Tesla 2025 Valuation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "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",
    "plt.style.use('ggplot')\n",
    "\n",
    "from model import TeslaValuation\n",
    "from simulation import MonteCarlo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"9\" halign=\"left\">Electric Vehicles</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">Tesla Consolidated</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Cars Produceable (units, not in millions)</th>\n",
       "      <th>Cars sold</th>\n",
       "      <th>Cumulative cars sold (modeled estimate)</th>\n",
       "      <th>ASP (not in millions)</th>\n",
       "      <th>Revenue (EV business only, ex credits)</th>\n",
       "      <th>Part and labor and other cost per vehicle (not in millions)</th>\n",
       "      <th>Capital consumed per vehicle</th>\n",
       "      <th>Total COGs per vehicle</th>\n",
       "      <th>Gross Margin (ex credits)</th>\n",
       "      <th>...</th>\n",
       "      <th>Interest paid</th>\n",
       "      <th>Debt to net PP&amp;E</th>\n",
       "      <th>Cash generation</th>\n",
       "      <th>Total Gross Margin</th>\n",
       "      <th>Total EBITDA Margin</th>\n",
       "      <th>Enterprise Value</th>\n",
       "      <th>Market Cap</th>\n",
       "      <th>Shares Outstanding</th>\n",
       "      <th>Stock Price</th>\n",
       "      <th>Cash flow yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>1.089766e+07</td>\n",
       "      <td>1.065236e+07</td>\n",
       "      <td>2.372273e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>3.846353e+11</td>\n",
       "      <td>21798.491790</td>\n",
       "      <td>1400.063679</td>\n",
       "      <td>23198.555470</td>\n",
       "      <td>0.357523</td>\n",
       "      <td>...</td>\n",
       "      <td>1.059599e+10</td>\n",
       "      <td>1.150668</td>\n",
       "      <td>2.696213e+11</td>\n",
       "      <td>0.596015</td>\n",
       "      <td>0.428340</td>\n",
       "      <td>6.273304e+12</td>\n",
       "      <td>6.640307e+12</td>\n",
       "      <td>9.636497e+08</td>\n",
       "      <td>6890.788914</td>\n",
       "      <td>0.040604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>1.039270e+07</td>\n",
       "      <td>9.824895e+06</td>\n",
       "      <td>2.438288e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>3.547573e+11</td>\n",
       "      <td>21568.029282</td>\n",
       "      <td>734.566243</td>\n",
       "      <td>25078.505101</td>\n",
       "      <td>0.305458</td>\n",
       "      <td>...</td>\n",
       "      <td>4.335748e+09</td>\n",
       "      <td>1.097997</td>\n",
       "      <td>2.299374e+11</td>\n",
       "      <td>0.548370</td>\n",
       "      <td>0.407798</td>\n",
       "      <td>5.058730e+12</td>\n",
       "      <td>5.429443e+12</td>\n",
       "      <td>9.633191e+08</td>\n",
       "      <td>5636.183741</td>\n",
       "      <td>0.042350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>9.075389e+06</td>\n",
       "      <td>8.771742e+06</td>\n",
       "      <td>1.997324e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>3.167301e+11</td>\n",
       "      <td>20163.576840</td>\n",
       "      <td>1872.744536</td>\n",
       "      <td>22036.321376</td>\n",
       "      <td>0.389711</td>\n",
       "      <td>...</td>\n",
       "      <td>9.112228e+09</td>\n",
       "      <td>1.158204</td>\n",
       "      <td>1.649688e+11</td>\n",
       "      <td>0.572519</td>\n",
       "      <td>0.375197</td>\n",
       "      <td>3.556635e+12</td>\n",
       "      <td>3.714701e+12</td>\n",
       "      <td>9.627084e+08</td>\n",
       "      <td>3858.594470</td>\n",
       "      <td>0.044410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>1.221666e+07</td>\n",
       "      <td>1.187439e+07</td>\n",
       "      <td>2.500438e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>4.287603e+11</td>\n",
       "      <td>18797.598189</td>\n",
       "      <td>1883.715279</td>\n",
       "      <td>20681.313468</td>\n",
       "      <td>0.427237</td>\n",
       "      <td>...</td>\n",
       "      <td>1.258931e+10</td>\n",
       "      <td>1.162888</td>\n",
       "      <td>1.364169e+11</td>\n",
       "      <td>0.426843</td>\n",
       "      <td>0.346661</td>\n",
       "      <td>2.229113e+12</td>\n",
       "      <td>2.212538e+12</td>\n",
       "      <td>9.637213e+08</td>\n",
       "      <td>2295.827741</td>\n",
       "      <td>0.061656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>9.309015e+06</td>\n",
       "      <td>9.001416e+06</td>\n",
       "      <td>2.170446e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>3.250231e+11</td>\n",
       "      <td>17900.247373</td>\n",
       "      <td>1056.238910</td>\n",
       "      <td>18956.486282</td>\n",
       "      <td>0.475006</td>\n",
       "      <td>...</td>\n",
       "      <td>7.561056e+09</td>\n",
       "      <td>1.125470</td>\n",
       "      <td>1.579421e+11</td>\n",
       "      <td>0.585575</td>\n",
       "      <td>0.381076</td>\n",
       "      <td>2.944968e+12</td>\n",
       "      <td>3.228993e+12</td>\n",
       "      <td>9.631560e+08</td>\n",
       "      <td>3352.513368</td>\n",
       "      <td>0.048914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>1.575972e+07</td>\n",
       "      <td>1.560824e+07</td>\n",
       "      <td>3.072903e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>5.635823e+11</td>\n",
       "      <td>16013.787968</td>\n",
       "      <td>2038.957945</td>\n",
       "      <td>19450.508231</td>\n",
       "      <td>0.461324</td>\n",
       "      <td>...</td>\n",
       "      <td>1.717767e+10</td>\n",
       "      <td>1.165487</td>\n",
       "      <td>2.258998e+11</td>\n",
       "      <td>0.458748</td>\n",
       "      <td>0.411561</td>\n",
       "      <td>4.182874e+12</td>\n",
       "      <td>4.122558e+12</td>\n",
       "      <td>9.629847e+08</td>\n",
       "      <td>4281.021610</td>\n",
       "      <td>0.054796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>1.376146e+07</td>\n",
       "      <td>1.358367e+07</td>\n",
       "      <td>2.744105e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>4.904793e+11</td>\n",
       "      <td>16209.945927</td>\n",
       "      <td>2179.998756</td>\n",
       "      <td>18389.944684</td>\n",
       "      <td>0.490696</td>\n",
       "      <td>...</td>\n",
       "      <td>8.676730e+09</td>\n",
       "      <td>1.166778</td>\n",
       "      <td>1.977682e+11</td>\n",
       "      <td>0.483054</td>\n",
       "      <td>0.403407</td>\n",
       "      <td>3.199587e+12</td>\n",
       "      <td>3.122864e+12</td>\n",
       "      <td>9.638211e+08</td>\n",
       "      <td>3240.086206</td>\n",
       "      <td>0.063329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>7.135337e+06</td>\n",
       "      <td>6.893776e+06</td>\n",
       "      <td>1.670395e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>2.489205e+11</td>\n",
       "      <td>19096.086030</td>\n",
       "      <td>2020.780946</td>\n",
       "      <td>22535.883093</td>\n",
       "      <td>0.375876</td>\n",
       "      <td>...</td>\n",
       "      <td>8.695094e+09</td>\n",
       "      <td>1.155394</td>\n",
       "      <td>1.495967e+11</td>\n",
       "      <td>0.577140</td>\n",
       "      <td>0.428447</td>\n",
       "      <td>3.444480e+12</td>\n",
       "      <td>3.564743e+12</td>\n",
       "      <td>9.656126e+08</td>\n",
       "      <td>3691.690805</td>\n",
       "      <td>0.041966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>5.627377e+06</td>\n",
       "      <td>5.468336e+06</td>\n",
       "      <td>1.460553e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>1.974507e+11</td>\n",
       "      <td>22665.203620</td>\n",
       "      <td>1612.750331</td>\n",
       "      <td>24277.953951</td>\n",
       "      <td>0.327630</td>\n",
       "      <td>...</td>\n",
       "      <td>4.037770e+09</td>\n",
       "      <td>1.127287</td>\n",
       "      <td>8.808066e+10</td>\n",
       "      <td>0.522718</td>\n",
       "      <td>0.318893</td>\n",
       "      <td>1.788597e+12</td>\n",
       "      <td>1.885773e+12</td>\n",
       "      <td>9.628629e+08</td>\n",
       "      <td>1958.506087</td>\n",
       "      <td>0.046708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>2025.0</td>\n",
       "      <td>2.117421e+07</td>\n",
       "      <td>2.039538e+07</td>\n",
       "      <td>3.672548e+07</td>\n",
       "      <td>36108.0</td>\n",
       "      <td>7.364364e+11</td>\n",
       "      <td>16749.825037</td>\n",
       "      <td>3456.345570</td>\n",
       "      <td>20206.170607</td>\n",
       "      <td>0.440396</td>\n",
       "      <td>...</td>\n",
       "      <td>3.290421e+10</td>\n",
       "      <td>1.166810</td>\n",
       "      <td>2.989921e+11</td>\n",
       "      <td>0.539414</td>\n",
       "      <td>0.400105</td>\n",
       "      <td>6.031970e+12</td>\n",
       "      <td>5.590887e+12</td>\n",
       "      <td>9.629017e+08</td>\n",
       "      <td>5806.290999</td>\n",
       "      <td>0.053478</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Electric Vehicles                \\\n",
       "        Year Cars Produceable (units, not in millions)     Cars sold   \n",
       "0     2025.0                              1.089766e+07  1.065236e+07   \n",
       "1     2025.0                              1.039270e+07  9.824895e+06   \n",
       "2     2025.0                              9.075389e+06  8.771742e+06   \n",
       "3     2025.0                              1.221666e+07  1.187439e+07   \n",
       "4     2025.0                              9.309015e+06  9.001416e+06   \n",
       "...      ...                                       ...           ...   \n",
       "4995  2025.0                              1.575972e+07  1.560824e+07   \n",
       "4996  2025.0                              1.376146e+07  1.358367e+07   \n",
       "4997  2025.0                              7.135337e+06  6.893776e+06   \n",
       "4998  2025.0                              5.627377e+06  5.468336e+06   \n",
       "4999  2025.0                              2.117421e+07  2.039538e+07   \n",
       "\n",
       "                                                                    \\\n",
       "     Cumulative cars sold (modeled estimate) ASP (not in millions)   \n",
       "0                               2.372273e+07               36108.0   \n",
       "1                               2.438288e+07               36108.0   \n",
       "2                               1.997324e+07               36108.0   \n",
       "3                               2.500438e+07               36108.0   \n",
       "4                               2.170446e+07               36108.0   \n",
       "...                                      ...                   ...   \n",
       "4995                            3.072903e+07               36108.0   \n",
       "4996                            2.744105e+07               36108.0   \n",
       "4997                            1.670395e+07               36108.0   \n",
       "4998                            1.460553e+07               36108.0   \n",
       "4999                            3.672548e+07               36108.0   \n",
       "\n",
       "                                             \\\n",
       "     Revenue (EV business only, ex credits)   \n",
       "0                              3.846353e+11   \n",
       "1                              3.547573e+11   \n",
       "2                              3.167301e+11   \n",
       "3                              4.287603e+11   \n",
       "4                              3.250231e+11   \n",
       "...                                     ...   \n",
       "4995                           5.635823e+11   \n",
       "4996                           4.904793e+11   \n",
       "4997                           2.489205e+11   \n",
       "4998                           1.974507e+11   \n",
       "4999                           7.364364e+11   \n",
       "\n",
       "                                                                  \\\n",
       "     Part and labor and other cost per vehicle (not in millions)   \n",
       "0                                          21798.491790            \n",
       "1                                          21568.029282            \n",
       "2                                          20163.576840            \n",
       "3                                          18797.598189            \n",
       "4                                          17900.247373            \n",
       "...                                                 ...            \n",
       "4995                                       16013.787968            \n",
       "4996                                       16209.945927            \n",
       "4997                                       19096.086030            \n",
       "4998                                       22665.203620            \n",
       "4999                                       16749.825037            \n",
       "\n",
       "                                                          \\\n",
       "     Capital consumed per vehicle Total COGs per vehicle   \n",
       "0                     1400.063679           23198.555470   \n",
       "1                      734.566243           25078.505101   \n",
       "2                     1872.744536           22036.321376   \n",
       "3                     1883.715279           20681.313468   \n",
       "4                     1056.238910           18956.486282   \n",
       "...                           ...                    ...   \n",
       "4995                  2038.957945           19450.508231   \n",
       "4996                  2179.998756           18389.944684   \n",
       "4997                  2020.780946           22535.883093   \n",
       "4998                  1612.750331           24277.953951   \n",
       "4999                  3456.345570           20206.170607   \n",
       "\n",
       "                                ... Tesla Consolidated                   \\\n",
       "     Gross Margin (ex credits)  ...      Interest paid Debt to net PP&E   \n",
       "0                     0.357523  ...       1.059599e+10         1.150668   \n",
       "1                     0.305458  ...       4.335748e+09         1.097997   \n",
       "2                     0.389711  ...       9.112228e+09         1.158204   \n",
       "3                     0.427237  ...       1.258931e+10         1.162888   \n",
       "4                     0.475006  ...       7.561056e+09         1.125470   \n",
       "...                        ...  ...                ...              ...   \n",
       "4995                  0.461324  ...       1.717767e+10         1.165487   \n",
       "4996                  0.490696  ...       8.676730e+09         1.166778   \n",
       "4997                  0.375876  ...       8.695094e+09         1.155394   \n",
       "4998                  0.327630  ...       4.037770e+09         1.127287   \n",
       "4999                  0.440396  ...       3.290421e+10         1.166810   \n",
       "\n",
       "                                                                              \\\n",
       "     Cash generation Total Gross Margin Total EBITDA Margin Enterprise Value   \n",
       "0       2.696213e+11           0.596015            0.428340     6.273304e+12   \n",
       "1       2.299374e+11           0.548370            0.407798     5.058730e+12   \n",
       "2       1.649688e+11           0.572519            0.375197     3.556635e+12   \n",
       "3       1.364169e+11           0.426843            0.346661     2.229113e+12   \n",
       "4       1.579421e+11           0.585575            0.381076     2.944968e+12   \n",
       "...              ...                ...                 ...              ...   \n",
       "4995    2.258998e+11           0.458748            0.411561     4.182874e+12   \n",
       "4996    1.977682e+11           0.483054            0.403407     3.199587e+12   \n",
       "4997    1.495967e+11           0.577140            0.428447     3.444480e+12   \n",
       "4998    8.808066e+10           0.522718            0.318893     1.788597e+12   \n",
       "4999    2.989921e+11           0.539414            0.400105     6.031970e+12   \n",
       "\n",
       "                                                                    \n",
       "        Market Cap Shares Outstanding  Stock Price Cash flow yield  \n",
       "0     6.640307e+12       9.636497e+08  6890.788914        0.040604  \n",
       "1     5.429443e+12       9.633191e+08  5636.183741        0.042350  \n",
       "2     3.714701e+12       9.627084e+08  3858.594470        0.044410  \n",
       "3     2.212538e+12       9.637213e+08  2295.827741        0.061656  \n",
       "4     3.228993e+12       9.631560e+08  3352.513368        0.048914  \n",
       "...            ...                ...          ...             ...  \n",
       "4995  4.122558e+12       9.629847e+08  4281.021610        0.054796  \n",
       "4996  3.122864e+12       9.638211e+08  3240.086206        0.063329  \n",
       "4997  3.564743e+12       9.656126e+08  3691.690805        0.041966  \n",
       "4998  1.885773e+12       9.628629e+08  1958.506087        0.046708  \n",
       "4999  5.590887e+12       9.629017e+08  5806.290999        0.053478  \n",
       "\n",
       "[5000 rows x 81 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mc = MonteCarlo()\n",
    "mc.simulate(5000)\n",
    "sim = mc.getResults()\n",
    "sim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tesla 2025 share price:\n",
      "Mean:  2976.05\n",
      "Bear:  1640.0\n",
      "Bull:  5173.72\n"
     ]
    }
   ],
   "source": [
    "mean = np.quantile(sim[(TeslaValuation.consolidatedCol, TeslaValuation.stockPriceCol)], 0.5)\n",
    "bear = np.quantile(sim[(TeslaValuation.consolidatedCol, TeslaValuation.stockPriceCol)], 0.25)\n",
    "bull = np.quantile(sim[(TeslaValuation.consolidatedCol, TeslaValuation.stockPriceCol)], 0.75)\n",
    "\n",
    "print(\"Tesla 2025 share price:\")\n",
    "print(\"Mean: \", round(mean, 2))\n",
    "print(\"Bear: \", round(bear, 2))\n",
    "print(\"Bull: \", round(bull, 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Nli9fjn379qF3797Nvi4AWLNmDdq0aYPo6GjExMQ02N+Seneu2BRFQffu3bFixYoG+87ni4i6fv75ZwBA586dG90/duxYHD9+HGvWrMGGDRswdepU9O7dG+vWrWs2IW7p39nZ6v6d1SaYZ//t1e1Cez4u9N4G4Ly+VCGi4MIxfkQUcLp3745BgwZh8+bNuPXWWxst07NnT2zcuLHeto0bN0KSpHotKc3R6/Vwu931ttUmMMePH0dqamq9n6Y+eALA1KlTkZmZiX//+9+N7i8qKgIAbNq0CePGjcMtt9yCfv36ITU1FYcOHWpxzLUiIyORkpLS4Dps2rQJHTt2PO8P2S193RqNBsOGDcPTTz+N7du3o02bNvjggw8aPeamTZvQr18/zJgxAwMGDEBaWlqTM0jW5Xa7cfPNN+Pjjz/Ghg0bcMkllzQoM2TIEKxZs6bettWrV6N9+/b1xrm9/vrrmD59Ot55550WJX0AsHPnToSFhZ2zJbMxtePK8vLyADRev3r27ImCggLs27fPs81ut2Pr1q3o2bMngJr34vvvv0dFRcU5z/fqq6/iT3/6E0aOHImdO3e2KMYOHTqgc+fOjSZ9LTFgwADYbLYmx7cNHDgQR44cQWRkZIN6dCFLFjidTsyfPx9dunRB3759mywXExODyZMn47XXXsMXX3yBjRs3eq5xY+/D+frhhx/qPd6yZYvn/a5tecvOzvbsz8vLa7DkREvi6NmzJ7Zs2eKZURUAfvrpJ5SUlHjqBxFRY9jiR0QBac2aNaiurm7yw+lDDz2E/v37Y8aMGfjzn/+MY8eO4e6778aUKVPOq5tTx44dkZubiy1btiAtLQ0mkwmpqam4+eabcdttt2Hu3LkYPHgwKioqsH37duTn52PmzJmNHmvSpEm44YYbcOONN2Lv3r246qqrkJycjKNHj+Ltt99GdHQ05s+fj65du+K9997DN998g+TkZLz77rv48ccfPZO/nI9HH30UDzzwANLS0jBixAisX78er7zyCpYsWXLex2rJ6/70009x5MgRDBs2DHFxcdi+fTtOnDjRZLLdtWtXLF26FJ9++il69eqFzz//HMuXLz9nHC6XC5MnT/ZMbBMbG+tp2TObzZ7unvfffz/S09Px+OOPY9q0adi6dSsWL16MBQsWeI61YMECPPTQQ1iyZAmGDx/uOY5er/fUrQULFqBdu3bo2bMnJEnCmjVr8Mwzz+DOO+9s0KpS1/DhwzF58mQMHDgQcXFxyMzMxGOPPYaoqCiMHDkSQE39+vjjj7F3714kJCQgIiICo0aNwm9+8xtcf/31WLJkCSwWC5555hlUV1fjr3/9K4CarouvvfYafv/73+Opp55CUlIS9u7dC41Gg/Hjx9eLY9GiRdDpdBg9ejS++uqrJrtgesuoUaMwdOhQXHfddZg/fz769OmD7Oxs7N+/H7feeiumTJmCBQsW4Oqrr8Zzzz2HLl264NSpU1i/fj26d++OCRMmNHlst9vteY9KSkqwc+dOLFiwAAcOHMCaNWua7Lr5+OOPY8CAAejZsydkWcb7778Ps9nsuRd07NgR33zzDQ4fPgyLxQKLxXLer3vp0qXo1q0bBg4ciGXLlmHLli14+eWXAdRMkjNkyBDMnTsX3bp1g8vlwuOPP16vm3ndOMaPHw+9Xt/oFwt33XUXFi5ciOnTp+Oxxx5DcXEx7rjjDlx++eUYOnToecdNRCFEnaGFRETn5+xJS8529mQOQtRfzsFqtYrbb7+90eUc6nrvvfdE3Vujw+EQkydPFtHR0fWWc3C5XOKFF14QXbt2FTqdTsTGxophw4aJ//znP82+lrffflsMGTJERERECJPJJHr27ClmzpwpsrOzhRBCFBcXiz/+8Y8iIiJCxMTEiDvuuEM88cQT9SaZaep6NLacw9y5c0WHDh2EVqsVHTt2vKjlHJp73Rs3bhQjR44UVqtVGAwGkZqaKp5//nnPhCZnT1ThcDjEn//8ZxEdHS0iIiLE5MmTxeLFi8W5/vdUO1FGYz91J8oQQojPP/9c9OnTR+j1etGuXTsxb968evsbm0IfQL0JV+bOnSu6dOkiwsLCRGRkpOjfv7/417/+5Vk6oCnPP/+8uPzyy0VcXJwwGAyibdu2YsqUKfUmbSksLBTjx48XkZGR51zOYdiwYQ0mSzl48KCYMGGCiIyMFGFhYaJPnz7iiy++EEI0/vfw6KOPCovFIrZs2dJovC2ZeAdnLdvQ1PbS0lJx1113icTERKHT6USHDh3E888/79lfUFAgbr/9dpGUlCR0Op1ISkoSEyZMEDt27Gjy3HWXv5AkSURGRop+/fqJhx56qEHMZ7/+p59+WvTs2VOEh4eLyMhIMWzYsHoTrRw+fFgMHTpUhIeHN1jO4ewJWc61nMPw4cOFwWAQ7du3F++++2695x08eFAMGzZMmEwmkZqaKj755JMGk7usWrVKdOvWTej1+hYv52CxWJpczqGub7/9VgAQR48ebfIaE1Fwk4Twwoq/RERERERE5Lc4xo+IiIiIiCjIMfEjIiIiIiIKckz8iIiIiIiIghwTPyIiIiIioiDHxI+IiIiIiCjIMfEjIiIiIiIKckG1gHt2drbaIcBqtaKgoEDtMM4pKTkZAJB98qTKkQSvuvWA1zs0BcK9gFof6wGxDhDAekC+qwNJSUlN7mOLHxERERERUZBj4kdERERERBTkmPgREREREREFOSZ+REREREREQY6JHxERERERUZBj4kdERERERBTkgmo5B2oZLivgW7zeRERERKQ2tvgREREREREFOSZ+REREREREQY6JXwiyjhsH67hxaocRMni9iYiIiEhtHOMXgvR79qgdQkjh9SYiIiIitbHFj4iIiIiIKMgx8SMiIiIiIgpy7OoZ5KrdEipdSr1tSaf/tdlFve0mrQyjpv42IiIiIiIKfEz8glylS8GagwX1tvU6/e/Z28d2tcKokXwUGRERERER+Qq7ehIREREREQU5tviFoN3jJqodQkipmDJF7RCIiIiIKMQx8QtBX987S+0QQkrJ3Llqh0BEREREIY5dPYmIiIiIiIIcE78QFH9oH+IP7VM7jJCh270but271Q6DiIiIiEIYu3qGoGn3XA8AmLdql7qBhIi48eMBANknT6ocCRERERGFKrb4ERERERERBTkmfkREREREREGOiR8REREREVGQY+JHREREREQU5Jj4ERERERERBTkmfkREREREREGOyzmEoPcWfaB2CCElf9UqtUMgIiIiohDHxC8E5aX1UDuEkOLs00ftEIiIiIgoxLGrJxERERERUZBj4heCrlj4NK5Y+LTaYYQMy8MPw/Lww2qHQUREREQhjIlfCOqzejn6rF6udhghI/z99xH+/vtqh0FEREREIYyJHxERERERUZBj4kdERERERBTkmPgREREREREFOSZ+REREREREQY6JHxERERERUZDjAu4h6FRqd7VDCCmO3r3VDoGIiIiIQhwTvxC0bPGHaocQUgpWr1Y7BCIiIiIKcezqSUREREREFOSY+BEREREREQU5Jn4h6IHxffHA+L5qhxEykpKTkZScrHYYRERERBTCmPgREREREREFOSZ+REREREREQY6zegaoareESpfSbDl380WIiIiIiCjIMfELUJUuBWsOFjRbbkSq1QfREBERERGRP2NXTyIiIiIioiDHxI+IiIiIiCjIsatnCPrq7ifUDiGkFL/wgtohEBEREVGIY+IXgvZcNUntEEJK5dSpaodARERERCGOiR95yJIMm735aUBNWhlGjfBBRERERERE5A1M/EJQ7y//C6Bhy1+VS8GGzOZnCh3b1QqjRmqV2IKRadkyAGz5IyIiIiL1MPELQVcufhYAu3z6StTMmQCY+BERERGRepj4hbB1R0oQrpNh0mkQYdBgqMLum0REREREwYiJX4g5Vmw/80AAeRUuVDkdEACq3dlIi9FDK7MbJxERERFRMGHiFyIUIbA7txIHCqo920Z3tnj2ZRZWY2dOObJLtRjaPgJ6DZd4JCIiIiIKFvx0HwKEEPj+eBkOFFQjNcbQYL8sSehiDcPNg9qgsNKF9UdKUeVsfnZPIiIiIiIKDD5t8VMUBY888ghiYmLwyCOPoLy8HAsWLEB+fj7i4uJw//33w2w2AwBWrFiB9evXQ5Zl3HTTTejbt68vQw0qJ0odOFnqxCWJJnSPC2uy3KCUSBwuKMd3v5Zh3ZESjE21QMeWPyIiIiKigOfTT/VffvklkpOTPY9XrlyJ3r17Y9GiRejduzdWrlwJAMjKysLmzZsxf/58PP7441i6dCkUhS1QF8Kt1HTxtBg16Go1Nls+0azH8A6RqHAo+Cm30gcREhERERFRa/NZ4ldYWIgdO3Zg9OjRnm0ZGRkYPnw4AGD48OHIyMjwbE9PT4dOp0N8fDwSExORmZnpq1CDyrfHilHuUHBJggmyVDNpy7xVuzBv1a4mnxMXrkOXWCMybXbkVTh9FGnwyj55EtknT6odBhERERGFMJ8lfm+//TamTp0KSTozY2RJSQmio6MBANHR0SgtLQUA2Gw2xMbGesrFxMTAZrP5KtSg4XQLfLG/EPHhWrSJ0J3Xc3snmhCuk5GRVQ4Xl3kgIiIiIgpoPhnjt337dlgsFnTq1Al79+5ttrwQLUs01q5di7Vr1wIA5syZA6vVelFxeoNWq/VJHBUFpTCZTOcssyOrBGUON0akxSM8vOGkLmfTaOR6xxzaWYPVB/Jx0ObEoHZRnu0GgwFWa+QFxx4KfFUPyH+xDhDAekCsA1SD9YD8oQ74JPE7ePAgtm3bhp07d8LhcKCqqgqLFi2CxWJBUVERoqOjUVRUhMjImmQiNjYWhYWFnufbbDbExMQ0OO6YMWMwZswYz+OCgoLWfzHNsFqtPonDbheorGx6DF6VU8HPOaUYkByBcNldr+zUuycDAJYt/rDec9xuU71yUTqgU7QBP+eUoU24jJgw7elzm/ziWvuzuvXAOm4cAKBg9Wo1QyIf89W9gPwb6wGxDhDAekC+qwNJSUlN7vNJV8/rr78er776KpYsWYL77rsPvXr1wj333IOBAwdi48aNAICNGzdi0KBBAICBAwdi8+bNcDqdyMvLQ05ODlJTU30RatDYm1cJtwL8vkfDbxYSMvcjIXN/i47Tt40JBq2EjJPlLW6Jpfr0e/ZAv2eP2mEQERERUQhTdQH3CRMmYMGCBVi/fj2sVitmzJgBAGjbti0GDx6MGTNmQJZl3HLLLZBlLivQUi5F4FixHR2iDYg367HvIo6l18jok2jC1qwKZJc5kRyp91qcRERERETkGz5P/Hr27ImePXsCACIiIjBr1qxGy02cOBETJ070ZWhBI6fMAZcCdIhqflxfS3SIMmBfXhV+PlWJpPOcJIaIiIiIiNTHZrQg9GuxA0athLhw7+T1siShR3wYiqrdyC7j8g5ERERERIGGiV+QcboFcsocaGsxeNbt84YOUQaY9TJ+PlXJsX5ERERERAGGiV+QOVnqgFsA7SzeHYtXt9VvV06FV49NREREREStS9XJXcj7jpfYYdLJsJqafmt3j7uwsZO1Y/1W7ivAqA5mSF5sUQxmFVOmqB0CEREREYU4Jn5BxOFWkFvuRJdY4zmTsq/vbXxCnebUtvptzarA1pPluDQl4kJDDSklc+eqHQIRERERhTh29QwiWSUOKAJoZ/HObJ6N6RBlQFy4Dp/sLWy1cxARERERkXcx8Qsiv5Y4YNbLiA7TnLNc/KF9iD90Yav7yZKEK9OicbCgGgcLqi7oGKFGt3s3dLt3qx0GEREREYUwJn5BotqlIK/ciXYWQ7Nj76bdcz2m3XP9BZ9rSHsLTDoZnx8ouuBjhJK48eMRN3682mEQERERUQhj4hckTpQ4IAC0i/LubJ6NCdPJGNPZgu+Pl6Kwkuv6ERERERH5OyZ+QSK71IEIvYwoo2/m67m6SzQUAXz5S7FPzkdERERERBeOiV8QUIRAfqUTCWadz86ZGKHHb1LMWJNZDLtL8dl5iYiIiIjo/DHxCwJFVS64FCDeh4kfAPy2WzTK7G5sPFbq0/MSEREREdH5YeIXBPIqXACA+HDfJn694k3oGG3A5weKIITw6bmJiIiIiKjlmPgFgbxyJyINGhi1vn07JUnCb7tG49cSO37KrfTpuYmIiIiIqOV8MxMItZra8X0do1q+aPt7iz7w2vmHdojEOzvz8eUvRejbJtxrxw0m+atWqR0CEREREYU4Jn4BznYB4/vy0np47fx6jYzRnS1Yud+GgkonrCbfdjcNBM4+fdQOgYiIiIhCHLt6Bri88prxfXE+Ht9X17i0KAgBfJVZrFoMRERERETUNCZ+AS6vwgnLeY7vu2Lh07hi4dNeiyHBrEf/pHB8lVkCl8JJXs5mefhhWB5+WO0wiIiIiCiEMfELYIoQKKh0nvcyDn1WL0ef1cu9Gsv4tGgUVbnwY1aZV48bDMLffx/h77+vdhhEREREFMKY+AUwW+Xp8X3h6g/V7J8UjvhwLVb/Uqx2KEREREREdBYmfgFMrfX7GqORJYxNjcbuU5XIKrGrHQ4REREREdXBxC+AnapwwmLUwODj9fuaMibVAq0MrD5UrHYoRERERERUh39kDHTeXIpAQYVTldY+WZJhs4sGP4qkwYDkCKw9UoKcCjdsdoFqt+Tz+IiIiIiIqD71B4fRBTlqq4ZbqDO+r8qlYENmQaP7wnUSqpwKlmZko3OMEWO7WmHUMPkjIiIiIlITE78A9UtBJYALG993KrW7t8PxiDNpYTFokGmrRucYY6udJ5A4evdWOwQiIiIiCnFM/ALUsaJqmPXyBY3vW7b4w1aIqIYkSUiNNWJ7dgUKK12tdp5AUrB6tdohEBEREVGI4xi/AHWsyI7oMP/M2ztE6aGVgUxbtdqhEBERERERmPgFpFK7GwWVTsT4aeKn08hoH2XA8WI7yh1utcMhIiIiIgp5TPwC0OHTLWkXmvg9ML4vHhjf14sRNZQaY4RbAN8fK2nV8wSCpORkJCUnqx0GEREREYUwJn4BKLOwCgAQHaZROZKmRYdpYTVp8c2RYihCqB0OEREREVFIY+IXgA7bqhFv1kGv8e+3LzXGiFPlTuzOrVQ7FCIiIiKikOafg8RCVLVbQqVLabbcL4XV6BwT5oOILk5bix4/52mw+lAR+rYJVzscIiIiIqKQxcTPj1S6FKw52PjC6LWqXQoKK10Y3skIoPkkUU0aWcLQDhasOWRDYaUTsabzX3OQiIiIiIgunn/3FaQGiqpq1sZrHxUYi6OP6GSBEMBXmcVqh0JEREREFLKY+AUY2+nEr12UQeVIWiberEf/pHB8lVkCl8JJXoiIiIiI1MCungHGVuVChF5GmO7CZ/T86u4nvBhR88alReG5jSexNasM6e0ifXpuf1D8wgtqh0BEREREIY6JX4CxVbkRZ7q4t23PVZO8FE3LDEgyI86kxapDxSGZ+FVOnap2CEREREQU4tjVM4BUOxVUOZULXrhdLRpZwti0KOzOrURWqV3tcIiIiIiIQg4TvwBSO74v5iJb/Hp/+V/0/vK/3gipxa7oHAWtDKw+VOzT8/oD07JlMC1bpnYYRERERBTCmPgFkNrEL9p4cYnflYufxZWLn/VGSC0WFabFZW0jsP5ICewtWKswmETNnImomTPVDoOIiIiIQhgTvwBSVOVCpEEDnUZSO5QLclVaNCocCr79tVTtUIiIiIiIQgoTvwBiq3IhOuzCZ/NUW4/4MLSz6LHql2K1QyEiIiIiCilM/AJElVNBlUsE3MQudUmShHFp0ci0VeNQYZXa4RARERERhQwmfgGiqHZ8X4AlfrIkw2YXnp9LkiNg0Ej49EBxve3V7sDsvkpEREREFAgCK4sIYSV2NwAgyhhYXT2rXAo2ZBbU25Zi0WPzryWIM8nQa2q+exjb1QpjgI5dJCIiIiLyd2zxCxAl1S6Eac8kSoEsNcYItwCOFnFNPyIiIiIiX2CLX4AoqXbD4qXWvnmrdnnlOBcqOkyLWJMWmYXV6BJrhCQFd0tf9smTaodARERERCEu8JuPQoAiBErs3kv8/EFqjBFlDgWnKlxqh0JEREREFPSY+AWAcocCRQTe+L5zaWfRQ6+RkFlYrXYoRERERERBj4lfACiprmkVsxi90zN36t2TMfXuyV451oXSyBI6RRtwstSBKqeiaiytzTpuHKzjxqkdBhERERGFMI7xCwAl1TUzekYavNPil5C53yvHuVidY4w4UFCNw7bgbvXT79mjdghEREREFOLY4hcASqrdMOtlaOXgmgQlwqBBG7MOmbZquBShdjhEREREREGLiV8ACLaJXerqYjWi2iWw9USp2qEQEREREQUtJn5+zq0IlNndsBiCs1duolmHSIMGaw4VQQi2+hERERERtQYmfn6u1O6GQHDN6FmXJEnoajXieLEdP+dVqh0OEREREVFQYuLn52ondgnWrp4A0D7KALNeg0/3F6kdChERERFRUArO/oNBpMTugizVTITiLbvHTfTasbxBK0sY1TkKn+0vxMlSB5Ij9WqH5FUVU6aoHQIRERERhTifJH4OhwOzZ8+Gy+WC2+3GZZddhmuvvRbl5eVYsGAB8vPzERcXh/vvvx9msxkAsGLFCqxfvx6yLOOmm25C3759fRGq3ympdiPCoIEseW9Gz6/vneW1Y3nLqM5R+PKgDZ8dsOH23ySqHY5Xlcydq3YIRERERBTifNLVU6fTYfbs2XjxxRcxd+5c7Nq1C7/88gtWrlyJ3r17Y9GiRejduzdWrlwJAMjKysLmzZsxf/58PP7441i6dCkUJbgX+W5KcbUbFi+29vkri1GLYR0isf5ICcrsbrXDISIiIiIKKj5J/CRJgtFoBAC43W643W5IkoSMjAwMHz4cADB8+HBkZGQAADIyMpCeng6dTof4+HgkJiYiMzPTF6H6FadbQaVT8fr4vvhD+xB/aJ9Xj+kNv+8WDbtbYM2hYrVD8Srd7t3Q7d6tdhhEREREFMJ8NsZPURTMnDkTubm5GDt2LNLS0lBSUoLo6GgAQHR0NEpLa9Zys9lsSEtL8zw3JiYGNputwTHXrl2LtWvXAgDmzJkDq9Xqg1dyblqt9oLjqCgohclk8jzOK7MDABIs4TCZwuqV1WjkemWb0li5afdcDwB4ZeMvXjvmxZY1GAwYmByHQe2K8eWhYtx0eRoM2sCde6huPdCPHw8AcNjtaoZEPnYx9wIKHqwHxDpAAOsB+Ucd8FniJ8syXnzxRVRUVOCll17C8ePHmyzb0vXcxowZgzFjxngeFxQUXHScF8tqtV5wHHa7QGXlmSUNTpVUAwCMkqvedgBwu00NtjXmXOVa45gXWtZuN6GgoAC/TYvArOPF+GTbEVyZGtWic/ijuvUg6fQ2f6if5DsXcy+g4MF6QKwDBLAekO/qQFJSUpP7fN6kEh4ejh49emDXrl2wWCwoKqqZwr+oqAiRkZEAgNjYWBQWFnqeY7PZEBMT4+tQVVdS7YZWBsJ1gdvydb76JJjQOcaIFfsK4Va4oDsRERERkTf4JKMoLS1FRUUFgJoZPvfs2YPk5GQMHDgQGzduBABs3LgRgwYNAgAMHDgQmzdvhtPpRF5eHnJycpCamuqLUP1KSbUbkQYtJC/O6OnvJEnCH3rEILvMiR+zytQOh4iIiIgoKPikq2dRURGWLFkCRVEghMDgwYMxYMAAdOnSBQsWLMD69ethtVoxY8YMAEDbtm0xePBgzJgxA7Is45ZbboEsh06rV60SuwttIoJrTbumyJIMm71m5tauCWbEm3X4z882dI03N0h8TVoZRg1bA4mIiIiIWsoniV/79u0xt5G1zCIiIjBrVuNryk2cOBETJ/rXQuO+ZHcpqHaJkFjKAQCqXAo2ZJ7p99wuUo9t2RV4b0cuEsy6emXHdrXCqAmdVlAiIiIioosVes1oAaL09Fp23l7KIVB0jDbAqJWwP79K7VCIiIiIiAKez2b1pPNTm/hFtEKL33uLPvD6Mb1NI0voEhuG3acqUVTlQnRY4FbV/FWr1A6BiIiIiEJc4H6aDnKldjc0UuvM6JmX1sPrx2wNqbEG7M+vwr68KgxpH6F2OBfM2aeP2iEQERERUYhjV08/VWZ3I8KgCakZPc+m18hIizXiRKkDJdUutcMhIiIiIgpYTPz8VKndjchWmtjlioVP44qFT7fKsb2tq9UIrQzsywvcsX6Whx+G5eGH1Q6DiIiIiEIYEz8/5FYEKhxKq4zvA4A+q5ejz+rlrXJsbzNoZaTGGHG8xIGy0+MeA034++8j/P331Q6DiIiIiEIYEz8/VOZwQwCt1uIXaLpZwyBLwD7O8ElEREREdEGY+Pmh2pYtJn41jDoZnWOMOFZkR7kjMFv9iIiIiIjUxMTPD7XmUg6BqlucEZIErutHRERERHQBmPj5oVK7GyadDK0cujN6ns2k06BTtAFHi+worHSqHQ4RERERUUBh4ueHWnNGz0DWPS4MAPD5gUKVIyEiIiIiCixcwN3PCCFQZncjLlrXauc4ldq91Y7dmsL1GnSONuDboyWY3CsWiRF6tUNqEUfv3mqHQEREREQhjomfn6lyKXAprTu+b9niD1vt2K2tR7wJx4od+OjnQtw7uI3a4bRIwerVaodARERERCGuxV09t2zZ0uj2H374wWvBEFBqVwBwRs+mhOlkjOochQ1HS5BValc7HCIiIiKigNDixO/VV19tdPtrr73mtWCISzm0xFVdY6DXSPhoN8f6ERERERG1RLNdPU+dOgUAUBQFeXl5EELU26fXB8Y4q0BRandDJ0swaltvRs8HxvcFAMxbtavVztGaIo1aXN0lGsv32TCpVyzaRxnUDumckpKTAQDZJ0+qHAkRERERhapmE7977rnH8/vdd99db19UVBT++Mc/ej+qEFZqdyPCoIEkcSmHc/m/HrFYdagYH+7OxyPDUtQOh4iIiIjIrzWb+H300UcAgNmzZ+Opp55q9YBCXandjYTw1pvRM1hEGDT4fbcYfLinAIcKq5AWG6Z2SEREREREfqvFY/yY9LW+KqeCKqfC8X0t9Lvu0Yg0aPDOzvx6XZCJiIiIiKi+Fi/nkJeXhw8//BDHjh1DdXV1vX2vvPKK1wMLRafKHQCASEOL8/GQZtJpcG2vWLyxPQ87cyrQP8msdkhERERERH6pxYnfwoULkZCQgBtuuAEGg39PphGocspqEr/WXMMv2IxLi8JnB4vw7q589G0TDpljI4mIiIiIGmhx4peVlYVnnnkGsszWqNaSU+qABMCsZ+LXUjqNjCl9rJi/OQebjpViREeL2iEREREREfmdFid+3bt3x7Fjx9CpU6fWjCek5ZTZYdbL0Mit22r11d1PtOrxfW1oh0is2G/D+z8VYEi7COg0/vXlRPELL6gdAhERERGFuBYnfnFxcXjuuefwm9/8BlFRUfX2XXfddd6OKyTllDl8MrHLnqsmtfo5fEmWJNzYLx5Prj+B1YeK8dtuMWqHVE/l1Klqh0BEREREIa7FiZ/dbseAAQPgdrtRWFjYmjGFJLcicKrcidQYjp+8EH0TTeiTaMJHPxdiZCcLu8sSEREREdXR4sTvjjvuaM04Ql5BpRMuRfhkYpfeX/4XQHC1/EmShJv6xWPGqmP4+OdC3NQ/Xu2QPEzLlgFgyx8RERERqafFid+pU6ea3JeQkOCVYEJZdpkTgG9m9Lxy8bMAgivxA4BOMUaM6mTB5wdtGJcWhTYRerVDAgBEzZwJgIkfEREREamnxYnfPffc0+S+jz76yCvBhLLs0tNLObCL4kWZcokV3x8vxTs78/DIsBS1wyEiIiIi8gstTvzOTu6Ki4vx8ccfo3v37l4PKhSdLHPAqJVh1HIduosRa9JhYo9YfLC7AD+fqkSvBJPaIRERERERqe6C572PiorC9OnT8cEHH3gznpCVXepAYoQOEhcgv2gTuscg1qTFmztOQRFC7XCIiIiIiFR3UQueZWdnw263eyuWkJZd5kCC2T/GpAU6g1bGDX3jcNhmx4ajpWqHQ0RERESkuhZ39Zw1a1a91ii73Y4TJ05g0qTgmiBEDU63grxyJy5rG6l2KAFBlmTY7Mo5y/RqE4HUmCK8uzMPl7U1w6Tj2EkiIiIiCl0tTvxGjRpV77HRaET79u3Rpk0brwcVanLKnRAAEiL0KK1yqB2O36tyKdiQWdBsuT9dEo9nvzmOj/b41/IORERERES+1uLEb8SIEa0YRmirndEz0eybxG/eql2tfg5/0Dk2DGM6W/DZARuu6GxBisWgShzZJ0+qcl4iIiIiolotTvxcLheWL1+OTZs2oaioCNHR0Rg2bBgmTpwIrbbFh6FG1CZ+CRE6/JKvcjBBZlrfOGw5XobXt53Ck6PacvIcIiIiIgpJLc7Yli1bhsOHD+O2225DXFwc8vPz8cknn6CyshLTp09vxRCD38kyB6KMGo5D8zJZkqEA+H0PKz74KQ9rj5ZhQHJEo2VNWhlGDWcAJSIiIqLg1OLE74cffsCLL76IiIiaD85JSUno2LEjHnroISZ+Fym71IGkCN/N6Dn17skAgGWLP/TZOdVQOxZQEQIWgwZvbstFbmk1tHLDVr+xXa0walqnNdA6bhwAoGD16lY5PhERERFRc1q8nIPgemitJrvMgaRI3yV+CZn7kZC532fnU5ssSeifFI5Kp4L9+VU+P79+zx7o9+zx+XmJiIiIiGq1uMVv8ODBeOGFFzBp0iRYrVYUFBTgk08+wWWXXdaa8QW9CocbxdVuJPuwxS8UJZh1aGfRY39+FdpHGRBpYLdaIiIiIgodLU78pk6dik8++QRLly5FUVERYmJiMGTIEPzhD39ozfiCXnZZzcQuvmzxC1X92oQjp8yJ7ScrMKJjBCd6ISIiIqKQ0Wzid+DAAWzbtg1Tp07Fddddh+uuu86zb9myZThy5Ai6dOnSqkEGs9oZPZn4tb4wnYw+iSZsz67A8RIH2keps7wDEREREZGvNTvGb8WKFejRo0ej+3r16oXly5d7PahQkl3mgASgjVmndighoXOMATFhGuzMqYDDragdDhERERGRTzSb+B07dgx9+/ZtdF/v3r1x9OhRb8cUUrJLnYg366DTtHieHboIsiRhYLIZdpfA7txKtcMhIiIiIvKJZrt6VlVVweVyQa9v2BXR7Xajqsr3syQGk5Nlvl3KAQB2j5vo0/P5m5gwLdJijfilsBodow2INbVua2vFlCmtenwiIiIiouY0m/glJyfjp59+wqBBgxrs++mnn5CcnNwqgYUCIQSySx3o1tni0/N+fe8sn57PH/VOCMOJEge2nqzA2NTWvf4lc+e26vGJiIiIiJrTbP/Cq6++Gv/617/w448/QlFqxkQpioIff/wRr7/+Oq6++upWDzJYFVe7UeVSuJSDCnQaGQOTw1FS7VZlbT8iIiIiIl9qtsXv8ssvR3FxMZYsWQKn04nIyEiUlpZCr9fjj3/8Iy6//HJfxBmU1JrRM/7QPgBAXlrjk/aEiuRIPdpa9NibV4WcMgdiDK0zy6du924AgLNPn1Y5PhERERFRc1q0jt8111yDUaNG4ZdffkF5eTnMZjO6dOkCk8nU2vEFtZO1a/hF+HZGz2n3XA8AmLdql0/P64/6twlHbpkT72zPxZwr20FuhbX94saPBwBknzzp9WMTEREREbVEixdwN5lMTc7uSRcmu9QBnSzB2sqTi1DTwnQy+rUxYevJCnydWYKxaVFqh0RERERE5HVcQ0BF2WUOtInQQSN7v5WJWq5jtAHd40x4e2ceCiudaodDREREROR1TPxUdLLU4fPxfdSQJEmYPiABbkXgHz/kQgihdkhERERERF7FxE8lbkUgt9z3a/hR4+LNetzYLx47cirw9eEStcMhIiIiIvIqJn4qyatwwqXUzCxJ/mF8lyj0TjDhze15yCtnl08iIiIiCh5M/FTiWcqBLX5+Q5Yk3H1ZIgSAxT/kQGGXTyIiIiIKEi2e1ZO8K7tMnTX8AOC9RR/4/JyBIsGsx8394/HPrblY9Usxru4afdHHzF+1yguRERERERFdOCZ+KjlZ6kC4TobFoPH5uUN94fbmXJlqwZYTZXhnZx76J4WjzUW2ynLhdiIiIiJSG7t6qiS7rGZGT6kVFgyniyNJEu66LBFaWcKiLezySURERESBzyctfgUFBViyZAmKi4shSRLGjBmDq666CuXl5ViwYAHy8/MRFxeH+++/H2azGQCwYsUKrF+/HrIs46abbgq6xeOzSx3oEW9S5dxXLHwaAPD1vbNUOX8gsJp0uHVgAhZuycFnB4rw++4xF3wsy8MPAwBK5s71VnhEREREROfFJy1+Go0G06ZNw4IFC/Dcc89hzZo1yMrKwsqVK9G7d28sWrQIvXv3xsqVKwEAWVlZ2Lx5M+bPn4/HH38cS5cuhaIovgjVJ+wuBfmVLtXW8Ouzejn6rF6uyrkDyciOkRiUbMayn/KRVWq/4OOEv/8+wt9/34uRERERERGdH58kftHR0ejUqRMAICwsDMnJybDZbMjIyMDw4cMBAMOHD0dGRgYAICMjA+np6dDpdIiPj0diYiIyMzN9EapP5JRxRs9AIEkS7rw0EQaNhIWbc+BW2OWTiIiIiAKTzyd3ycvLw9GjR5GamoqSkhJER9fMmhgdHY3S0lIAgM1mQ1pamuc5MTExsNlsDY61du1arF27FgAwZ84cWK1WH7yCc9Nqtc3GsaeoAADQs108rFazZ3tFQSlMppZ1/9Ro5BaVPVe5s7d745itEacvjmkwGGC1RjbYbgXwwCgNnlx9EF/9Wo1pg9q26HiN1QN/qJ/kOy25F1DwYz0g1gECWA/IP+qATxO/6upqzJs3D9OnTz/nB3LRwsk0xowZgzFjxngeFxQUXHSMF8tqtdaLo9otodJVv5vqzuOFNfsqK/DLySrPdrcCVFZWtug8brepRWXPVe7s7d44ZmvE6YtjOh1m/HIyv9F97cIFBiab8fqWX5EQBvSIM8GoOXcdrVsPkk5v84f6Sb5z9r2AQhPrAbEOEMB6QL6rA0lJSU3u81ni53K5MG/ePAwdOhSXXnopAMBisaCoqAjR0dEoKipCZGRNi0tsbCwKCws9z7XZbIiJufDJNdRU6VKw5mD9N3nHyXIYtRI2Hanfijkild8EqaXKpWBDZtN/jG0jddibJ2P+tycw96rOSAr3/TIcREREREQXyidj/IQQePXVV5GcnIxrrrnGs33gwIHYuHEjAGDjxo0YNGiQZ/vmzZvhdDqRl5eHnJwcpKam+iJUnyizuxGhwvp9dOEMWhmDU8wocyh4f+cptcMhIiIiIjovPmnxO3jwIDZt2oR27drhoYceAgBMnjwZEyZMwIIFC7B+/XpYrVbMmDEDANC2bVsMHjwYM2bMgCzLuOWWWyDLwbPkYJndjWSVZvQEgFOp3VU7dyCLN+vQIy4M3/1aiktTzBjWoeGYwMY4evdu5ciIiIiIiM7NJ4lft27d8J///KfRfbNmNb6W3MSJEzFx4sTWDEsVdpcCu1sgUsUWv2WLP1Tt3IGuV0IY7G6BV7bmoqvViARz8wl8werVPoiMiIiIiKhpwdOMFiDKHW4AYFfPACVLEm6/tGbQ7LzvucQDEREREQUGJn4+VmqvmeGTiV/gsobr8NffJOJgQRX+vYczdBERERGR/2Pi52NldjckAOE69S79A+P74oHxfVU7fzAY1iESozpZ8N+9hdh76txLRiQlJyMpOdlHkRERERERNcTEz8fKHG6E62VoZEntUOgi/XlgAhLNOszbnI0yu1vtcIiIiIiImsTEz8e4lEPwCNPJeGBIMkqqXVjyYw6E4Hg/IiIiIvJPTPx8SAhRk/jpmfgFi9RYI6ZeEoctJ8qx+lCx2uEQERERETXKJ8s5UI0qlwK34MQugU6WZNhOT9IDAEM7RWN7diXe2J6HhEgjOkQbUVFQCo1bglHDVkAiIiIiUh8TPx8q44yeQaHKpWBDZv3ZPFNj9Mi0VeGlTScwNs2CqAgzhrY1wajhWE4iIiIiUh+7evpQ7QQgEXpe9mBj0MoY0s6MSqeCH7PKOd6PiIiIiPwKW/x8qMzuhkYCTCou5QAAX939hKrnD1ZWkw5925iwM6cSP+eWYVi7cABA8QsvqBwZEREREYU6Jn4+VOqomdFTktTt/rfnqkmqnj+YdYk1Ir/ChW3HS3CwYyQGp4SjcupUtcMiIiIiohDHPoc+VGp3I5Lj+4KaJEm4NCUcEUYt/vlDNgornWqHRERERETExM9X3IpAhUPxi4lden/5X/T+8r9qhxG0dBoZo9OscLgVzNl0EoZ334Np2TK1wyIiIiKiEMaunj5S5qiZ2MUfWvyuXPwsAHb5bE3RJh1uGdgGS37IRuyjjwAAu3wSERERkWrY4ucjpXb/SfzINwamROAPPWLUDoOIiIiIiImfr5RWn17KgYlfSJlySZzn9wP5VSpGQkREREShjImfj5TZ3TDpZGhlLugdSjR13u/nN2Uhv4KTvRARERGR7zHx8xHO6El2l8DfN2ah2qWoHQoRERERhRgmfj4ghGDiR3jw8iQcLbJj0ZYcCCHUDoeIiIiIQggTPx+odCpwC07sEmpkSYbNfibB62QNxx97x+H742V4a1cBbHbh+al2swswEREREbUeLufgA7UzevrLxC7zVu1SO4SQUOVSsCGzAGtqr/fBAkhCoEOUAZ/uK0RemR3towwAgLFdrTBqmPwRERERUetgi58PlHEpBzpNkiQMSg5HnEmLH7PKOdkLEREREfkEEz8fKLW7oZMlGLVs0aGamT4vbx+BcJ2Mb38t83wxQERERETUWpj4+UDtxC6S5B+J39S7J2Pq3ZPVDiNkNHa9DVoZwzpEQgKw6Vgpypn8EREREVErYuLnA6V2t9+M7wOAhMz9SMjcr3YYIaOp6x1h0GBo+whUOBUs2nwSdi7zQERERESthIlfK6t0ulHtEhzfR42yhutwWVszMgurMO/7bLgVLvNARERERN7HxK+V5ZY5AHBiF2paO4sB1/eNx49Z5Xg1I5dr/BERERGR13E5h1aWw8SPWmBMajTsTjf+u7cQUUYtplwSp3ZIRERERBREmPi1spxSByQAZgMbV6lpsiTjqm6xOFXhwn9+LoReq8Ho1OgG5UxaGUYNWwSJiIiI6Pww8WtlOWUORBg0kP1kRk/yTzWLvReijVmD5Agdlu3Kw6GCSnSMNtQrx4XeiYiIiOhCMPFrZbllDkT4WWvf7nET1Q4hpJzP9ZYlCentIrDxWCm2ZpVDKwNtLYbmn0hEREREdA5M/FqRSxE4Ve5AF6tR7VDq+freWWqHEFLO93prZAlD20diw7FSbDlRDq0soU2EvpWiIyIiIqJQ4F9NUUHmVLkTbsGJXej86TQShneIQKRBg+9+LcOpcqfaIRERERFRAGPi14qySu0A/C/xiz+0D/GH9qkdRsi40Out18gY0TES4XoNNh0rZfJHRERERBeMiV8rUhQgMUKPCD9L/Kbdcz2m3XO92mGEjIu53katjFF1kr99pyq8HB0RERERhQImfq1ocLsIPD+2I/QaXma6cEadjFGdImHWa/Dy9yexK4fJHxERERGdH2YkRAHAqJUxslMkEiP0eHZDFnZkl6sdEhEREREFECZ+RAHCqJXx0LAUpFj0+PvGk0z+iIiIiKjFmPgRBZAIgxbPjG6HthY9ntt4EttOMvkjIiIiouYx8SMKMBEGDZ4e3Q7towx4flMWtmaVqR0SEREREfk5Jn5EASjCoMHTo9qiY7QRL3x7Et//Wqp2SERERETkx7RqB0C+996iD9QOIaS01vU2GzR4alRbPLshCy99n41Kp4IrUqNa5VxEREREFNiY+IWgvLQeaocQUlrzeofrNXhyVFvM2XQS//gxFxVONyZ0j2218xERERFRYGJXT6IAZ9DKeGx4Coa0i8BbO/Lx/k/5EEKoHRYRERER+RG2+IWgKxY+DQD4+t5ZKkcSGnxxvXUaCQ8MSUKYLhf/+bkQFQ43bh2YAFmSWu2cRERERBQ42OIXgvqsXo4+q5erHUbI8NX11sgS7ro0ERO6x+CLX4qxcHMO3Apb/oiIiIiILX5EQUWSJEzvF4dwvYz3fypAlUvBg5cnQa/hdzxEREREoYyJH1GQkSQJ1/ayQq/R4K0dpzBrXRbuTk9GmK7x5M+klWHUsGWQiIiIKJgx8SMKUsM6RWFfXgW2ZpXjb18dxbAOETBoGyZ/Y7taYdRwLCARERFRMGPiRxRAZEmGza60qKxbATpGG6DTSNh8vAzrj5RiRMfIJlv+iIiIiCh4MfEjCiBVLgUbMgtaVHZEqhUAkBKpx7AOkfju11KsPVKCkR0jYdZrWjNMIiIiIvIz/Oo/BJ1K7Y5Tqd3VDiNk+MP1TjTrMLJjJJxugbWHS1Bc7VI1HiIiIiLyLbb4haBliz9UO4SQ4i/XO9akw+hOkdhwtBTrDpdieIcIWMN1aodFRERERD7AFj+iEGIxajG6swUGrYRvjpYiu8yhdkhERERE5ANM/IhCjFmvwZhOFkQaNPj2WBl+OF6qdkhERERE1MqY+IWgB8b3xQPj+6odRsjwx+tt1MkY2SkS1nAt/rU1B18cLFI7JCIiIiJqRRzjRxSi9BoZIzpEIrPIgX9tO4VSuwt/6m2FJHFNPyIiIqJg45PE75///Cd27NgBi8WCefPmAQDKy8uxYMEC5OfnIy4uDvfffz/MZjMAYMWKFVi/fj1kWcZNN92Evn37+iJMopCjkSXcPTgFb27Pxr/3FCKv0o0pfeMhN5H8mbQyjBrh4yiJiIiI6GL5JPEbMWIExo0bhyVLlni2rVy5Er1798aECROwcuVKrFy5ElOnTkVWVhY2b96M+fPno6ioCM888wwWLlwIWWavVKLW4FAEks1adLMasf5wMX7Jr8Rlbc3Qyg2Tv7FdrTBq2CJIREREFGh8kk316NHD05pXKyMjA8OHDwcADB8+HBkZGZ7t6enp0Ol0iI+PR2JiIjIzM30RJlHIkiQJfduEo18bE7JKHdhwtBR2l6J2WERERETkJaqN8SspKUF0dDQAIDo6GqWlNTML2mw2pKWlecrFxMTAZrM1eoy1a9di7dq1AIA5c+bAarW2ctTN02q19eKoKCiFyWRq0XM1GtnrZc9V7uzt3jhma8TpT8dsaVlZlhuUO9dz/OU69WtnQlR4GDYeLsT6o2W4slscIgxnbhMGgwFWa2SLzh/qzr4XUGhiPSDWAQJYD8g/6oDfTe4iRMvHD40ZMwZjxozxPC4oKGiNkM6L1WqtF4fdLlBZWdmi57rdJq+XPVe5s7d745itEac/HbOlZU0mE9xupV65cz3Hn65TQhgwomMkvj1Whs9+zsXQ9hGINdUs9G63m/zi7ywQnH0voNDEekCsAwSwHpDv6kBSUlKT+1RL/CwWC4qKihAdHY2ioiJERta0IsTGxqKwsNBTzmazISYmRq0wg9JXdz+hdgghJRCvd3y4DmM6R2LTsTKsO1KKS1PMaB9lUDssIiIiIrpAqs2YMnDgQGzcuBEAsHHjRgwaNMizffPmzXA6ncjLy0NOTg5SU1PVCjMo7blqEvZcNUntMEJGoF5vi1GLK1MtiA3TYsuJcuzOrYRyHi3yREREROQ/fNLi9/LLL2Pfvn0oKyvD7bffjmuvvRYTJkzAggULsH79elitVsyYMQMA0LZtWwwePBgzZsyALMu45ZZbOKMnkUoMWhkjOkZiW3YF9uVXYcmWbDx0eRuYdBq1QyMiIiKi8+CTxO++++5rdPusWbMa3T5x4kRMnDixFSMKbb2//C8ABGQrVCAK9OutkSX8JjkcUUYNduWU44FVxzBzaDI6RBvVDo2IiIiIWohNaSHoysXP4srFz6odRsgIhustSRK6WsPw8LC2qHIqeGjNr/jmSInaYRERERFRCzHxI6IW6xpnwoKrOqJLrBEvb8nB4h9yUOXken9ERERE/o6JHxGdl+gwLZ4e3Q6TesZi3eES3L/qKA4WVKkdFhERERGdAxM/IjpvGlnCtL5xeG5MO7gVgUe++hUf7s6HS+Gsn0RERET+iIkfEV2wngkmvHxVRwzrEIl/7ynEQ6uP4YitWu2wiIiIiOgsTPyI6KKE6zW4Pz0JM4cmoajKhQdWH8M7O/Ngd3HsHxEREZG/8MlyDkQU/NLbRaJPQjje2pmH5fts2HKiDLcPSkTfNuFqh0ZEREQU8pj4haB5q3apHUJICaXrbTZocPdlbTC8QyT+uTUXs9efQHq7CNzcPx5x4Tq1wyMiIiIKWUz8iMjr+iSGY+64Tli+rxCf7y/EtpPl+F33WIztEgOtLNUra9LKMGo4KQwRERFRa2LiR0StwiUAgywwNs2CnTkV+O/PBfjqUBH6J4Uj0Xym9W9sVyuMGukcRyIiIiKii8XELwRNvXsyAGDZ4g9VjiQ0BNP1liUZNnvLJm1xny5m1mswtH0ksksd2JFTgQ1HS9HWoke/NiaYdJpWjJaIiIiIajHxC0EJmfvVDiGkBNP1rnIp2JBZ0KKyI1Kt9R4nReqRYNZhf34V9udXIafMgZ7xJoxOEwDY4kdERETUmricAxH5jEaW0CvBhPFdopAQrsNPuZWY/fUx7M6tUDs0IiIioqDGxI+IfM6s12Boh0gMbR8BpyLwt3Un8NJ3J1FY6VQ7NCIiIqKgxK6eRKSa5Eg9bhiQhM8PFOCLAzZknCzH73tYMSY1usHsnwBnACUiIiK6UEz8iEhVbgGEaYBxaRbsyK7AR7vzseqgDQOSwpFgrr/2H2cAJSIiIrow7OpJRH7BrNdg2Onun25F4Jujpdh8vAxVzpbNIkpERERETWOLXwjaPW6i2iGEFF7v85N81uyf2WUO9Io3oYvVqHZoRERERAGLiV8I+vreWWqHEFJ4vc+fVpbQO8GEDlEG7MipwK7cShwtsqNjbDjSU8LVDo+IiIgo4LCrJxH5rQiDBsPaR3hm/3xh4wnM/z4btiqX2qERERERBRS2+IWg+EP7AAB5aT1UjiQ08HpfHEmSPN0/HYqELw/asDWrHNdfYsXVXaKhaWT2TyIiIiKqj4lfCJp2z/UAgHmrdqkbSIjg9fYOrSzh6u5WXJVmwb8yTmHp9jysPVyCvwxKQM94k9rhEREREfk1dvUkooDSJkKPWSNT8OiwZFQ63Hjs6+NYsDkbRez+SURERNQktvgRUcCRJAmXtY1Avzbh+PjnQqzYf7r7Zx8rrmL3TyIiIqIG2OJHRAHLoJUxtW8cFl/dEV2tYXhjex5mrDqGvXmVaodGRERE5FeY+BFRwEuK1GP2yBQ8MiwZFae7f/59YxaySuxqh0ZERETkF9jVk4iCgiRJGNw2Av3bhOPTAzYs32vD3V8cxRWdo/CnPlbEhPF2R0RERKGLn4SIKKgYtDKu7WXFlalR+M+eAqw+VIxvjpZgfFoUJvaIRRQTQCIiIgpB/AQUgt5b9IHaIYQUXm/vkSUZNrvSbDmTVkaUUYs/D0rEb7vF4KM9BfjsYBFWHyrG+C7R+L8eMYgy8vZHREREoYOffEIQFxL3LV5v76lyKdiQWdBsufHd4lHpEgAAg16HGwa0wZVdYvG//YX4dL8NXxwswuUdIjG2Sww6Rhlh1IjWDp2IiIhIVUz8iCjoNJUgtrfoEN0lCgfyq7DxaAm+OVKCgclmTOoRg25xYZAkLgNBREREwYmJXwi6YuHTAICv752lciShgdfbv0QaNPhNihm9E0z4pbAKe/Mqse1kOTpFG3B112gMbR8Jg5YTHhMREVFw4aebENRn9XL0Wb1c7TBCBq+3fwrTybgkMRwvX5OGG/onwO4WWPxDLm5akYlFP+RiR24VCqsV2OwCNrtAtZutgURERBS42OJHRCFNAHA4Xbi8nRn5FS5k2qrxzZFirDtcDItBgw7RBnSIMmBCr3gYNUz+iIiIKDAx8SMiQs06gPFmHeLNOjjcCo6XOHC0yI6fciuxO7cSR4odGNvZgkvbmqHXsLMEERERBRYmfkREZ9FrZKTGGJEaY0Sp3Y1jRXZkldjx0vfZMGplDEwOr1ksPikcJp1G7XCJiIiImsXEj4joHCINGvRJNOGBLrHIKqrC98dL8WNWOb77tQw6WULfNuEY3NaMQSkRiDQwCSQiIiL/xMSPiKgFZKkmyevbJhy3DxI4UFCFLSfK8MPxMmScLIcs5aJXvAkDk83o1yYcsbFcG5CIiIj8BxO/EHQqtbvaIYQUXu/go5El9Iw3oWe8Cbf0j8dhmx0/nCjDD1lleHNHHgDAGn4SfRLC0K9NOPommhBp5O2WiIiI1MNPIiFo2eIP1Q4hpPB6BwdZkmGzK43uizEbcFV3A67qbkVhpROH8qtwqNiJrb/asP5ICSQAnWKM6JtoQo94E7pZw2Bmt1AiIiLyISZ+REQtUOVSsCGzoEVlx3a14ob0OJzKy8dhWzV25VRgZ04FVuy34ZN9NgBAO4se3eNM6BYXhh5xYUgw6yBJXC6CiIiIWgcTPyIiL5MlGb8WlMLuBKwRRoyJMGJMl1jYXQqO2KpxqLAKhwoqselYKdZkFgMAoo0adLGGoXOMEZ1jjOgUY0RM2JlbdLVbQqWr8RbHs5m0MowajjEkIiKiM5j4haAHxvcFAMxbtUvVOEIFr3foqXIp2Hi8CJWVlY3uN8hAr/gw9IgzoldiBLJLqrE/vwqHCqvxY1a5p1y0UYNOpxPB+AgDjhZWwqyXm20ZHNvVysXmiYiIqB4mfkREKpElCW2jjLgkIQzju0QDACqdbhwtsuOIrRpHiqpx2GbHzpxCKKcb8LQyEGnQIsqogcWogcVY87tRy0XliYiIqGlM/IiI/IhJp/HMGFrL7lKwJ78aqw8WoqTajeJqF06WOnCk6Ex3ToNWQpRBC4tRgzC9Dj3jDGhrMTAhJCIiIgBM/IiIVHWu2ULPkNA+qmb8X13VTgXFdtfpZNCNkmoXDtuc+KUw9/SzgLhwHVIshjM/kXrEm/XQyBLHAhIREYUQJn5ERCpq6WyhI1KtDbYZdTISdXokms9sE0KgZxsLvjqYfzoZdCOzsAo7s8tRm+LJEmAxaNA9IRxpMQZ0iKppHbSatJxZlIiIKEgx8SMiCiKSJCHerD/dwndmu1sRKLWfaRksrnZj36lKbP611FPGqJWREqlHikWPtpEGtLXUHCfRrINGZkJIREQUyJj4ERGFAI0sITpMi+gwLQADgJrZP3VQcLzYjhOldpwocSCrxI49pyqx4eiZhFArS0iM0KPN6Z+kyDO/6zT1xxCy+ygREZF/YuIXgr66+wm1QwgpvN7kzyIMGvRMMKFngqne9kqnG1klDmSVOnCixI4jRXbsz6vAtqwy1E3rzHoZkQaN5+fKLrHobjXArNf49oUQERHROTHxC0F7rpqkdgghhdebApFJV7OgfBdrGADAZhdYc7AAbkWgzO5Gqd2NktP/lla7kVvuhCKArScrAACRBg3aROiRWPtjrvk3LvxMt1G2DhIREfkOEz8iImoxjSwhKkyLqLD6//tQhEC5Q0G7aBO2/FqMUrsbhZVOHCuqht19JrmTJcCs1yDCIOOSNhHoFFWTDFpNWljDdVx+goiIqJUw8QtBvb/8LwC2RPkKrzf5q5YtJVHD3UwxWZIQadCgb1IEiivt9fbZXUpNK6HDjTK7G2V2BaV2N746VASXUr/FL0Ivwxqug9WkQ1y4FhajFma9DLNeA7Neg/A6v5v1MrSydMEzkVa7JVS6mn/9bJkkIqJgwMQvBF25+FkATER8hdeb/FVLl5IAGl9OoqUMWhkGbU1CV9eYtFgobhcKKl0oqHAi//S/BZVO5Fc4sT+/EuWO5hMznSxBpzn9I9f/VyNJ0Mg1P1qppsVSe/qxWwCnyhyQpZqWSEmSIAOQpJpEtub5QL/kSMSGyTBqZBh1MsK0MsJ0MiL0Gpj0MmQugUFERAGAiR8REalCI0uIC9MjwaxvsoxbEahwuFHmUFDucKPC4UZ5nd8dbgGnW8CpnPnX5RZwKgqcbgGXqDmGWxGoEgIupeaxSxFwKALldjeEEFAEoAhA4MzvtXbkVDYZnywB4XoNIvQyIgw1LZEReg3MBg0iDBokxjggOaoQadTCcnqbxaiBXsMurURE5FtM/IiISBUt7moqaWAx6RBmUBDXTFG9RoajuX6pp7kVYO2hxls8hRBwC8ClCKR3iIJRBqpdCqqcCuwuBRXOmuSzpuuq2/N7UZUbx0scKLe7UeVSADR+fINWgsWgReTpRDDCoIHFoEGkQYtIY80MqRaDBhFGDcJ1Ghi1MgxaSZXWRXaJJSIKDn6d+O3atQtvvfUWFEXB6NGjMWHCBLVDIiIiLznfrqYtKdvScrVlmyJJNV1DtbKEBLMRilAQ0YJj1k0mFSGg0RtRUlYJu7smYbS7BewugcRIAxyumhlRS6rdOFFiR6ndjWrXuRMno1aCUSt7fgxaGRqppntq3a6q0unXUBuHcrrls6Y1s/6/7rMeK0pN0lv3eQ638LSGCgEI1JxDPt19ViMBZoMWRq0EvUaCVpah19T8rtNI0Mtyzb+1jzVynd9rHutkCXrtmbIaGdCe7qqrrdNFVyujzu+nt0s12y90vCcRUSjw28RPURQsXboUTzzxBGJjY/Hoo49i4MCBSElJUTs0IiIKIRc6FlKWJITpNBBGDYD66xqO7xYPRTRsRXO4lTOtiHY3yhxuuN0CLsUNu0tBtUugyqmg2nXmRwhAQU0rpUMBXEJ4kjOImkRQI0s1Yxk9SVJNgqSRpDPjG0+PbdSc9VgCkFVSXS+hrE2v3EJ4EsWECAMkCDjdiqcLbolTgVMRcLhrut46Tv843QrcrdA4qKkzjlNbZ2ynVnPmdWtOX4Pa66Kpkzie/diolWE4PdZTq5EaSUTh+V2BDJcQnjK1+8IKXHC7nJ7nmXUyTNqasan1E1gmrkTUuvw28cvMzERiYiISEhIAAOnp6cjIyGDiR0REAe98ksmmksTGnKv7al3n2zLakrLnG+dXv+R7WhTdQsCt1CaSZ1ohB6RY4FIUuE6P06ztfuv2PBanH9cc1+5SPMdyeY4rPOM63afP51QECiocNUlz3TGep7v41o77lGXpdGJbMz60tWnlmmRcqzmTXDb+gwbbmtJYLilOJ92141prvygQdb40cNX9EqHuftQ+FvVaf08fuV6rcO11rHuu2mutnA6itnzN3tMx1/1vnfhrf62/rfbLi5rEX5bOJOU1X2TU/K6RpNNffJxppZZrk3TPNqleK3bdyaDqPZbOJPYaz5cBqPP7mRZr+fTjElSgrMTuOU/d5+Ni8/3aL3pQ+4WP8PwumigjhEBd4szTGqi93meuf82XP1KdjWceN7HP87uEs1/ymcdSI+eq34OhJerX0/r1FThTF2t/r702des46nyh5il31rEEgESzLqC+sPHbxM9msyE2NtbzODY2FocOHVIxIiIiIt/z1eyrF+t845RPf8g+V9KSajU1e0wNAI1cN0Ft/kNYS5PZsV2tiDHUHK82KaxNImt/apPMQruCb48UeRJIRQAKBHR6A6qq7Z7n906MgFNRTh/nzPHqHrc2YVUE4HCLeslubRm7W/E83y0EGpsuqLHP8crpD6y13YKB0y27nt9rPpwDQGm1q/4Hcan+h//a7fGnJ2iSpPof7Gvf2toW5FqnyuwA5EY/5Nd+OG8TaUROaXWjr6N+giKQZAk7fc3PXLe6XyK4xZnuyi6l6XJK3S8gan9XRKPX8fwd88pR6OxE8kz9ULzzRp2Xj//UBXpN4CR+kjg75fcTW7ZswU8//YTbb78dALBp0yZkZmbi5ptv9pRZu3Yt1q5dCwCYM2eOKnESERERERH5O7+dTzo2NhaFhYWex4WFhYiOjq5XZsyYMZgzZ45fJX2PPPKI2iGQH2A9INYBAlgPiHWAarAekD/UAb9N/Dp37oycnBzk5eXB5XJh8+bNGDhwoNphERERERERBRy/HeOn0Whw880347nnnoOiKBg5ciTatm2rdlhEREREREQBx28TPwDo378/+vfvr3YY52XMmDFqh0B+gPWAWAcIYD0g1gGqwXpA/lAH/HZyFyIiIiIiIvIOvx3jR0RERERERN7h1109A8muXbvw1ltvQVEUjB49GhMmTFA7JPKyO++8E0ajEbIsQ6PRYM6cOSgvL8eCBQuQn5+PuLg43H///TCbzQCAFStWYP369ZBlGTfddBP69u0LADhy5AiWLFkCh8OBfv364aabbgqoxT9DyT//+U/s2LEDFosF8+bNAwCvvudOpxP/+Mc/cOTIEUREROC+++5DfHy8Wi+XmtBYPfjPf/6DdevWITIyEgAwefJkz9AE1oPgU1BQgCVLlqC4uBiSJGHMmDG46qqreD8IMU3VA94PQofD4cDs2bPhcrngdrtx2WWX4dprrw2ce4Ggi+Z2u8Vdd90lcnNzhdPpFA8++KA4ceKE2mGRl91xxx2ipKSk3rb33ntPrFixQgghxIoVK8R7770nhBDixIkT4sEHHxQOh0OcOnVK3HXXXcLtdgshhHjkkUfEwYMHhaIo4rnnnhM7duzw6eugltu7d684fPiwmDFjhmebN9/z1atXi9dee00IIcR3330n5s+f78NXRy3VWD346KOPxKefftqgLOtBcLLZbOLw4cNCCCEqKyvFPffcI06cOMH7QYhpqh7wfhA6FEURVVVVQgghnE6nePTRR8XBgwcD5l7Arp5ekJmZicTERCQkJECr1SI9PR0ZGRlqh0U+kJGRgeHDhwMAhg8f7nnfMzIykJ6eDp1Oh/j4eCQmJiIzMxNFRUWoqqpCly5dIEkShg0bxrrix3r06OH5xq6WN9/zbdu2YcSIEQCAyy67DD///DMEh137ncbqQVNYD4JTdHQ0OnXqBAAICwtDcnIybDYb7wchpql60BTWg+AjSRKMRiMAwO12w+12Q5KkgLkXsKunF9hsNsTGxnoex8bG4tChQypGRK3lueeeAwBcccUVGDNmDEpKShAdHQ2g5n8IpaWlAGrqRFpamud5MTExsNls0Gg0DerKuf6nQf7Hm+953XuHRqOByWRCWVmZp7sQ+bc1a9Zg06ZN6NSpE2644QaYzWbWgxCQl5eHo0ePIjU1lfeDEFa3Hhw4cID3gxCiKApmzpyJ3NxcjB07FmlpaQFzL2Di5wWNZeEcsxV8nnnmGcTExKCkpATPPvsskpKSmizb1Dcz/NYueF3Ie857R+C68sorMWnSJADARx99hHfffRd33HEH60GQq66uxrx58zB9+nSYTKYmy7EeBLez6wHvB6FFlmW8+OKLqKiowEsvvYTjx483Wdbf6gC7enpBbGwsCgsLPY8LCws9WT8Fj5iYGACAxWLBoEGDkJmZCYvFgqKiIgBAUVGR59uYs+uEzWZDTExMo3Wl9rgUGLz5ntfd53a7UVlZ2eIuhaSuqKgoyLIMWZYxevRoHD58GADrQTBzuVyYN28ehg4diksvvRQA7wehqLF6wPtBaAoPD0ePHj2wa9eugLkXMPHzgs6dOyMnJwd5eXlwuVzYvHkzBg4cqHZY5EXV1dWoqqry/L579260a9cOAwcOxMaNGwEAGzduxKBBgwAAAwcOxObNm+F0OpGXl4ecnBykpqYiOjoaYWFh+OWXXyCEwKZNm1hXAow33/MBAwZgw4YNAIAffvgBPXv25De7AaL2f/AAsHXrVrRt2xYA60GwEkLg1VdfRXJyMq655hrPdt4PQktT9YD3g9BRWlqKiooKADUzfO7ZswfJyckBcy/gAu5esmPHDrzzzjtQFAUjR47ExIkT1Q6JvOjUqVN46aWXANR8+3L55Zdj4sSJKCsrw4IFC1BQUACr1YoZM2Z4vpVZvnw5vvnmG8iyjOnTp6Nfv34AgMOHD+Of//wnHA4H+vbti5tvvpk3dT/18ssvY9++fSgrK4PFYsG1116LQYMGee09dzgc+Mc//oGjR4/CbDbjvvvuQ0JCgpovmRrRWD3Yu3cvjh07BkmSEBcXhz//+c+enh6sB8HnwIEDmDVrFtq1a+e5X0+ePBlpaWm8H4SQpurB999/z/tBiPj111+xZMkSKIoCIQQGDx6MSZMmefXzYGvWASZ+REREREREQY5dPYmIiIiIiIIcEz8iIiIiIqIgx8SPiIiIiIgoyDHxIyIiIiIiCnJM/IiIiIiIiIIcEz8iIqLzdOedd2L37t1eP25BQQGmTZsGRVG8fmwiIgptWrUDICIi8pYDBw5g2bJlOHHiBGRZRkpKCm688UakpqZiw4YNWLduHZ555hmfxnTttdfCYDAAAEwmE9LT0zFt2jTIcsPvXq1WK9577z2fxkdERKGBiR8REQWFyspKzJkzB7feeivS09Phcrmwf/9+6HQ6tUPDiy++iMTERJw8eRJPPvkk2rRpgyuvvLJeGbfbDY1Go1KEREQU7Jj4ERFRUMjJyQEAXH755QAAvV6PSy65BACQlZWF119/HS6XC9OmTYNGo8Hbb7+NyspKvPnmm9i5cycMBgNGjx6N//u///O0xq1duxZffPEFCgsLERsbi7vvvhudOnWqd96TJ0/i73//O66//noMGTLknDEmJyeje/fuOHHiBPLy8nDXXXfh9ttvx8cff4z4+HjceeeduOuuu/Dhhx9Co9GgvLwc7777Ln766Sc4HA50794dDz/8MABg+/bt+Pe//438/HykpKTgtttuQ/v27b16TYmIKHgw8SMioqDQpk0byLKMf/zjHxgyZAjS0tJgNpsBwJMYnd3V880330RlZSX+8Y9/oKysDM899xyio6MxatQobNmyBR9//DEeeughdO7cGadOnWrQInfkyBG8+OKLuPXWWzFgwIBmY8zKysL+/fsxefJkz7Z9+/ZhwYIFkGUZxcXF9covXrwYRqMR8+bNg9FoxC+//OI57yuvvIKZM2eic+fO2LRpE+bOnYuXX37ZL1o4iYjI/zDxIyKioGAymfD000/j008/xWuvvYbi4mL069cPf/nLXxAVFdWgvKIo2Lx5M+bOnYuwsDCEhYXhmmuuwaZNmzBq1CisX78ev//975GamgoASExMrPf8AwcOYP369bjrrrvQq1evc8Y2c+ZMyLIMs9mM0aNHY8SIESgoKAAA/PGPf4TRaGzwnKKiIuzatQtLly71JLA9evQAAKxbtw5jxoxBWloaAGDEiBFYsWIFDh065ClDRERUFxM/IiIKGikpKbjzzjsB1HTBXLx4Md5++23cd999DcqWlpbC5XLBarV6tsXFxcFmswGomWEzISGhyXN9/fXX6N69e7NJHwC88MILDRLHWrGxsY1uLywshNls9iR9dRUUFGDjxo1YvXq1Z5vL5fLETkREdDYmfkREFJSSk5MxYsQIfP31143uj4yMhEajQUFBAVJSUgDUJFQxMTEAambYPHXqVJPHv+222/Dpp5/i7bffxvTp0y84TkmSGt0eGxuL8vJyVFRUIDw8vMG+iRMnYuLEiRd8XiIiCi1cx4+IiILCyZMn8dlnn6GwsBBATRL3/fffe7pDRkVFwWazweVyAQBkWcbgwYPx4YcfoqqqCvn5+fj8888xdOhQAMCoUaPw2Wef4ciRIxBCIDc3F/n5+Z7zGY1GPPbYY9i/fz/ef/99r7+e6Oho9O3bF2+88QbKy8vhcrmwb98+AMDo0aPx9ddf49ChQxBCoLq6Gjt27EBVVZXX4yAiouDAFj8iIgoKYWFhOHToED7//HNUVlbCZDJhwIABmDp1KgCgV69enkleZFnG0qVLcfPNN+PNN9/EXXfdBb1ej9GjR2PkyJEAgMGDB6OsrAwLFy6EzWZDfHw87rrrLsTFxXnOGR4ejr/97W946qmnoNFo8Kc//cmrr+nuu+/G22+/jfvvvx8ulws9e/ZEjx490LlzZ/zlL3/Bm2++iZycHOj1enTr1g3du3f36vmJiCh4SEIIoXYQRERERERE1HrY1ZOIiIiIiCjIMfEjIiIiIiIKckz8iIiIiIiIghwTPyIiIiIioiDHxI+IiIiIiCjIMfEjIiIiIiIKckz8iIiIiIiIghwTPyIiIiIioiDHxI+IiIiIiCjI/T89PYqC8NaM7AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "sns.histplot(sim[(TeslaValuation.consolidatedCol, TeslaValuation.stockPriceCol)], ax=ax, kde=True)\n",
    "ax.set_title(\"Monte Carlo Tesla 2025 Stock Price Distribution\")\n",
    "ax.set_xlabel(\"Stock Price\")\n",
    "ax.axvline(bear, color='r', linestyle='dashed', linewidth=2)\n",
    "ax.axvline(bull, color='r', linestyle='dashed', linewidth=2);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "sns.histplot(sim[(TeslaValuation.consolidatedCol, TeslaValuation.marketCapCol)], ax=ax, kde=True)\n",
    "ax.set_title(\"Monte Carlo Tesla 2025 Market Cap Distribution\")\n",
    "ax.set_xlabel(\"Market Cap\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,6))\n",
    "sns.histplot(sim[(TeslaValuation.consolidatedCol, TeslaValuation.enterpriseValueCol)], ax=ax, kde=True)\n",
    "ax.set_title(\"Monte Carlo Tesla 2025 Enterprise Value Distribution\")\n",
    "ax.set_xlabel(\"Enterprise Value\");"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}