbuOUWePJJqK7GlzeZ4yqfYv6Wodx8sz04Sl2dffP5dr/vdsPll9vFPhGRrmDDbx9myB8vopwMPD0zSf5ygT7kEpRGs5SEZtXUYlJTeG3q7zn20982fMyyLzD8+OPwzatrmVvzP85w/o/JoYUAhEaOxnnGaXDqqZCXRyyVBIPs6juS9cUZlL29iBd//Rk3LzqKqoGj6LXkLcjJ6einmVgsiyLPAaztOZ0ZW5+Od2v2SnU1fPABfPh8KVUvv0/ejreZzdsMw6681lx4GSn3/r1VI2Cu845ie4/RTN/yTDu3WhJGZaUd6K6+mjCGq/o/ya0r5jY7e1ISeL1QUwMZGfY10Y8/vuOaKyLSXpbN/j+Gv/MPzj7gYx7ddAT+PgfQ4+OXMMOGxrtp0ojCnCS04g9XkDtrDG+d/wRzHj2r2fnq6uC99+D552HR85s5rOQFTjfPcZg1HydhAmPH437ycRg9Gv+j/8Fz4dncmPccNyw9lbo6+OusV7l64amUZw0m+9PXcI8Y1oHPMrEUf7GB3ClDefuku5n9wmXxbs5+WbMG3ngDvnpuPfnz7+Ly8O1UjpxM+uvPwKBBLf7tRs+BbOo3lRkF/+6g1krCWLcOTjkFa/lySr/3E8jOxh2sxeWvwRWoxemvxeGrxdTWQG0tNX4nV5dczd0bjuOKK+Cmm5oeSFNEpLNYMXAewaIdDCv7kr8e8x6/+fgYkvBTmDWa4mknkH3uCRxwxiEYlzPeTe32FOYkoa28+SVG/fokPr3tM6ZdeUir/iYUss/Xff55+OjZHYzf+Dx/MNeT467EdfcdlFx/B9u2WZR+8DUzZtqnhgYC8I8fzOec507G6XYQfv4lco6b1p5PLWEt+tmjTLrnQpb8axn5546Nd3PazLJlcP/c//HnbRfiSXbiueRCnMfOtUe8aLTnbS37mtr8qXw2/FyO/Oa+OLVY4qq6Gn78Y/j3v+2RMlNS7PdJ/Vt02saNsHYtiw/6AfO+vYPkgT25+Wb4wQ9I+G7KInuyeTM88ACMHQvTptmDwUrXty3pAL7OPpzZ2/5NOAxP/6WA2iefZ/jql5kamI+bIMUml68HHkvNkSfQ/8I5jD00A6eyXYdTmJOE9vkPbmPKU79k/cKdDJ2Su9d/b1n2Tvx1F2/jikXncDTvAvCHEU/w21W7V/pe/Nu3jLn6WAZamyjsPQnf2ElkHj2ZPsdPwjHy4G5xsfKFo3/IgStfJL12Jx5v13q+5eXwmzPXctybP+dI3iMJPwGXl7pzfkT6LTdAjx5YXyyi5vC5lNV5eeua97nwptafZyddUDAITmfLqczvh5tvhj/+kUByBnekX8dvt1zKuEOSuekmmDVLoU46r2uugb/85bvf+/e3Q9306fbP8eNb1XNdOpFgaQWuHpm8dtifOXb+rxs8Zlmw5osyNv/zTbzvvMzoja+RFd6FHzcfO2eyufdkwjm5OHvnknXMNI67cngs4FmWfWnQ1avty4H26xeHJ9cFKcxJQvt08s8ZtehfpPjKcHv2fW8oEIDrfxMi/LdbGM9X9Hrz3xw5x9XkvMveK+abH/6F/oWfMS70JanUAFDjTGN7/4mEJ0yi57GTyThykn0B4i62l1aYNIyC9LEcVvxCvJvSLqLnWn70ejW1b37EhPXPcj6PEkjOwH3ZpQTu/AdF/h7867x3uf7RoV3t5ZX2tHIl/Oxn8P771GT15abwNfyt4hKmzPByww1w5JFd7uNCuoGpU+2fd98NCxbAp5/at40b7ekeD0ycCIceCpdcYl/2UTq3dU98xrBzpvHBL15k1q0ntjxzMMiOFz+l5NGXyfrkFXqVfYvTCgFQRxJ/6n8v0x+8kF694NrLyjlp4a/JZwnXuG9l/E+mctVVGldlfynMSUL7qt+xuEu2Mcb3ZZss76237MvKXXXVnneqQiFYvSLENy+souK9RXhXLGJI8SLGsQQvPgAKBs2kx6N/J33WxDZpX7xVrS4kbeRAXpt9K8e+9Yt4N6dDFBTA3y5cwfEf/D+O4Q1WczBPXfQONzw4QDvesm8++ABuuAE++oiqzH78mWv5e/nFTD40iRtugKOPVqiTzqGqCkZnFvLI9Ac58rKRMHly7CBmUdF3wW7BAli0yP7ePO88+O1vYciQeLde9tWCix9m+kMXsfaNtRw4dy/HELAsqKjA2rKVHWf+nN7L3+V+LuEt5nC343J6W9sI5+TiKNnJvean/Nr6M8m9MjjoIHvA6YMP/u7n0KGq+raGwpwktI3eg9mYlcfh2xJjRMHqavhqoZ/1L6/A98Z7nLT6L/RiJ8vyz2XIYzeSnte5v72+vvZJxt50Fp/evYhpl3WNgNpaL70E/7liISNPPojrb83WzrbsH8uC99+3Q93HH1OZNYCbuJa/l/2QSdOTOOIIu6LR0u3AAyE/P95PRLqzN9+E5fP+j//j1u8m5uTApEl2sIve+vVj+3a7t/G999qh7vvfhyuusGeVzuX9if/H1C//gcdXhdOzHyfBBYOErv0tzr/dDEBodB7OR/4JI0bAdddh3XUXPm8ma3pMZbGZzHsVk3infBJF2P0vHQ77oMDBB9tdemfMgClTNMBUYwpzkrCsYIiAO5kPxv+SOV/eHO/mNGnJh+Wsvfgmjl97O24CfD3sFHL/9AsGfG96pzz0/sXEH3Pwl/+BklIycpruhioie8Gy4N137VC3YAGV2QO52fEb/lFyJmVk7fHP8/PtS+yddRZkZ7d7a0Ua+PWv4bybRzJ8Zj9ct90CX3xh3z7/HFassFMb2Cc/HXIInHMOWyaeyN9uc/Hww/bVPqZNg4susq8SpPdw57AwZx5Z/h0cXNU2vaJ49VV7lOCf/KTh9UI//xzuv99+T61YAeEwAP6e/dg+cBLfpk/iC2sSr2yfzIJvc7EscLkgMxNSUyE93Q543/seHH443XbwFYU5SVi7lmwke/xg3j7jAWb/90fxbk6Llr2+hY1X3c2hK+4nh12sSxvHzuMuYMTvzyLroM5zIfKC1FEUugZzWPlr8W6KSNdiWfD223ao++wze1KvXoSHDSc07CACgw/CN+ggagceRE3fYdSZZObPhwcftLuGu91w1FH2DvHRR0OPHpCW1i3GZJI4On3Cep79ahjcdhtceWXDB2tq4Kuvvgt4H34IW7bAAQfAZZdRefqFPPJKT+65B7791n4Pz5ljV+xOPNG+NqMknnAYtroGsnX4LKZ883jHrbimxv6wW7TIfj8tWgTffGN/dgLBiYfw7ZhTeTP5ZNZbQ6isc1NcbHeAqKmB3r3htNPsYHfYYd0r2CnMScJadc97jPzZUSz4w7tMv+7IeDenVbatq2bxFf9i4DsPk+dbRAAXi3sfR+Cs8xl/3XGk5Xji3cRm+Qt34BnYm5en38QJn1wT7+aIdE2WZe/0fvGFvYf77bf2BRGLir6bxxh7/PesLCgvJ1haztbUgzjL8yyfbBrYYLaMDPso9Z5uWVn2z+xse4j5tLQOf+bSyVRVwbWZ93Bn+Gf2+3RPI5sEg/Dyy3DnnfZ5o243nHQS1kUX82X2UTz1rIunn7YvdeD1wrHH2sW8rKymb5mZOl8qHtZ9VcGwCZl8cepNTH4uzvsCFRX2AYOPP4YXXrADXlRqKvToQWDe8bw76nIe/uRgXnkFamuhTx8YOdKu4rndu9+amt67tz1IVV5e5ztIpjAnCeuzix9k6kOXsObtAoYf3fIFnhONZcGK/65g5y2PMerLx+kd3kYxPVjWeza1uQcQ6jsAxwEDSD6wPxmjBtBzTG/6DnC2+xeXb8Fitvz2PkzAR48TDyPj2MPsvusOB9/e9BwHXXs67/9pAUdc2z2vsScSN5WVdqiLBrxvv7WnZWbafYn+/W+stDS+vf115pfnUV5Oi7eyMvtnMGiRQQXZ7CKbXaRTybeOkQyZ0pOZM+1//wED7Ow4YIC9f7Q/tmyxB8Q48EB72V6v/XlYXW23JyPDDpKdsBd6t/PWWxCceywz+60hdcuavfvj5cvhoYfg8cehpMQ+ijBnDuG5x7C45zwef6s3zzwD27a1vJjkZLvQd8QR9o72uHFQV2cHzVDIvkzCgAH2OabSNt7542cc/dtprLv1RYb9Yg8jWXa0jRvtEzm3b7c/5DZvhhdftC8Pc+yx1F3wY14OzOPZF90UFdkjmbd0Cwa/u++zx7WjZ0/7cjJTp9oHG8aPty8pmsgU5iRhfXzYNUz55FbCVbV4UztvvTzsD7Lyjrfx3f8ofQq/INe3hST8DeYJ4mQr/dju7E9x5lBqJxxG3+/PZPxZI/Em78deT3U1VV+sYvtbSzGPPszQogVUkUo1qfRmBwAh46QmtSfhQAi3r4rKTWX0HqhvRpGE8vXXcMwxdsC75x47dZWWwq5d390a/W6VlkJZGSZyHkp9m7zD+cA3nW+tAymiL9voQxF9qcnoS9LAXgw7yMmYMTB6NAwa1LBa4vXuHsYqKuxrkf331kLG1n3OBoaw1hxEep9UKkqDpPmKyaCCUnKocOaQleMgPd3OqWlpNHk/Pd0+FWvoUHsQhD59Ot8R887sd7+q4eq/9cD5k0vw/OOOfVuIz2dfC+bVV+H1179LbxMmYB1zLL4DR1Nt0qgI27eyQCql/jRKfGkU16VRWulm5Ur46CP7rd8UY+yqygEHfHdQIifHzo/Z2fb7tvH9pt7DYnvu2Ic47fWL8a1YS9KovRzJMh62b7fPu/vHP+z7PXvaJxnn5zdfhmviti3Uk7e+6snbb9udJzZvthfvdNq9GQ45xB585ZRTEu/cT4W5NlS9o5qCV5Yz9OQ8knM01M7++nzQGfTYuoxhgW/i3ZS2ZVlYO4spW15I2fJCatZuIbihELYUkrSzkB47VtHTvxWAUrIp8g6lKncQVv+BkJGOSU3BmZlOxiEjGXhCPskDehCuqWP7h6vZ+eEKfItXkLR2ObnbVtCnbgMO7P/j9Qxlfv7PGfS7C0npk8FXz6yl8vWP8WxcQ3L1Tnqyk4LeU7lym7pYiiSkzZvtQLdiRcPpTud3e6v192KbmpacDMuWwSefYH32GWb79t1WE8JBoXsonwfH86U1ng0MoYIMysmkggxq3ZmYzAxc2elkZDvJzITixRv5UenNXOx4GHf4u4NVNZ5MvP6K2OcQ2AeQqry5VLsyqXZmUEU65WRQEU6nNJTBrmA6xf4Myq0MKkmnAvvnVs9gGDKUwUMdDB0Kw4bZtwMOsHfme/a099ukbfy/Ua9xy6rj7ErInDn7v8BwGJYutUPd66/b1zNo4kBDAx4P9OlD+JBpbBxwKGtdI0h1+Ug1NTj8dezaZRf+dpValJRASSmUlDrY6suhmNzYrYIMwDRYbHLydyPHut3Njyrb3GNNTU9Pt3ujHnSQfRCk/vuxtBQee8zOtn36fDcEf06OfRCj8S05OT6B87nBv+TYTfeRHKjsXCeeBQLwxhv2Rn75Zbtat7dGjrRLwDNnsvOAiXy6bQiff2H4/HN7rJbycrsDxYEHtn3z94fCXBv68m/vMuFXRxPEyVrvGLb3G08gqxfhlDTCqfYhR5ORjiMjDWdWOq6sNFzZaXhy0vHkpOHtkUrf/vbRyoQRDEJxsX20Y8cO2L4da/sOglt34HA7cQ4bDIMHQ26u/aljjP1uX7WK0IrVhHaW4h59EGbMaPsTLivL/pRKTd3jt+43qRMoS+7DIcXdbDAOy6L66/Wse/hDaj78HPeWAjLLNtIrsIVUqnHS8Muv2NGT7HBJbHoAF2scB7M1azQVB4zGjB5N2iGjGX/mQeT2avqwts9nd4/KyrK/WKR1wuEw4XAYl/YgpaNUV8PixXZ/xWhI259+iz6fXS0pKvru59atsGoV4S+/wrFhfYt/XuNMo8qRSXZwB04nOC6+yL7Q2JYt9uAF27bZo7X06mW3ubTU/i7ZscMu51VU2CWX+j8rKuwdsybUOVNYkzSGlYHhbAgMYDMDKWRA5DYQX3ouSckOvF77fCuvl93up6R891lXP+s2/tmdu4NWV8O/0i/jItejeCpK7A3X1srL7fdaVZV9q65u+DN6f906O/gVFu7zqsJOF770XGpScqny5lLh6kGdI5kAbgKWGz9uAmEXfssdu/nCDW91IfvmC7upDUZ+D7qoDbqpDbkJ4KaMLFYxEh9e3G77YMPBB9tB76WX4ADft/ys1zNsDvXlk5KRrGJEZFTb3d9oDsd3wS5aeYzeBg367iBGZqb9r9UWucuy4P2keQzL2MGg4jYayTIeKivtfdfW9rEMBOyLzr7/vn1+XnW1vZysLJgwASZOJJw/gYIeExly9DCMM7G6CCjMtaFd60r55oEP8X2yiPRvFjFg1zIyQrtiF5hujS30oyDpYEp7jSA0YBBJ/XJJHdyTrANzyR2RS69Rubhys9qtr4n/08Vs+flNpBSsIrV6O2l1JU3O58ODgzBugs0uq5oUdpHNALY0vS6nF39SOgFPGgFvGkFvGsGUTIJDhuOakEf2H3/JolHnc8Tyu9rkuXV2gQDUVFtU7/JTuWkX299bQe2nS3CvW0WgZz8cY8eQdehoDjhqOL0GeLrtTkhHWrNmDYFAgFGjRsW7KSLtI7rDXVFh34/+rH+/osJOQJdfbvdzaws+X8OAV14Oa9fa3U2//hpr/XrYsgXTROgLOVwEHEkEHF78jiT8xr758OIjiWpS2BnKYbs/h51WD0qwb8XkspmBbGQQZWThcpkGBc1o9SUpqeHP6P30dPu4Zo8e9q3+/R499v7aWJZlf+5HN0F1tb2MaHfUtqzc1NTAe+/B+vV2hbNoq8Up/28oqYeMpddnL7XNSvbX5s2wYYOdxpOT7Y1ef18oujGCQburcXFxy7e6uuZ39KOXXNgHYaeLsr4jKcgaz1dmAh9Vjmd7RTJ/zLmViev/u1u3Z8sYQkkpBL1pBNyp+Nyp+Fxp1DpTqTWpVJk0tod6sq62HyvL+7O8bhgrGE01DUcxysqCvn3tW8+e9jHzlJSmb40fM8Y+TXfJErjy1oHUTJ7FwZ934EiWiSQQsCvIixfDl1/at2XLvqv0ffmlfSJdAlGY6wiBAKHyKuqKq/AVV+IrqcJfWkWgtJJgWRWh8krC5VVYlZVYGzeRsmk1fXatIj1U3uTigjipcPegOjmXQGo2QXcyIbeXUFIyYbeXcFIy4SQvVlIyVpIXKykJF0Hs40ZBXFlpJPXKIKVPJqn9MknqmUEoaFH4qzsZ9NULlJDDh+YIyr29qEruRU16b/xZvQj26I3VsxeOPr3w9s6kpipMybIt+L4pwFleitdrkeQBV0YKwQNHkDpiIKnpDratqST49SqSCtfhqqsiKVBJkr8Kb9C+pYQrSaOKNKrIZhcjWE0a9lGRd06+m6Ofv6wjXy2RVqmsrOTbb78FYPz48Th0Mo9IxwqH7QpfYaG9o19YaFf+fD57R93na/pWXQ2lpVglJVBSggnuflDSl5ROtbcHle4cKhzZVDvSqXakUUNq5NsqjSorNXauV0UolR01aeysS6O63jzVkXOUwZCSYgcxh+O7KkooZGeP6K3+79F9fkOYTMpJpzLW1RVMg8oNfPd3DseeR+9LTf3uPMhNm+D99yz6+9czgEK20J8MKviSidTdfh/eKy7tgBczwUSTdOPqzZ5uxcV2IvrqK/tWf4SXtDS47DL7Suo1NbBypZ2gysvt92TjymR0WmWl/T6PVosiqvsMpazHMKo8PSh357Ld9GZDaBCrawexvro3u+qSKavzsqvWS5nPSwA3TVUAowxhxri+YVlwFCVX3USPv+qUixi/3369Fi+Gc89NuBF3FOYSlWVBTQ1VBcXsWFlM6bfFVGwoxrd5J8Ft9lEld0UxybW78Fh1eMO1JFFHMrV46/2sXxUMYwjhbLaaVk4GT/b/fxx8zxXMOjGjwyo74bD9f+Lz2Z9vhZvCFC8qILB6HYddcxg5/XX+oSSeb775hqqqKgBGjRpF8t4edheR+LMse8e5pAR27rSTTUGB/bP+gDLRbn/1d7JbKeTyUJnej13J/al0ZeEMBXCEAzjCQVxWAJcVwGkFcYUDOK3I9HAAZziAM+TD6yvH1NsfCznd1KTk4nOnUedIoc6RgmUc9nmJBsLGScB4CBr7EG4ADwHc+PHY3QktN7UhD9V+N1V+D4Ocmzk8/AHZVU10Y9y40e7PJ/tm2zY71G3dao+csT/nMVRUfNd9OVKhZvPm7967ZWUt/rllDHgjB/w9XrsI4PYSdHkhbJFe9C2O2sj7uq3Ok5QOoTDXhViWfVQvELDDUSAAAV+YQLXf/iAPOfH5oGy7j4rCCmqKyqnZVoFvRznB8mqGnHMox52Tre55IntQUVHBmjVr6NGjByUlJQwdOpTsRBveSkTaTzhsH32sf35XU+d7VVbaO9tbtnzXXbV+qax+yaypaR7Pd4PXpKfbVZxoN8FoqKypiV1YGWhiR2AP93NyYOZMezz2Aw+0z5ssLLT7hl7aDatynVVtrX0QYuNGu5IXrVC35hYK2eMajB5tjwI5eXL3PWG0E2opzOmM/k7GGPs7wOWq3zffATQ+cTkJ6Bm5icje2rp1K263mwEDBlBSUoLP1/rzYkWkC2g8OoVIvCUn26OtHHxwvFsiCUQngIiINFJeXk51dTV9+/bF5XLhdrupq6uLd7NEREREGlCYExFpZOvWrXg8HnJzcwHwer0KcyIiIpJwFOZEROopKyujpqaGvn37YiLnEyjMiYiISCJSmBMRibAsi61bt5KUlESPHj1i071eL6FQiEAzFzkWERERiQeFORGRiLKyMmpraxtU5QCSkpIANAiKiIiIJBSFORERvqvKeb1echpdJ8jrtUeLVVdLERERSSQKcyIiwK5du6irq9utKgfg8XgwxijMiYiISEJRmBORZlVXV7Njxw6s+her7YKiVbnk5OQmLwxujNEgKCIiIpJwdNFwEWkgHA5TWlrKzp07qampAcDtdjcZcrqK0tJSfD4fw4YN260qF+X1emPbQ0RERCQRKMyJCGCfD7Zz505KSkoIhUIkJydzwAEHsG3bNoqLi7tsmLMsi6KiIlJSUsjKymp2vqSkJHbt2oVlWc0GPhEREZGOpDAnCaO0tJS0tDQ8Hk+8m9JtWJZFWVkZO3fupLKyEmMM2dnZ9OzZk7S0NAACgQBFRUX4fL7YqI5dSUlJCT6fjwMPPLDF+aKDoPh8vth9EZGuIhwO43Do7JvuxO/3U1BQQN++fUlPT493c2QfKcxJQti1axcbNmwgOTmZESNG6AulA+zatYvNmzcTCATweDz079+fHj164Ha7G8yXm5tLUVERJSUl9OvXL06tbR/hcJiioiJSU1PJzMxscd76I1oqzLUfy7KoqqoiLS1NFVCRDrJ161aKiorIzs6mV69esYN50nVZlsX69euprq7G5/MxatQonE5nvJsl+6DD95iNMfOMMd8YY9YaY67p6PVL4gkGg2zatAm3201tbS1FRUVttuzKyko2bdpEKBRqs2V2BWVlZaxfvx63282wYcMYM2YMffr02S3IgT2SY2ZmJsXFxV1uIJSSkhL8fn+rQmprL0/g8/nYunUrZWVlhMPh/WpfOByO+za3LAufz9dkO+rq6tr82nubN2/m22+/ZdOmTXv1d3V1dRQXF7Nx48ZuMWiPSFuprKyMdTWvqKjgm2++YfXq1bFu5dI1bdmyherqanr37o3f72fLli3xbpLsow6tzBljnMA9wGygEPjCGPOSZVkrO7IdYgeoaJeK6C1eNm/eTCgUYsSIEezcuZNt27aRmZm530cGo4HFsiyqq6sZPnw4LlfXLEYHg0Hq6uoahFav19tkt8iKigrWr19Pamoqw4cPb9WRuNzcXNatW0d5eXmL55XtrUAgQGVlJQ6Hg8zMzA6txJSUlFBYWEhaWhoZGRl7nN/pdOJ2u1sMc+Xl5WzYsCH2OhhjSE9PJysri8zMzL3qQlxZWcn69etxuVwMGzasw6qBwWCQ6urqBrfoOZTDhg2LvadKS0spKCjAGMPQoUP3WNlsje3bt7Nz506Sk5MpLi4mKSmJPn367DafZVnU1NRQVVUVuwWDQQAcDgfhcJjy8nIGDx7c5AGKveH3+6mrqyMQCJCZmdllP0P2RkVFBdXV1eTk5HTJrtfdSSAQYMOGDXi9Xg466CDA/mzcsWMH69evx+Px0KtXL3Jzc1W1aaVgMEhVVRXp6ekJu8127drF9u3b6dmzJwMGDMCyLHbs2EFOTs5e7XuFQiEsy2rwuVhbW8umTZvw+Xz06dOHnj177td3u7r/7pnpyKMuxphpwO8sy5ob+f3XAJZl3dTU/JMmTbIWLVrUYe1rjWAwSEVFBW63G7fbjcvlatcwFAqFYkf3LcuKHSXb00+Px9PkTkxtbS3bt2+ntLR0tyNu9YOdMQaHw4HX643tiDqdTnw+H1VVVbHgEA6HMcaQkZFBenp6kzs60XZH54/+47tcLsrKyli3bh19+/alX79+hEIhVq5ciTGGwYMHU11dTVVVFeFwOPY39W9Op7PB79HXoaSkhIKCAlJTU+nVqxcFBQUkJSVx0EEH4Xa7Y+1papu2Zvs2ntflcuH1evf5AyscDuPz+QgEAgQCAYLBIKFQiJSUlAZfCKFQiNraWmpra6mrq4v9DAQCTS43PT2d3NxckpOTCQQC1NXVsWXLlti2aO2OqWVZfP3116SkpOzx3LL6fxMMBhs8p+j9QCBATU1Ng6pOSkoK/fv3b1Wwaq2amhpKS0spLy+PVRjT0tIoKiqirKyMtLQ0hgwZ0uqQ9c0332BZFiNGjGgwPRwOs2PHDrZs2UJycjJDhw4lEAhQVlZGeXl57HkmJyeTmZlJVlYWKSkphMNhqqurqampwe12k56ejtvtZtu2bbELmEcPvAwePLjVg9AEg0EqKytj5/clJyc3udMdCoXw+XwNglv9sJqcnExqaiperzdWMR86dChVVVUUFRWRlpZGOBympqaGgQMH0qtXLwKBQCxcOZ3O3W71/0/rKy0tZcOGDWRnZzNkyBAKCgooLS1lyJAhZGZmxj4LqqqqqK6ujn0uJiUlkZaWFrslJSVRXFzM5s2bcTqd9O3bN/b8g8EgZWVl7Nq1i2AwSFZWFtnZ2aSlpeHz+airq9vtVr+6aoyhR48e9OrVi+Tk5D2+Dnv6HwgEAjidzthn7P4Gz9YKh8MNDua1Vk1NDYWFhVRWVsamZWdnk52dTV1dXez94/F48Hg8JCUl4XK5Yt+V9T+3G39WhsNh6urqMMbg8Xj2aSfYsqzYcwNwuVzteoCopcGQgsFg7Badt/6tuWlgH4hLSUlp8NrUfy8Fg8HYd7TT6Yy9jk1t1yi/38+uXbvYtWsXgUAg9t4vKiqisrKSkSNHNnhPW5ZFeXk5O3bsiB1wy83NpVevXvsc4KPfu6FQKPYdF/1pjCE5OZnk5OTYudylpaXU1taSlJQUeyz6edbcd1dT3+nRbdL4Z1sLBAKxA1LRfZa+ffvud5iB7/4/LMvC6/Xu8f8juh2i+1zhcJhQKBT7nN+1axder5eDDz4Yh8PRYN9r+PDhsf3AxreoqqoqiouLY/uS6enp5OTk4PP52L59Ow6Hg+TkZKqqqvB6vfTt2zf2mtVfTv3XJNoLpPEtGAzG9uWys7Ob3JbhcLjB/1xzN2PMPh1cTQTGmMWWZU1q8rEODnOnA/Msy7o48vu5wCGWZf2sqfkTMcxVVFSwZs2aJh+Lvtnr/xM0dT/6oRw9eh/9cgNiH3TR2/5wOByxL0VjTGynK/qhnJycHPvia+5WU1NDIBDAGIPL5YqFhvpfJPXbGv0gbryc5rYX2F9cI0eOjP1eWVnJt99+G5vP4/Hgcrli/4wtdV2r38709HSGDRuG0+mksrKStWvXxl6D5sLP/oheiyz6gdXcl3bj36Mfsi1JTk6OfZFHRcN2/S+5+uuurKykuLgYv9/fYFnRI7B7u+O4ZcsWtm3bRkZGRpNdb+q/7vV3YhpzOBy43W68Xi/p6emkp6dTW1vL1q1b8fv9JCUl7fZFAs1/ATe1UxjdSYi+d9PS0vD7/bFQZYyhX79+9O7de6++ZDdt2sTOnTsb/G/5/f7Y65Kdnc3gwYN320Guq6ujvLycsrIyqqqqAGL/O41F3+s5OTkccMABhEKh2HkNTZ1H1vj3QCBAbW3tbsuN/r9GPw+iO4X115uamkpqaippaWmkpKQ02GHw+XysXbs2FvZ69OjBoEGDsCyLDRs2UFZWhtvtbtX/ljEmthNav93RanG0urZmzZrY9opKSUlpEN6aex/X1tayYcOGJrdF9MBTeXl5k58nHo8Hr9fb4OZwOCguLqakpATLsmLvY7fbjcPhiP1PRN//0fdgU6Kh1u124/f7Y/+jjd/7TdmX7+zo/0T0/7P+MlwuFx6Pp8FzaBwyordAIBDbQc3MzGTnzp0UFxfH3sfRbRUMBmMHp5oTff5Op5NAILBbd936QTO6vaPbLfp9Vv85NfVdEw2Ge7vT1tJBvPqfL43XFX3NGoezfeX1enfbX9iT+t/N9Z9P9LVISUnB7XZTUVERa+MBBxxAz549m11mTU0N27dvj3W7dDgcsWAe3aepr/Hve7tPE12mx+NpcKCl/t9HP8eaC8StXU9TQa+5+81Nqx9QLcsiJyeH7OzsWBCOHthoSUttb+r/I/rZU/97t354a2l5LpeLtLQ0Bg4c2OB/o6X92/qi293hcNCjRw+cTie7du2KtbFHjx4MGDAgdsC+sLBwr7vjR7dZUlISbrc7dvkgt9tNUlLSbv+LLe0X1j+QVH9bRj/X6++bR2/Dhg1LuLDXqcKcMeYS4BKAAw44YOLGjRs7rH2tEQ6HYztv0Vv9f5493Y8eDY3uVMF3HwSWZTV5JDs6354+YKI/LcuK7bj6/f4GX94ZGRnk5ubuVUUmehQnGAzGdqDqV6Gi85SXl8fCYv0jhfV/j96CwSB+v59gMEjv3r13O8odPd+oqdEto19u9W/Rf+joze1207dv3wY7i9XV1bEjRtEPwsY7TS1t16Z+Ru9Hd6Bra2tjR38av17N/R4NBtFbdCfHGEN1dTWVlZVUV1fHAlA0uHk8nj0GEcuyB5OIDnLidrtb9XdNiY561bhSUf9+9EMx+hyiR+Tr32/uiGI4HKa4uJjKyspmQ3D959Wc+u+9aBfH6Pu9rq6OqqoqUlNTW1VZaSwQCMS+tPx+P6FQKPalk5yc3KouqNHqfmVlJW63Oxac/H5/rPKUnp7eYOcqHA6zdetWqqur9/j8nU5nrOto9ELn0Qpu9LMmHA43eM+lpKS0qhtnKBSisLAQr9dL7969Y9Mty2L79u3U1NTEwqDH49nt4FT9I/GNd+6iIaH+Z1MwGKSwsDC2U5eamrpXFZvoTmz03L5od97oOqLdMWtra3cLbs0JBoOxHYvod0D916P+53ZT/wPR8FdfTU1NrB17u2Pamv/lxp/H0Z+hUCgWJqO9LFq6Rbvc1X8Nor0FkpOTd3ttmjpaHj2I0PjzOrrtgQbfrVH1Q010R7K575loO6L/p41foz1ty5Z+Nj4oEm1b9Ge0Whd9raPzNVXhaGqaZVnU1tZSXV1NbW1t7Puqca+U6PatH2ij9+v3gqn/2mVnZ8e2cSgUory8nGAwSK9evfa4baKvS2lpaey7O/pa1N9GjbclEAt/0TDe1M9wOExtbS01NTWEw2GysrJ26+4X7fJcW1vb4MBcS9u3qddnb6e19Dh89z/vcrnIzc1tENyi1c36n3V7+p9t/Hi0509ycjLGmFivgUAgsFtvqsY/G99PSUlpMVhGe141d0AnevN6vWRnZzf4n49ehzUlJaXBMqOvbf1t1nibRkW/kxp/RlqWRUVFBTt37iQUCjX4X2+q11ZLvQDq6uooKyuL9fBo/L9ijGHQoEEKcy00pNN3sxQREREREekoLYW5jj6j8AtguDFmiDHGA3wfeKmD2yAiIiIiItLpdeiwXJZlBY0xPwPeBJzAw5ZlrejINoiIiIiIiHQFHT7GsmVZrwGvdfR6RUREREREuhJduEFERERERKQTUpgTERERERHphBTmREREREREOiGFORERERERkU5IYU5ERERERKQTUpgTERERERHphBTmREREREREOiGFORERERERkU5IYU5ERERERKQTUpgTERERERHphBTmREREREREOiGFORERERERkU5IYU5ERERERKQTUpgTERERERHphBTmREREREREOiFjWVa829AsY8xOYGO827GXcoHieDeim9K2bx/arvGl7d+xtL3jS9u/Y2l7x5e2f/x0tm0/yLKsnk09kNBhrjMyxiyyLGtSvNvRHWnbtw9t1/jS9u9Y2t7xpe3fsbS940vbP3660rZXN0sREREREZFOSGFORERERESkE1KYa3sPxLsB3Zi2ffvQdo0vbf+Ope0dX9r+HUvbO760/eOny2x7nTMnIiIiIiLSCakyJyIiIiIi0gl1+zBnjBlojHnfGLPSGLPCGHNFZHqOMeZtY8yayM/syPSzjTHLjDFfG2MWGGPG1VvWw8aYHcaY5XtY5zxjzDfGmLXGmGvqTf9ZZJpljMltr+ecKBJs2z8Rmb48six3ez3v9pZg2/UhY8zSyPKfNcaktdfzThSJtP3rPX6nMaaqrZ9rIkik7W2MedQYs8EYsyRyy2+np50wEmz7G2PMn4wx3xpjVhljLm+v5x0vCba959d7r281xrzQTk87YSTY9j/KGPNlZPt/bIw5sL2edyJIsG1/ZGTbLzfGPGaMcbXX824Vy7K69Q3oC0yI3E8HvgVGAX8FrolMvwb4S+T+dCA7cv8YYGG9ZR0OTACWt7A+J7AOGAp4gKXAqMhj44HBQAGQG+9t0822/bGAidyeBH4S7+3TRbZrRr35bo2uvyvfEmn7Rx6fBDwOVMV723T17Q08Cpwe723Sjbf/hcC/AEfk917x3j5deXs3mu854Lx4b5/utP0j6x4Zuf9T4NF4b5/usO2xC2GbgYMi8/0euCiu2ybeL06i3YAXgdnAN0Dfem+gb5qYNxvY0mja4D28OaYBb9b7/dfArxvNU0A3CHOJuO0j038B/Cne26MrbVfskHwvcHW8t0d32v6RL6P3I+vrkmEuwbb3o3SzMJdg2/9z4MB4b4Pusr3rTcsAdlHv4F13ucX5/f4NcEi96X+O9/boDtse6Amsqzd9BvBaPLdFt+9mWZ8xZjB2dWwh0NuyrKLIQ9uA3k38yUXA63u5mv7YiT6qMDKtW0uUbW/s7pXnAm/s5bITUiJsV2PMI5H1jQDu2stld2oJsP1/BrxUb71dWgJsb4A/Rbr23GaMSdrLZXdqCbD9hwFnGmMWGWNeN8YM38tldyoJsL2jTgbetSyrYi+X3aklwPa/GHjNGFOIvd9y814uu9OK87YvBlzGmOgFx08HBu7lsttUfPt4JhBjn8vzHHClZVkVxpjYY5ZlWcYYq9H8R2C/OQ7r0IZ2QQm27f8BfGRZ1vx2WHaHSpTtalnWhcYYJ3aQOxN4pC2Xn6jivf2NMf2AM4BZbbG8RBfv7R3xa+ydCQ/2sNdXY3fB6fISZPsnAXWWZU0yxpwKPIx91LzLSZDtHfUD4J/tsNyElSDb/xfAsZZlLTTGXIV9KsPFbbj8hBTvbR9Zx/eB6AG7t4BQWyx7X6kyR6wa8xzwhGVZ/4tM3m6M6Rt5vC+wo978edgfXCdZllWyh2UPrHeC8I+BLTRM8AMi07qlRNr2xpgbsMvnv9z/ZxZfibRdASzLCgFPAaft3zPrHBJk+48HDgTWGmMKgBRjzNo2eYIJJkG2N5ZlFVk2H/ZBiylt8wwTW6Jsf+wj59H1Pw/k7d8zS0wJtL0x9mBtU4BX/387d6xaRRDFYfxbEESwEIOWomJnYWchCGIldr6CNlZiL1gHkyIPkCaiiIVvoCKCBtFCjSAYCVba+AYGxmJOuNdwtbE4OzvfD5a7zM5d9v73NrOzZ/7/l7VhDPkPw3AMOFdKeRPtj6k1YpM2huwBSimbpZSLpZTzwEtq/V6ezHc8x7BRa3nuA2v72lf4s6DyXuyfAL4CF/5yvpP8+x3cA8AOcIpZQeXZfX2+0UHN3Jiypz7Neg0cys5lKrnGdZyZu6ZVYDU7n17yX9BvkjVzY8qbWd3GAKwBy9n5dJb/MnA99i8Bb7PzmXLecfwmsJGdS2/5R/tPZotw3ACeZOfTQ/Zx7Hh8HgSeAZdTs8m+Odkbddq1AB+B97FdBZbiBm0DT4Gj0X+dWui71/fd3LkeAT+AX9QnhAtXt4nzf6GuknNnrv1WfG8X+A6sZ+fTUfa70bZ37rvZ+bSeK3Xm/xWwBXwCHtJBgfxY8l/QZ6qDudHkDTyf+78/AA5n59NZ/keoM0RbwCZ15iI9o6nmHcdeAFeyc+kxf+Ba/Nc/xH04nZ1PR9mvAJ+pi6/czs5miIuSJEmSJDXEmjlJkiRJapCDOUmSJElqkIM5SZIkSWqQgzlJkiRJapCDOUmSJElqkIM5SZIkSWqQgzlJkiRJapCDOUmSJElq0G8qPxHwHTCKtAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.plot(returns_sq.iloc[end_loc - 1 :], color=\"grey\", alpha=0.4, label=\"Price Returns\")\n",
    "plt.plot(res_rec[\"h.1\"], color=\"blue\", label=\"Recursive window forecasting\")\n",
    "plt.plot(res_rolling[\"h.1\"], color=\"red\", label=\"Rolling window forecasting\")\n",
    "plt.legend(loc=\"upper right\")\n",
    "plt.show()"
   ]
  }
 ],
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