布林 + ATR_實驗組.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "856d50e4-ee1c-4fac-a439-0db669d3eab1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import tejapi\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# set tej_key and base\n",
    "tej_key = 'your key'\n",
    "api_base = 'https://api.tej.com.tw'\n",
    "\n",
    "os.environ['TEJAPI_KEY'] = tej_key \n",
    "os.environ['TEJAPI_BASE'] = api_base\n",
    "\n",
    "# set date\n",
    "start = '2022-01-01'\n",
    "end = '2023-01-01'\n",
    "os.environ['mdate'] = start + ' ' + end\n",
    "os.environ['ticker'] = '2330'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3db27a31-fe4a-4fdf-8cdf-9985ebff6590",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Merging daily equity files:\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2024-01-12 05:34:56.677799] INFO: zipline.data.bundles.core: Ingesting tquant.\n"
     ]
    }
   ],
   "source": [
    "!zipline ingest -b tquant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d94e2f90-3645-446b-92a8-55d5bd66b7e5",
   "metadata": {},
   "outputs": [
    {
     "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></th>\n",
       "      <th>SMA_ATR</th>\n",
       "      <th>upper</th>\n",
       "      <th>middle</th>\n",
       "      <th>lower</th>\n",
       "      <th>curr_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>NaN</td>\n",
       "      <td>631.000000</td>\n",
       "      <td>631.000000</td>\n",
       "      <td>631.000000</td>\n",
       "      <td>631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>NaN</td>\n",
       "      <td>668.500000</td>\n",
       "      <td>643.500000</td>\n",
       "      <td>618.500000</td>\n",
       "      <td>656.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>NaN</td>\n",
       "      <td>666.979156</td>\n",
       "      <td>645.666667</td>\n",
       "      <td>624.354177</td>\n",
       "      <td>650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>NaN</td>\n",
       "      <td>663.763509</td>\n",
       "      <td>645.250000</td>\n",
       "      <td>626.736491</td>\n",
       "      <td>644.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>NaN</td>\n",
       "      <td>661.846750</td>\n",
       "      <td>643.000000</td>\n",
       "      <td>624.153250</td>\n",
       "      <td>634.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-26 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>10.015883</td>\n",
       "      <td>495.811271</td>\n",
       "      <td>474.605632</td>\n",
       "      <td>453.399993</td>\n",
       "      <td>455.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>9.415138</td>\n",
       "      <td>496.098595</td>\n",
       "      <td>473.543132</td>\n",
       "      <td>450.987670</td>\n",
       "      <td>456.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>9.338450</td>\n",
       "      <td>495.276002</td>\n",
       "      <td>472.182492</td>\n",
       "      <td>449.088982</td>\n",
       "      <td>457.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>8.975450</td>\n",
       "      <td>494.139699</td>\n",
       "      <td>470.372711</td>\n",
       "      <td>446.605723</td>\n",
       "      <td>451.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30 00:00:00+00:00</th>\n",
       "      <th>Equity(0 [2330])</th>\n",
       "      <td>8.978011</td>\n",
       "      <td>490.939646</td>\n",
       "      <td>467.890362</td>\n",
       "      <td>444.841077</td>\n",
       "      <td>446.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              SMA_ATR       upper      middle  \\\n",
       "2022-01-04 00:00:00+00:00 Equity(0 [2330])        NaN  631.000000  631.000000   \n",
       "2022-01-05 00:00:00+00:00 Equity(0 [2330])        NaN  668.500000  643.500000   \n",
       "2022-01-06 00:00:00+00:00 Equity(0 [2330])        NaN  666.979156  645.666667   \n",
       "2022-01-07 00:00:00+00:00 Equity(0 [2330])        NaN  663.763509  645.250000   \n",
       "2022-01-10 00:00:00+00:00 Equity(0 [2330])        NaN  661.846750  643.000000   \n",
       "...                                               ...         ...         ...   \n",
       "2022-12-26 00:00:00+00:00 Equity(0 [2330])  10.015883  495.811271  474.605632   \n",
       "2022-12-27 00:00:00+00:00 Equity(0 [2330])   9.415138  496.098595  473.543132   \n",
       "2022-12-28 00:00:00+00:00 Equity(0 [2330])   9.338450  495.276002  472.182492   \n",
       "2022-12-29 00:00:00+00:00 Equity(0 [2330])   8.975450  494.139699  470.372711   \n",
       "2022-12-30 00:00:00+00:00 Equity(0 [2330])   8.978011  490.939646  467.890362   \n",
       "\n",
       "                                                 lower  curr_price  \n",
       "2022-01-04 00:00:00+00:00 Equity(0 [2330])  631.000000       631.0  \n",
       "2022-01-05 00:00:00+00:00 Equity(0 [2330])  618.500000       656.0  \n",
       "2022-01-06 00:00:00+00:00 Equity(0 [2330])  624.354177       650.0  \n",
       "2022-01-07 00:00:00+00:00 Equity(0 [2330])  626.736491       644.0  \n",
       "2022-01-10 00:00:00+00:00 Equity(0 [2330])  624.153250       634.0  \n",
       "...                                                ...         ...  \n",
       "2022-12-26 00:00:00+00:00 Equity(0 [2330])  453.399993       455.0  \n",
       "2022-12-27 00:00:00+00:00 Equity(0 [2330])  450.987670       456.5  \n",
       "2022-12-28 00:00:00+00:00 Equity(0 [2330])  449.088982       457.0  \n",
       "2022-12-29 00:00:00+00:00 Equity(0 [2330])  446.605723       451.0  \n",
       "2022-12-30 00:00:00+00:00 Equity(0 [2330])  444.841077       446.0  \n",
       "\n",
       "[245 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from zipline.data import bundles\n",
    "from zipline.pipeline import Pipeline\n",
    "from zipline.TQresearch.tej_pipeline import run_pipeline\n",
    "from zipline.pipeline.data import EquityPricing, TWEquityPricing\n",
    "from zipline.pipeline.factors import BollingerBands, TrueRange, CustomFactor\n",
    "from zipline.utils.math_utils import nanmax\n",
    "from numpy import dstack\n",
    "\n",
    "start_time = pd.Timestamp(start, tz = 'UTC')\n",
    "end_time = pd.Timestamp(end,tz = 'UTC')\n",
    "bundle = bundles.load('tquant')\n",
    "\n",
    "class AverageTrueRange(CustomFactor):\n",
    "\n",
    "    inputs = (\n",
    "        EquityPricing.high,\n",
    "        EquityPricing.low,\n",
    "        EquityPricing.close,\n",
    "    )\n",
    "    \n",
    "    window_length = 20\n",
    "\n",
    "    outputs = [\"TR\", \"SMA_ATR\"]\n",
    "    \n",
    "    def compute(self, today, assets, out, highs, lows, closes):\n",
    "\n",
    "        high_to_low = highs[1:] - lows[1:]\n",
    "        high_to_prev_close = abs(highs[1:] - closes[:-1])\n",
    "        low_to_prev_close = abs(lows[1:] - closes[:-1])\n",
    "        tr_current = nanmax(\n",
    "            dstack(\n",
    "                (\n",
    "                    high_to_low,\n",
    "                    high_to_prev_close,\n",
    "                    low_to_prev_close,\n",
    "                )\n",
    "            ),\n",
    "            2,\n",
    "        )\n",
    "\n",
    "        sma_atr_values = np.mean(tr_current, axis=0)\n",
    "        \n",
    "        out.TR = tr_current[-1]\n",
    "        out.SMA_ATR = sma_atr_values\n",
    "\n",
    "def make_pipeline():\n",
    "    \n",
    "    ATR = AverageTrueRange(inputs = [TWEquityPricing.high,\n",
    "                                     TWEquityPricing.low,\n",
    "                                     TWEquityPricing.close])\n",
    "    TR = TrueRange(\n",
    "        inputs=[TWEquityPricing.high,\n",
    "                TWEquityPricing.low,\n",
    "                TWEquityPricing.close]\n",
    "    )\n",
    "    perf = BollingerBands(inputs=[EquityPricing.close], window_length=20, k=2)\n",
    "    upper,middle,lower = perf.upper, perf.middle, perf.lower\n",
    "    curr_price = EquityPricing.close.latest\n",
    "    \n",
    "    return Pipeline(\n",
    "        columns={\n",
    "            'SMA_ATR': ATR.SMA_ATR,\n",
    "            'upper': upper,\n",
    "            'middle': middle,\n",
    "            'lower': lower,\n",
    "            'curr_price': curr_price\n",
    "        },\n",
    "    )\n",
    "\n",
    "pipeline_result = run_pipeline(make_pipeline(), start_time, end_time)\n",
    "pipeline_result "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b1ab8f61-f024-4054-a3ba-a3014e0d1beb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from zipline.api import *\n",
    "from zipline.finance import commission, slippage\n",
    "\n",
    "def initialize(context):\n",
    "    set_slippage(slippage.VolumeShareSlippage())\n",
    "    set_commission(commission.PerShare(cost = 0.001425 + 0.003 / 2))\n",
    "    set_benchmark(symbol('2330'))\n",
    "    attach_pipeline(make_pipeline(), 'mystrategy')\n",
    "    context.last_buy_price = 0\n",
    "    context.stop_loss = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9213b9d2-9900-4cc0-954b-799ba7083ae0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def handle_data(context, data):\n",
    "    out_dir = pipeline_output('mystrategy')  # 取得每天 pipeline 的布林通道上中下軌 & ATR\n",
    "\n",
    "    for i in out_dir.index: \n",
    "        curr_price = out_dir.loc[i, 'curr_price']\n",
    "        upper = out_dir.loc[i, 'upper']\n",
    "        lower = out_dir.loc[i, 'lower']\n",
    "        atr = out_dir.loc[i, 'SMA_ATR']\n",
    "        \n",
    "        cash_position = context.portfolio.cash  # 記錄現金水位\n",
    "        stock_position = context.portfolio.positions[i].amount  # 記錄股票部位\n",
    "\n",
    "        loss_stopped, buy, sell = False, False, False\n",
    "        record(price = curr_price, upper = upper, lower = lower, stop_loss = context.stop_loss, buy = buy, sell = sell, loss_stopped = loss_stopped)\n",
    "\n",
    "        # 收盤價 > 止損價的狀況：\n",
    "        if (curr_price > context.stop_loss) or (context.last_buy_price == 0):\n",
    "            \n",
    "            # 若收盤價 <= 布林下軌，則買入或加碼\n",
    "            if (curr_price <= lower) and (cash_position >= curr_price * 1000):\n",
    "                order(i, 1000)\n",
    "                buy = True\n",
    "                record(buy = buy)\n",
    "                context.stop_loss = curr_price - (0.1 * atr)\n",
    "                \n",
    "            # 若收盤價 >= 布林上軌，則出清部位\n",
    "            elif (curr_price >= upper) and (stock_position >= 1000):\n",
    "                order_target(i, 0)\n",
    "                sell = True\n",
    "                record(sell = sell)\n",
    "            else:\n",
    "                pass\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "        # 若收盤價 <= 停損價，則出清部位\n",
    "        if (curr_price <= context.stop_loss) and (stock_position > 0):\n",
    "            order_target(i, 0)\n",
    "            sell = True\n",
    "            loss_stopped = True\n",
    "            record(sell = sell, loss_stopped = loss_stopped)\n",
    "        else:\n",
    "            pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7c9690e0-ca6e-4bf8-b821-1dfb80ad2f83",
   "metadata": {},
   "outputs": [],
   "source": [
    "def analyze(context, perf):\n",
    "    fig = plt.figure()\n",
    "    ax1 = fig.add_subplot(211)\n",
    "    perf.portfolio_value.plot(ax=ax1)\n",
    "    ax1.set_ylabel(\"Portfolio value (NTD)\")\n",
    "    ax2 = fig.add_subplot(212)\n",
    "    ax2.set_ylabel(\"Stock Price (NTD)\")\n",
    "    perf.price.plot(ax=ax2)\n",
    "    perf.upper.plot(ax=ax2)\n",
    "    perf.lower.plot(ax=ax2)\n",
    "    \n",
    "    buy_status, sell_status = perf.buy, perf.sell\n",
    "    buy_status.fillna(False, inplace=True)\n",
    "    sell_status.fillna(False, inplace=True)\n",
    "    \n",
    "    ax2.plot( # 繪製買入訊號\n",
    "        perf.index[perf.buy],\n",
    "        perf.loc[perf.buy, 'price'],\n",
    "        '^',\n",
    "        markersize=5,\n",
    "        color='red'\n",
    "    )\n",
    "    ax2.plot( # 繪製賣出訊號\n",
    "        perf.index[perf.sell],\n",
    "        perf.loc[perf.sell, 'price'],\n",
    "        'v',\n",
    "        markersize=5,\n",
    "        color='green'\n",
    "    )\n",
    "    \n",
    "    plt.legend(loc=0)\n",
    "    plt.gcf().set_size_inches(18,8)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4e0ed298-3fb2-48d4-b2a0-af67881d18a8",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>period_open</th>\n",
       "      <th>period_close</th>\n",
       "      <th>capital_used</th>\n",
       "      <th>portfolio_value</th>\n",
       "      <th>longs_count</th>\n",
       "      <th>shorts_count</th>\n",
       "      <th>long_value</th>\n",
       "      <th>orders</th>\n",
       "      <th>ending_exposure</th>\n",
       "      <th>treasury_return</th>\n",
       "      <th>...</th>\n",
       "      <th>trading_days</th>\n",
       "      <th>period_label</th>\n",
       "      <th>algorithm_period_return</th>\n",
       "      <th>price</th>\n",
       "      <th>upper</th>\n",
       "      <th>lower</th>\n",
       "      <th>stop_loss</th>\n",
       "      <th>buy</th>\n",
       "      <th>sell</th>\n",
       "      <th>loss_stopped</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-03 13:30:00+08:00</th>\n",
       "      <td>2022-01-03 09:01:00+08:00</td>\n",
       "      <td>2022-01-03 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-04 13:30:00+08:00</th>\n",
       "      <td>2022-01-04 09:01:00+08:00</td>\n",
       "      <td>2022-01-04 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[{'id': '17ae5cef928c4f478e522b73c84e6b67', 'd...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2022-01</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>631.0</td>\n",
       "      <td>631.000000</td>\n",
       "      <td>631.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05 13:30:00+08:00</th>\n",
       "      <td>2022-01-05 09:01:00+08:00</td>\n",
       "      <td>2022-01-05 13:30:00+08:00</td>\n",
       "      <td>-650002.925012</td>\n",
       "      <td>9.999997e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>650000.0</td>\n",
       "      <td>[{'id': '17ae5cef928c4f478e522b73c84e6b67', 'd...</td>\n",
       "      <td>650000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>2022-01</td>\n",
       "      <td>-2.925012e-07</td>\n",
       "      <td>656.0</td>\n",
       "      <td>668.500000</td>\n",
       "      <td>618.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06 13:30:00+08:00</th>\n",
       "      <td>2022-01-06 09:01:00+08:00</td>\n",
       "      <td>2022-01-06 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.993997e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>644000.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>644000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2022-01</td>\n",
       "      <td>-6.002925e-04</td>\n",
       "      <td>650.0</td>\n",
       "      <td>666.979156</td>\n",
       "      <td>624.354177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07 13:30:00+08:00</th>\n",
       "      <td>2022-01-07 09:01:00+08:00</td>\n",
       "      <td>2022-01-07 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.983997e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>634000.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>634000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>2022-01</td>\n",
       "      <td>-1.600293e-03</td>\n",
       "      <td>644.0</td>\n",
       "      <td>663.763509</td>\n",
       "      <td>626.736491</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</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>2022-12-26 13:30:00+08:00</th>\n",
       "      <td>2022-12-26 09:01:00+08:00</td>\n",
       "      <td>2022-12-26 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.981130e+06</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>456500.0</td>\n",
       "      <td>[{'id': '4b64125852e746189e73dc288cabaf57', 'd...</td>\n",
       "      <td>456500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>242</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>-1.886994e-03</td>\n",
       "      <td>455.0</td>\n",
       "      <td>495.811271</td>\n",
       "      <td>453.399993</td>\n",
       "      <td>456.517601</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27 13:30:00+08:00</th>\n",
       "      <td>2022-12-27 09:01:00+08:00</td>\n",
       "      <td>2022-12-27 13:30:00+08:00</td>\n",
       "      <td>456997.074584</td>\n",
       "      <td>9.981627e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[{'id': '4b64125852e746189e73dc288cabaf57', 'd...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>243</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>-1.837286e-03</td>\n",
       "      <td>456.5</td>\n",
       "      <td>496.098595</td>\n",
       "      <td>450.987670</td>\n",
       "      <td>456.517601</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28 13:30:00+08:00</th>\n",
       "      <td>2022-12-28 09:01:00+08:00</td>\n",
       "      <td>2022-12-28 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.981627e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>244</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>-1.837286e-03</td>\n",
       "      <td>457.0</td>\n",
       "      <td>495.276002</td>\n",
       "      <td>449.088982</td>\n",
       "      <td>456.517601</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29 13:30:00+08:00</th>\n",
       "      <td>2022-12-29 09:01:00+08:00</td>\n",
       "      <td>2022-12-29 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.981627e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>245</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>-1.837286e-03</td>\n",
       "      <td>451.0</td>\n",
       "      <td>494.139699</td>\n",
       "      <td>446.605723</td>\n",
       "      <td>456.517601</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30 13:30:00+08:00</th>\n",
       "      <td>2022-12-30 09:01:00+08:00</td>\n",
       "      <td>2022-12-30 13:30:00+08:00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.981627e+06</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>246</td>\n",
       "      <td>2022-12</td>\n",
       "      <td>-1.837286e-03</td>\n",
       "      <td>446.0</td>\n",
       "      <td>490.939646</td>\n",
       "      <td>444.841077</td>\n",
       "      <td>456.517601</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>246 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        period_open              period_close  \\\n",
       "2022-01-03 13:30:00+08:00 2022-01-03 09:01:00+08:00 2022-01-03 13:30:00+08:00   \n",
       "2022-01-04 13:30:00+08:00 2022-01-04 09:01:00+08:00 2022-01-04 13:30:00+08:00   \n",
       "2022-01-05 13:30:00+08:00 2022-01-05 09:01:00+08:00 2022-01-05 13:30:00+08:00   \n",
       "2022-01-06 13:30:00+08:00 2022-01-06 09:01:00+08:00 2022-01-06 13:30:00+08:00   \n",
       "2022-01-07 13:30:00+08:00 2022-01-07 09:01:00+08:00 2022-01-07 13:30:00+08:00   \n",
       "...                                             ...                       ...   \n",
       "2022-12-26 13:30:00+08:00 2022-12-26 09:01:00+08:00 2022-12-26 13:30:00+08:00   \n",
       "2022-12-27 13:30:00+08:00 2022-12-27 09:01:00+08:00 2022-12-27 13:30:00+08:00   \n",
       "2022-12-28 13:30:00+08:00 2022-12-28 09:01:00+08:00 2022-12-28 13:30:00+08:00   \n",
       "2022-12-29 13:30:00+08:00 2022-12-29 09:01:00+08:00 2022-12-29 13:30:00+08:00   \n",
       "2022-12-30 13:30:00+08:00 2022-12-30 09:01:00+08:00 2022-12-30 13:30:00+08:00   \n",
       "\n",
       "                            capital_used  portfolio_value  longs_count  \\\n",
       "2022-01-03 13:30:00+08:00       0.000000     1.000000e+07            0   \n",
       "2022-01-04 13:30:00+08:00       0.000000     1.000000e+07            0   \n",
       "2022-01-05 13:30:00+08:00 -650002.925012     9.999997e+06            1   \n",
       "2022-01-06 13:30:00+08:00       0.000000     9.993997e+06            1   \n",
       "2022-01-07 13:30:00+08:00       0.000000     9.983997e+06            1   \n",
       "...                                  ...              ...          ...   \n",
       "2022-12-26 13:30:00+08:00       0.000000     9.981130e+06            1   \n",
       "2022-12-27 13:30:00+08:00  456997.074584     9.981627e+06            0   \n",
       "2022-12-28 13:30:00+08:00       0.000000     9.981627e+06            0   \n",
       "2022-12-29 13:30:00+08:00       0.000000     9.981627e+06            0   \n",
       "2022-12-30 13:30:00+08:00       0.000000     9.981627e+06            0   \n",
       "\n",
       "                           shorts_count  long_value  \\\n",
       "2022-01-03 13:30:00+08:00             0         0.0   \n",
       "2022-01-04 13:30:00+08:00             0         0.0   \n",
       "2022-01-05 13:30:00+08:00             0    650000.0   \n",
       "2022-01-06 13:30:00+08:00             0    644000.0   \n",
       "2022-01-07 13:30:00+08:00             0    634000.0   \n",
       "...                                 ...         ...   \n",
       "2022-12-26 13:30:00+08:00             0    456500.0   \n",
       "2022-12-27 13:30:00+08:00             0         0.0   \n",
       "2022-12-28 13:30:00+08:00             0         0.0   \n",
       "2022-12-29 13:30:00+08:00             0         0.0   \n",
       "2022-12-30 13:30:00+08:00             0         0.0   \n",
       "\n",
       "                                                                      orders  \\\n",
       "2022-01-03 13:30:00+08:00                                                 []   \n",
       "2022-01-04 13:30:00+08:00  [{'id': '17ae5cef928c4f478e522b73c84e6b67', 'd...   \n",
       "2022-01-05 13:30:00+08:00  [{'id': '17ae5cef928c4f478e522b73c84e6b67', 'd...   \n",
       "2022-01-06 13:30:00+08:00                                                 []   \n",
       "2022-01-07 13:30:00+08:00                                                 []   \n",
       "...                                                                      ...   \n",
       "2022-12-26 13:30:00+08:00  [{'id': '4b64125852e746189e73dc288cabaf57', 'd...   \n",
       "2022-12-27 13:30:00+08:00  [{'id': '4b64125852e746189e73dc288cabaf57', 'd...   \n",
       "2022-12-28 13:30:00+08:00                                                 []   \n",
       "2022-12-29 13:30:00+08:00                                                 []   \n",
       "2022-12-30 13:30:00+08:00                                                 []   \n",
       "\n",
       "                           ending_exposure  treasury_return  ...  \\\n",
       "2022-01-03 13:30:00+08:00              0.0              0.0  ...   \n",
       "2022-01-04 13:30:00+08:00              0.0              0.0  ...   \n",
       "2022-01-05 13:30:00+08:00         650000.0              0.0  ...   \n",
       "2022-01-06 13:30:00+08:00         644000.0              0.0  ...   \n",
       "2022-01-07 13:30:00+08:00         634000.0              0.0  ...   \n",
       "...                                    ...              ...  ...   \n",
       "2022-12-26 13:30:00+08:00         456500.0              0.0  ...   \n",
       "2022-12-27 13:30:00+08:00              0.0              0.0  ...   \n",
       "2022-12-28 13:30:00+08:00              0.0              0.0  ...   \n",
       "2022-12-29 13:30:00+08:00              0.0              0.0  ...   \n",
       "2022-12-30 13:30:00+08:00              0.0              0.0  ...   \n",
       "\n",
       "                           trading_days  period_label  \\\n",
       "2022-01-03 13:30:00+08:00             1       2022-01   \n",
       "2022-01-04 13:30:00+08:00             2       2022-01   \n",
       "2022-01-05 13:30:00+08:00             3       2022-01   \n",
       "2022-01-06 13:30:00+08:00             4       2022-01   \n",
       "2022-01-07 13:30:00+08:00             5       2022-01   \n",
       "...                                 ...           ...   \n",
       "2022-12-26 13:30:00+08:00           242       2022-12   \n",
       "2022-12-27 13:30:00+08:00           243       2022-12   \n",
       "2022-12-28 13:30:00+08:00           244       2022-12   \n",
       "2022-12-29 13:30:00+08:00           245       2022-12   \n",
       "2022-12-30 13:30:00+08:00           246       2022-12   \n",
       "\n",
       "                           algorithm_period_return  price       upper  \\\n",
       "2022-01-03 13:30:00+08:00             0.000000e+00    NaN         NaN   \n",
       "2022-01-04 13:30:00+08:00             0.000000e+00  631.0  631.000000   \n",
       "2022-01-05 13:30:00+08:00            -2.925012e-07  656.0  668.500000   \n",
       "2022-01-06 13:30:00+08:00            -6.002925e-04  650.0  666.979156   \n",
       "2022-01-07 13:30:00+08:00            -1.600293e-03  644.0  663.763509   \n",
       "...                                            ...    ...         ...   \n",
       "2022-12-26 13:30:00+08:00            -1.886994e-03  455.0  495.811271   \n",
       "2022-12-27 13:30:00+08:00            -1.837286e-03  456.5  496.098595   \n",
       "2022-12-28 13:30:00+08:00            -1.837286e-03  457.0  495.276002   \n",
       "2022-12-29 13:30:00+08:00            -1.837286e-03  451.0  494.139699   \n",
       "2022-12-30 13:30:00+08:00            -1.837286e-03  446.0  490.939646   \n",
       "\n",
       "                                lower   stop_loss    buy   sell loss_stopped  \n",
       "2022-01-03 13:30:00+08:00         NaN         NaN  False  False          NaN  \n",
       "2022-01-04 13:30:00+08:00  631.000000    0.000000   True  False        False  \n",
       "2022-01-05 13:30:00+08:00  618.500000         NaN  False  False        False  \n",
       "2022-01-06 13:30:00+08:00  624.354177         NaN  False  False        False  \n",
       "2022-01-07 13:30:00+08:00  626.736491         NaN  False  False        False  \n",
       "...                               ...         ...    ...    ...          ...  \n",
       "2022-12-26 13:30:00+08:00  453.399993  456.517601  False   True         True  \n",
       "2022-12-27 13:30:00+08:00  450.987670  456.517601  False  False        False  \n",
       "2022-12-28 13:30:00+08:00  449.088982  456.517601  False  False        False  \n",
       "2022-12-29 13:30:00+08:00  446.605723  456.517601  False  False        False  \n",
       "2022-12-30 13:30:00+08:00  444.841077  456.517601  False  False        False  \n",
       "\n",
       "[246 rows x 46 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from zipline import run_algorithm\n",
    "\n",
    "results = run_algorithm(\n",
    "    start = start_time,\n",
    "    end = end_time,\n",
    "    initialize=initialize,\n",
    "    bundle='tquant',\n",
    "    analyze=analyze,\n",
    "    capital_base=1e7,\n",
    "    handle_data = handle_data\n",
    ")\n",
    "\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1b401f1f-7f15-4f19-ab05-4d7f207d5483",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyfolio as pf \n",
    "returns, positions, transactions = pf.utils.extract_rets_pos_txn_from_zipline(results)\n",
    "benchmark_rets = results['benchmark_return']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0abca57d-0ca1-4d3f-b311-abf72c596f7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Rolling Sharpe ratio (6-month)'}, ylabel='Sharpe ratio'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyfolio.plotting import plot_rolling_sharpe\n",
    "\n",
    "plot_rolling_sharpe(returns,\n",
    "                    factor_returns=benchmark_rets\n",
    "                       )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e4f1e71d-bba5-4146-b22b-1fb18922034c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Worst drawdown periods</th>\n",
       "      <th>Net drawdown in %</th>\n",
       "      <th>Peak date</th>\n",
       "      <th>Valley date</th>\n",
       "      <th>Recovery date</th>\n",
       "      <th>Duration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.80</td>\n",
       "      <td>2022-10-06</td>\n",
       "      <td>2022-12-23</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.90</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>2022-10-05</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.90</td>\n",
       "      <td>2022-01-17</td>\n",
       "      <td>2022-03-15</td>\n",
       "      <td>2022-07-13</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.50</td>\n",
       "      <td>2022-07-29</td>\n",
       "      <td>2022-08-02</td>\n",
       "      <td>2022-08-05</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.47</td>\n",
       "      <td>2022-08-05</td>\n",
       "      <td>2022-08-10</td>\n",
       "      <td>2022-08-12</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyfolio.plotting import show_worst_drawdown_periods\n",
    "show_worst_drawdown_periods(returns, top=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "18b0b169-507d-431f-bbe1-2ec6b1ca63b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Cumulative returns'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5HBkZGdi8ebPDNfV6PWbMmIFrrrkGq1atwrx589DQ0ACO45Cdnc2f9/rrryMnJwcRERGYN2+eaMrt+++/R1FREcLCwpCZmYk9e/Zg9erVPV6L+A5tUupHBw8ehFarRUtLC2bMmOH0HGHgI5zWEoqIiEBLSwsA66hPbGys9xtLCBmyOro7sGbrmoC24eG5DyNc5vw1sCeVlZW466678OCDD0KpVKKsrAwKhQL//e9/kZSUhBUrVmD58uX46aefAAAvvvginnvuObz11luYNWsWSkpKRKkFgDUIvOmmm6BSqfDee+9BJpNh/vz5uPbaa1FfX8+f98knn+DVV1/Fhg0bkJeXhzfeeAOLFy/GqVOn0N7ejiuvvBJff/01pk+fjpMnTyIiIgKrV6/G3LlzHa5FfItGfPyEMcZPTbW2tva43YQw8LGf5rKhBGdCCPnV2rVrwXEccnJycPbsWSxcuBAAkJeXh7Vr1yI/Px+RkZFYsWIFfvnlFwCA0WjEk08+iTfffBMXXnghwsPDMWHCBIwfP1507QcffBCVlZX44osvIJPJemzD448/jrfeegvjxo1DeHg47r33XnAch71796KmpgYWiwUTJkxAWFgYJk6ciOHDh/usP0jvKPDxE4vFwg/dMsbQ3t7u9DxXproiIiL479Vqtei+lpYWHD16FBqNpr9NJoSQAcGW3NzW1oa1a9fisssuw8aNGwFYR2Kuv/56jBs3Dueddx6/KOTEiRPo6urCBRdc0ON13333XXzxxRf49ttvexyBB6wfQEtKSjBp0iR+hRnHcSgvL0dVVRUmTJiAhQsXYvTo0Xj++edpYUqAUeDjJ/bbS9gHLDa2wEehUIiqNAtFR0fz9507d44vZGixWLB//36cPXsWx48f91bTCSFkQIiKisLixYuxYsUKvPPOO3jqqafwzDPP4LrrrsNXX32FXbt28ecyxiCVSiGR9Pw2GBcXh+bmZlRUVPT6c20j+HV1dWCMib5uvPFGcByHDRs24J133sF3332H/Px8HDt2zDtPmriNcnz8xD7wsS1Ztz/HYDAA6HmaC7BuW5GRkYGKigqYzWZUVVUhLy8PTU1NfLIzTYERQjylClXh4bkPB7wNnuru7oZCocD69euxatUqXHLJJQCAL774gj+noKAAJpMJe/fuxbRp05xe55JLLsFFF12Eiy66CDt27MDIkSMBABKJRLQaKyoqCklJSdi1axeuuOKKHtt1wQUX4IILLsANN9yAl19+Ga+//rrDtYjv0YiPn7gy4iMMVnoLfACIsv9ra2sBQJQcZzAYvPrH1NnZiUOHDuHkyZM+rY9BCAk8juMQLgsP6Jd9krErurq6sHHjRrzyyiu45ZZbkJycjK+++gparRaHDh3C2rVr+XNVKhXuv/9+LFmyBD///DM6Ojqwa9cuPgfIZvny5fjDH/6ACy64AFVVVQCAtLQ0tLS04PDhw/xCk/vuuw/33Xcftm/fjo6ODuzfvx/Lli0DAJw8eRKffPIJ2tra0NzcjLq6OuTl5fV4LeJbNOLjJ/aBT1dXFwwGA1+TBxAHPr3NJ9vuVyqV6OzshE5nXfppvypAr9f3mCfkjtbWVvzyyy/8lFpMTAxSUlL6fV1CCPGGtWvXYu3atVAoFCgsLMQ777yD888/H6mpqfj973+PxMREjB07Fo8//jg/+gMATz31FKRSKa6++mq0traisLAQ//znPx2uv2bNGtTU1OCCCy7Ajh07kJeXhz/+8Y+YNWsWRo8ejT179uD+++9HW1sbrr76amg0GuTm5mLFihUArHssrl27FkuWLEFMTAyuu+463HfffQDg9FrEtzhGH99FNBoNoqKi0N7ejsjISK9dt6GhweGTxOTJk5GcnMzfPn36NEpKSgAAU6ZMQVJSUq/X3L17N5qbmwEAkyZNwv79+0X3z5w50ytL3X/55Rc0NDTwt9PT0zFhwoR+X5cQEjy6u7vR1NSEhIQE0WbIhAST3n5PXX3/pqkuP7Ef8QEc83zcGfEBxKu+ysrKHO7X6/VutLBn9tdpbGyk6S5CCCEDEgU+fuIs8LHP87EtcZRIJC5NUQnPcZYz5K3Ax5ZwbWM0GtHa2grAujLi8OHD+Pnnn2l+mhBCSNCjwMdPehrxsY2cWCwWfil7eLhriX3OgiNhzlBXV5enzeUxxpxui2Gb+mpra0N1dTVaW1uxa9cuqj5KCCEkqFHg4yfCwMdWg8dkMvHTWx0dHXwQJCxQ2BtngU9WVhb/vTdGfMxmM786LDIykg/IbIFPZ2en6Pzi4uJ+/0xCCCHEVyjw8RNh4BMXF8d/b6vg7G5+D+AY+HAc5/XARzjaEx4ezidL63Q66HQ6h2kwrVZL+T+EEEKCFgU+fiLcmysqKor/3jYdJVw15eqIj0wmg1Qq5W/Hx8dDoVDw+8l4O/CRyWSilWYNDQ0OP8NisTiMAhFCCCHBggIfP7HVwAEgWmbX2dkJg8GAc+fOAbDWe0hISHDpmhzHiUZ9bEvjFQoFAGtQ1d/RF+GIjlwudwh87Ed8AKoaTchARiO2JJh54/eTAh8/EU512Qc+VVVVfB5NRkZGj3t0OWMbHeI4jg98bMEQY0y06akn7Ed8wsPD+am41tZWp5vt0QZ8hAw8tj2rhKPThAQb23uScLbDXVS52U+ELyZhYWEIDQ1Fd3c3Ojo6+OCE4zjk5OS4dd0RI0ZAIpEgMTGRH+mJiYnhV1e1tLS4nDPkjH3gAwBJSUl8tWhnu8zTiA8hA49EIoFMJoNGo4FUKvVoywhCfMW2wlij0UCpVPa6uWxfKPDxE9uIj0Qi4ev0tLe3i5acJyUlub3FhEqlcqiiHB8fz3/f3NwsSnh2V0+Bj33BRIVCAYPBAMYYjfgQMgBxHIfo6Gg0NTXxFeEJCTZKpVKUJ+sJCnz8xBb42KaxbIGPkLujPT2JioriR5Sam5uh1+sRGhoKiUTi9qc4Z4FPbGwsf30blUoFiUTC7x1mNpv7NRRJCPG/kJAQJCcnO607FsxMFhOKm4sRKglFXlweJBxlcQxGUqm0XyM9NhT4+Il94BMWFia6PyIiQrTMvT84jkNcXBzq6+thNBrx3//+F4B1tCk0NNThKyQkBDKZDCEhIaLj0dHRosDHVhyR4zgkJSWhpqZGdJ9cLkdnZydMJhOOHj2K8ePH03A5IQMMx3EDaq8uk8WE9w+/j0p1JQBgcvpkXFZ4WUDbRIIbBT5+Ygt8bKMg9lNaOTk5Xg0SkpKSHKooWywWGAwGpyuxnLEFRDbCF0P7wEehUCAzMxONjY0wmUyoqalBbGxsv6bZCCEDk8FkgIVZEBYa1vfJ/bSlfAsf9ADA/nP7sSBvASLkrpUFIUMPBT5+wBjjk5uFU102oaGhSEtL8+rPzMjIgMlkgkajgclkgtFohMlkQnd3N//VF5PJxAdstqkym8TEREgkEn41mlwuR0REBMaOHYuDBw8CAI4fP46oqChER0d79bkRQpyzMAs0eg0szOKzn6E36WEwG5ASngJFqMLh/iN1R/DN6W/Q2d2JiWkTcXnh5T4b+W3UNWJbxTbRMcYYTjWewpSMKT75mWTgo8DHD4Tz5bZRk6ioKD5wyM7OdmsJuys4jkNubm6P9zPG0N3d7TQo0mg0qKioEJ0vHPkBrAFcXFwcmpqaAPxaOygtLQ1qtRoVFRWwWCw4cOAAZs+e7fB4Qoh36Iw6lLaU4kzTGZS2lKKz2z8FRKMUUVg6aSnilHFo7mhGaUspTjWdQmlLKX/OgXMHkBubi/Ep433ShkO1h5zWdTnReIICH9IjCnz8QBj42Ka6FAoFpk2bBp1Oh4yMDL+3ieM4yGQyyGQyh2k3o9HoEPjY5yQBQHp6Oh/4CLPsCwsL0dbWBrVajc7OTpw8eRLjx4/3/pMgZJAymAyQSqQIkTh/ia7T1uFU4ykUNxejRlMTkKKD7fp2vLDzBcSExUDdpe7xvC9Pfoms6CzEhMWIjmsNWnAch3CZZ+U2GGM40XjC6X3lreXoNHZCKXNvlSwZGijw8QNnG5QC1j27vJXQ7E0ymQxhYWGipfbCJfI2aWlpfO0P4TYbEokEEydOxLZt29Dd3Y36+nowxijRmZA+6Lv1ePfgu6hur4aUkyIxPBEpESlIjUzFsLhhMFlM+OrUV6hqqwp0U3m9BT0AYDQb8eLOFzEvbx4mpU1ChDwCP5b8iG0V2yDhJBiVNApTM6ZCyvW8ClQRokBMWAxCpb/mGdbr6tHS2eL0fAuzYP+5/ZiTM8ezJ0UGNQp8/KCnwCeYRUZGigIfZwEax3FITU11+viwsDAkJCSgtrYW3d3daG9vp1wfMuQdOHcAu6t2I1QaiuzobGTHZCMzOpNPAv6x9EdUt1cDAMzMjDptHeq0dThYezCQze43MzPjp9Kf8FPpT6LjFmbBsfpjOFZ/rM9rhEpCMSF1AmZkzUC8Mh6Haw/3ev6uql2YkTWjx1EzMnTRb4QfKJVKjBs3DiaTSbRdRTCLjIwUbZzqSdASHx+P2tpaANZCihT4kMGq09iJA7UHUNZaBpPZhARVAhLDE5GoSkRqZCoO1x3G98Xfw2T59UNQVVsVtlduB8dxGBE/Anlxedhbvdejny+TypAXm4fh8cORH5/v8fSRK8pby/HvQ/92OB4uC0d+XD6GxQ9DpDwSHx/5GB3d/dsyR6jb0o1fan7BLzW/OL0/OyZbtLpLa9DiSN0RTEyb6LU2kMGBAh8/kMvlyMzMDHQz3GKf0+NJ0SjhKFFLSwuGDRvW73YREkgWZkG7vh0tnS1o7WyFLESGKHkUPj76MXTGX7dqqVBX9HIVMcYYTjWdwqmmU263Z2bWTAyPH47smGy/jWwUJBTgunHXYV/NPoRIQpAVnYVhccOQEpEims5ePn05NpdtxoHaAz7PQZJwElxeeDk2nNwg6vudlTtRlFpE0+xEhAIf4lRycjJOnjwJk8nksCWGq1QqFRQKBfR6PVpaWqDX6/nVX4QMJFqDFhtObkBpS6lo1MaX8uPzkR+Xj5r2GhytP+pw/x8m/wE5Md6p9u6u0UmjMTppdK/nRCmicPmoy1GUVoTtFdtRoa6AweRYQ0weIu/1OowxGM3GXs+Znjkd8ap4zM6eLQp8GjsaUdxcjIKEAv5Yc0czQqWhiFL0b9sDMnBR4EOcksvlmDdvHvR6vcf7onAch5SUFFRUVMBsNuP48eOYNGmSl1tKiO99efJLnG467dVrZsdko6qtymnNHQknwXl55yE9Kh2ANdD48MiH/P358fkBC3rclRWdhZsm3AQLs6BeW48KdQVaOluQqErE1IypLo3GtHS2YHPZZpxqOuUQPMUr4zEvdx4AYHj8cCSqEtHY0cjfv6NyBx/4bDy9EbuqdgEALiq4CDOzZnrraZIBhAIf0iOFQtHvEZrhw4ejtrYWBoMBdXV1aG9v7/cGc4T4k7pLjdPNrgU9aZFpyI/PR1tXG+q0dWjQNYjuT1QlYmb2TExMnQiO4/Df0v9ia/lW0TkyqQy/LfwtH/QAwKikUbis8DLsqd6DuLA4XFp4ab+fl79JOAlSI1ORGul8QURv4pRx+N2Y31k3QTZo0dTRhMaORoRKQzEyYSSfHM5xHGZlz8J/TvyHf2yFugLn2s9BJVNhd/Vu/vh3xd8hNzYXKREp/X9yZEAJusCnq6vLac0YMjDJZDLk5OTg9GnrG0dnZycFPmRA2Xl2p0OOikwqE02/SDgJZmXNwnnDzoNU8uuy7LNtZ/Fz5c8AgHl58xzeZOdkz0GluhKV6kqESEJwWeFlmJDqfGp5cvpkTE6f7K2nNSBxHIdIRSQiFZHIi8tzes64lHH4b+l/oTVo+WM7zu5AYWKh6P+RMYavT32N2ybfRjlAQ0xQBD719fX44osv8Pnnn0Ov12Pnzp09nrt+/Xo89thjOHv2LCZNmoQ333wTI0aMcPn+gcpgMqBB14A2fRuSwpOQFJ4U6Ca5TFi12ZWtMgjxt67uLpzTnEOUIgrxynj+jXBL+RbsqdojOndK+hRcOtI64lLcXIyWrhaMiB+BWGWsw3WzorOQNb7n/erkIXIsKVqCem09VDKV02sQ94RIQjA9czp+LPmRP3a84bjTKcWzbWdxpP6IzypLk+AUFIHPJZdcgsjISMTExIg2vrS3e/duLFu2DF988QWKiorwxBNPYPHixTh9+jRCQkL6vH8gsTALylvLsf/cftS014iKhHEch0XDFw2Y+Wnh5qYU+JBgU95ajo+OfMRv9aCSqZAdnQ2ZVIZDdYcczp+SMYUPjIRJs54KlYYiI9r/1dsHsynpU7C1fCs/KscYw4kG51WevzvzHUYmjOwzyZoMHhwLRK1zO7bprXfffRevvfYa9uzZ4/S8K6+8EkVFRXj00UcBWAsDpqen4+2338ZFF13U5/2u0Gg0iIqKQnt7u9dq7hyqPSQaFufAIU4Zh6yYLNESVIPJgGMNx7CvZh9q2nsOAG0yozMRrYj2Sht9SavVory8HIB1V/fk5GSHcyScBJGKSJgtZkQpojAlfYqoSit/LYMWp5tOIyUiRZQDEaz03Xq0drV6bTlviDQEylAlVDIVJNyvJQYadA2oaa9BelT6gBoNDLSK1gq8e/Bdl1dqTUybiCtGXeHjVhFv+PbMt/j57M8unTsraxYWFSzycYuIr7n6/h0UwyCu5vRs2bIFDz/8MH87JCQEc+bMwd69e3HRRRf1eX+g/Lf0v2jXtzscl4fIkRmdCblUjpbOFjR3NqPb7PqISFVbFaoQPKXre2I0GlGnrwMAtLW2oRGNfTwC2Fy2GYsKFkER8mtydaW6Enur98LCLOA4DosLFmNa5jTR40wWE7498y3KWspgZmbvPhEPtOnbfFLDhOM4hIWEIVwWjm5Lt2hEsDCxEHmxeYgOi0a0wvqlN+mhN+m93o6BjIHh8xOfuxz0ZEZl4rcjf+vjVhFvmZE5A7urdru0U/3Oszuxp9r5B27iukhFJEYnjsaIxBHgwMHCLGCMwcIs/BcDg9liBgNDflx+QEbagiLwcYVarYZarUZ2drboeFZWFs6dO9fn/T0xGAwwGH5dHqnRaAAAI0aM6LNoX1FREb766ivRsUsvvRQHD4rLy2uNWoc3vylXTMHUK6eipLnE2o5OA/552z97/Xk2V62+Cin5vyZJluwpwfd//77Px4UqQnHnW3eKjm16YxNObj3Z52PzpuThorvFwePbK95Gh7rvyqxzlsxB9PBoAIDFYkFLdQs+/NOHvT8IwDqsw+9f+j3C436tQnvo20PY+YE1B+wlvAQAkHJScByHEEkILMwCo9mI2LRY3PDsDaLrffnMl6g61negOH7ReMy+cbbo2N9v+HufjwOAS//fpcga92tOx9kjZ/HVs1/18ohfrfxgpej2jvd34PB3h/t8XOaYTPz2T7++IZ9sPIlHlzyK1nOtfT521g2zMOGiX5NpdS06vPPHd1xq7/XPXI+4jF+LVJ7YfAKb39rc5+NUMSrc+vKtomPf/t+3KPulrM/HFs4txILbFoiOvbb0NXTr+/7AcOHKC5E/LZ+/XVdSh89Wf9bn4wDg9jdux2+n/5ZPXH7hhRfwwgsv9Pk4V18jnLnvvvtw33338be1Wi1GjhzpUnu//PJLTJz4a8Xib775BnfeeWcvj7AKDw/nFyLYPPjgg/joo4/6fOzFF1+M119/XXRs0qRJqK+v7/Oxzz77LK6//nr+9pkzZ7BgwYJeHvGrffv2ISXl19fDf/7zn/jzn/8MANCb9E5rAHHgEJsei+vX/vozTRbTkHmNAIAP/t8HAX+NCJeFi0aubZKTk7F//37RsTvuuAMbN27s9edZLH0HucAACnx0OmtVVJVKJToeFhaGurq6Pu/vyZo1a/Dkk086HO/tMTbOdlVvamrqNdCyMXTaFfJigLZZ6/xkO5xFvALBZDS59FiZUuZwTK/Tu/RYvdZxtKBD3eHSY83GX0deLBYLYHb9udr/Ihu7jC49Vq50/BTRqel06bGGDscia66219xtdrjt6mOdtcOVx3ZqOh2Oufp/Y+wSvylYLBbX/2/M4v+bbkO3x89Vr3Xx91Dn+Huoa9XB2Nl7gTvA+nci5M7/TVxYnGgKUaPRuPR33p/XCNuHMBvGmEuPA6yjrEJdXV0uPVa42bCNWq126bGtrY5vovX19S49trNT/DtsMplcfq5ms/hvTqfTufRYZ1vo0GuEI1++Rmjh+vNubW11+XeiLwMm8LGtDDIajaKpMYPBAKVS2ef9PXn44YdFn6o0Gg0yMjKQkpLS54hPQkKC02NpaWmiY53dnWAQL6NUKO3q43BARLz1RSdEEgKZVMaPZNhbOmUp5OlytHZZX2gUlQrsSNrRa1sBQKFSYG7uXNGx4rRinEvq+5cpNzXX4bHrk9dDLu17mHJc5jhEqqzzrRGREVAlqvBF0heic2zDn/bTU/b/B7IwGd9PvVHFqByOKSOVLj1WrnJ8Tq48DgCkoVKH264+1n7LgbDwMJceq4x0/P1Wxagcg2snZGHiYFgikbjcXolU/H8TKg/1+P9GEaFw6bGKcMe6UuGx4ehW9j3iEyIT96/9/01YaBhCJda8MvuRgrEpY0V/i5GRkQ5/5864+hrhjH2OAsdxLj0OEK+kBKwfAF15bHi44x5fMTExLj02NtZxRZqzfD5n7F+jQ0JCXH6uUqn4by48PNzhsUazEUazERZmgZSTIiw0DLnpuciLzUNZ668jjcH+GuGsHQP5NUIlU0HKSe0f5vT3JjY2ts/fCYvF4tKgRVAkN9v0ltxsNpuhVCpx8OBBjBo1ij9+/fXXY8yYMfh//+//9Xq/MPenN75IbnamuaMZB84dgFqvRqQ8EvHKeMQp45AUkeTTDQYD5dtvv4XZbEZkZCR+85vf9Hhec0czfij5AU0dTU7vD5GEoE7b9y82YK1uOy1jWt8n+pA8RI70yHSnidqeMFvM6OzuhM6oQ6exEx1G61RjnDIO8hA5jtQfQaOuEW36NrR1tYn2j6JaJWLCl77UyFQsm7qMH3Y3WUzYcHIDipuLkRebhytHX0m7fA9CjDG0dLY43UqDuKepswmHag/hbNtZgFlfbyScBBJOAo7j+A/ytmMSToJrxl7j1QKSAyq52RVSqRTTpk3Dpk2b+MDGbDZj27ZtuPvuu/u8P9jEq+KxcPjCQDfDb0JCQmA2m/tczh6viscN42/o9RzAuht2a1crdEYdtldst/6x2ZmXOw9Z0T3XUBmIpBIpIuQRiJA7/8S1IE+cF9Ft7obGoIFMKkO4LJyCHwF1lxqH6w6DMYbJ6ZNFuQYhkhBcNfqqALaO+APHcYhXxQe6GYNCWlTagKmH5P6W236kVqsxe/ZslJaWAgBWrlyJNWvW4MCBA+jo6MBDDz2E/Px8TJ061aX7SeDYavl4q46PUqZEelQ6RiSMwG2TbxOt7uI4DrOzZw+6oMcTodJQxCnjECGPoKDHTkxYDOblzsP8vPk9BpKEkMEnKEZ85s6di23btvG3bS/QO3fuxMmTJ9Hc3Ixhw4bhqquuwtmzZ7F48WJoNBpceOGF+PTTT/nH9XU/CRxb4GMymcAY8+qbMMdxuGTEJZibMxc6ow6R8kioZI55JIQQQkhQ5fgEA3/l+Aw1e/fuRWOjtX7PhRdeKKrmTAghhPSXq+/fQT3VRQYP4ZYhtG0FIYSQQKHAh/gF7ddFCCEkGFDgQ/xCGPiYTK5tEUAIIYR4GwU+xC9oqosQQkgwoMCH+AVNdRFCCAkGQbGcnQx+wsBHp9NBqxXv0RISEiLaaoQQQgjxBQp8iF8IA5/S0lK+KKXQ8OHDUVBQ4M9m9chgMEAmk1HRP0IIGWRoqov4hUql6jOIKCsrg1arDXjyc1lZGX788Uf88ssvoDJXhBAyuNCID/ELlUqFiRMn8kUMhbRaLdRqNcxmM7Zu3YrQ0FDMmzcPcnnfO7/3B2MMXV1dCAsLEwVlp06dAgA0NjaitbUVcXFxPm0HIYQQ/6HAh/hNSkoKUlIcd+LV6XTYsmULf7u7uxtNTU1IT0/3WVsYY9i9ezdaWlpQUFCA4cOHi+6zqaiooMCHEEIGEZrqIgEXHh6O5ORk0bH29naf/kyDwYCWlhYAQGVlJR/s2E+z1dfXo6ury6dtIYQQ4j8U+JCgMG7cOAwbNoy/rdFofPrzhNc3GAz8KjP7IIcxBrVa7dO2EEII8R8KfEhQkMlkGDlyJJ/Xo9FofJpYbD+i1NTUBMAx8AGsU3GEEEIGBwp8SFCx7ahrNBphMBh89nPsR5Qo8CGEkKGBAh8SVGyBD+Db6S77AootLS0wm81OAx/7cwkhhAxcFPiQoCIMfHyV4Gw2mx1GcSwWC1pbW50GPh0dHVTPhxBCBgkKfEhQiYqK4r/3ReDDGENxcTEfyMhkMv6+xsZGUeATHx8PAD2OBBFCCBl4KPAhQSU8PJzfyd0XgU9tba1ou4yRI0fyxQubmpr4ACc0NBTR0dH8eTTdRQghg4PXAp+GhoaAbzVABj6O4/hRn87OThiNRq9eX1g5esSIEcjIyOADHK1Wi87OTgBAWFgYIiIi+HNpSTshhAwOHgU+t9xyC7777jv+9ooVK5CSkoLExETs2bPHa40jQ5Nwuqutrc2r17aNInEch7y8PHAch4SEBIfzwsPDERsby48GVVRUQK/Xe7UthBBC/M+jwOc///kPpkyZAgDYs2cPPv74YxQXF+Odd97BAw884NUGkqFHOMXkrekurVaL0tJSfsoqIiICEon1199Z4BMfHw+lUomsrCwA1orOtj28CCGEDFweBT5KpRKhoaEAgHXr1mHlypUYNmwYFi1ahMOHD3uzfWQI8vaIj06nw86dO0WBi3D1WHR0NJ9XZGNLbC4oKOB/12tqamjKixBCBjiPAp/f/va3uOWWW/DII49g06ZNWLlyJQCgvLwcKpXKqw0kQ49KpeIDEfvAp6OjA8eOHeMLDvbFZDJh//79DvlnwsBHIpEgNjZWdL9SqQRgXfVVUFDAHz9+/DgtbSeEkAHMo8Dnb3/7G7Kzs3HixAl8+eWX/JvGjh07cOedd3q1gWTo4TiOn+7S6/Wi3JpDhw6hsrISe/bsgcVi6fU6jDEcO3bM6YosYeADQBT4REVF8bk9AJCdnc0nOre1taGmpsbt50QIISQ4hPR9iiOlUokXX3zR4fhtt93W7wYRAliDj+bmZgDWPB+FQgFAvLrKYDAgLCzM4bGtra1oaGiA2Wzmg5SQkBDRqI994JOZmYmKigoYjUaMGjVKdB/HcRg9ejR2794NADh16hRSUlIcpscIIYQEP49fuRsaGrBnzx40NjY6DP3ffvvt/W4YGdqECc5tbW1ISkpyOEev1zsEPowx7N+/32Gfr3HjxqGjowOnT59GYmIivxmqjVwux4IFC2AymRzuA6w5PykpKairq4PBYEBxcTEKCwv78QwJIYQEgkeBz4cffoilS5ciKSkJmZmZkEql/H0cx1HgQ/rNlZVdXV1diImJER0zm80OQU9ubi5SU1MBWEd2hNWahaRSqeh32V5hYSEaGxthNptRXl6OzMxMhIeHu/J0CCGEBAmPAp9HH30UL774IuXzEJ8JCwtDaGgouru70dbWBsaYw8iis7o69knMycnJGDlyJH/b2WiOq5RKJfLy8vgtL06cOIGpU6d6fD1CCCH+51Fyc2trK2666SZvt4UQnjDB2WAwQK/Xo7u7W3SOs8BHeE5qaiomT57M1+vxhry8PH56rbGxEQ0NDV67NiGEEN/z6B3h+uuvx8aNG73dFkJE7Ke7XAl8hCM+/Rnd6UlISIhoBKmystLrP4MQQojveDTVNXLkSPzpT3/CTz/9hHHjxvEF3mwox4d4g30hQ/tAxtmO6cLAx1errlJTU3H06FGYTCZ+by9CCCEDg0fvDF988QWysrJQUlKCkpIS0X2U3Ey8xX7Ex77IYF8jPr4KfDiOg0KhgE6ng16vB2NMVPeHEEJI8PLonWHLli3ebgchDhQKBeRyOQwGA9ra2hx2ancWdAgDH/uRSG+3TafTwWQywWQy+fRnEUII8R63c3wYY8jLy6M9i4jPcRzHT3cZjUZoNBrR/RaLxSEYEgY+vS1N7y9bQUXA+cgTYwxHjx7F5s2bsXPnTvp7IYSQIOF24MNxHFQqFV9VlxBfEub5tLS0ONxvX+PHXyM+wsKJzgKflpYWnD17Fh0dHVCr1SguLvZZWwghhLjOo6mup59+GsuWLcONN96IcePGOWxMOnz4cK80jhBhgKHT6Rzu37dvH8aMGYPMzEwA/snxAcQjPs6SrO2PdXR0+KwthBBCXOfRO8Nll10GANi8ebPDfRzHwWw296tRhNgIAwz7oMZkMsFiseDIkSNQq9UYPXp0QAIfZyM+9lNwXV1dDvlIHR0d2L9/P8LDw1FUVEQJ0oQQ4gce1fGxWCw9flHQQ7ypp1o8c+fORXZ2Nn+7qqoK+/btC9rAx1k+0okTJ6DRaFBbW4v6+nrfNJQQQoiI90raEuIDwgBDSC6XY8yYMZgwYQKfxNzU1CQKQoIp8AEcp7+EVZ8pZ44QQvzDo3eGRx55pNf7//rXv3rUGELsyeVycBwn2qdLKpXy21Ckp6ejsbER586dAyDOpfFl4CNsV0NDA3bt2oUpU6bwP7OnwMdWm8g+CKJVX4QQ4h8evTPU1dWJblssFpSVleHAgQP43e9+55WGEQJYc8ZkMplox3X71VrC6TBbQMFxnFf36HLWrtDQUD7AaWlpQXV1NXJycgDAYYd4YdsAxxEejUYDo9HY487xhBBCvMOjwOedd95xenzDhg3YtGlTvxpEiD2FQiEKJOyDA2d5QKGhoT5PFo6KikJTUxN/u7KyEtnZ2eA4rs+pLvvAhzGGlpYWpKSk+K7BhBBCvJvjc9lll2Hnzp3evCQhDoGNfd6Ps8DHl9NcNoWFhUhLS+Nv63Q6PhCyBT7CUSdb4MMYEwVMNjTdRQghvufVwKempsahui4h/WUf6MTFxYluByrwiYyMRFFRESZNmsQfq6yshMVi4XeSj4yM5EeebIFPa2srP4Il3I+M/nYIIcT3vJLcbLFY0NDQgK+//horV670SsMIsbEPfOLj40W3AxX42CQnJyMsLAxdXV1obGxEW1ubqG0KhQJdXV1ob2/HL7/8Iir5kJOTgxMnTjjdkoMQQoj3eSW5WSKRIDk5GR9++CEuuOACrzSMEBv7wEa4jYWz+wH/Bj4cxyE7OxunTp0CY0y0PYVMJkNERARfwFC4hJ3jOCQlJaG6uhrNzc0wGAwwGAw91i4KdmazGRaLhTZsJYQENa8mNxPiC/ars+yTlp0tefdn4AMAmZmZKC4uhtlsFuXvyOVy5Ofn48yZM3xwY5OUlITQ0FBERkbyyc4ajQYJCQl+bbs3GAwGbN26FWazGbNnz0ZERESgm0QIIU55lOOTm5vr9HhraytmzJjRrwYRYi8pKYkPfoqKihzuty15F/J34COTyUSJzsLjKpUKRUVFOP/88/Gb3/wGo0aNwvDhwzF27FgA1jwgm4E63VVaWgqj0Qiz2YyjR48GujmEENIjjwKfyspKp8erq6tx7Ngxt69nsViwatUqJCcnIzw8HDfccAO0Wq3Tc//+978jOzsbCoUCs2bNwqlTp0T3b926FePHj4dCocD48eOxa9cut9tDgotcLsfcuXMxc+ZMpKam9niOkL8DHwCiLTRshAEZx3GIjIxEbm4uCgoK+DYPhsBHWL26p79dQggJBi4HPiUlJUhJSUFqaio4jkNqaqroKzk5GZMmTcLtt9/udiOee+45bNy4EXv27EFZWRnq6uqcJkl/9NFHeP7557F+/XqcO3cOkydPxkUXXcRPH1RUVODyyy/H6tWroVarsWTJEixevBitra1ut4kEF5VKhdjY2B5r89gHPsJd3f0lKirKIfHalYKEERER/LYbjY2NsFgsPmmfLwmnI4VTjoQQEmw45sar1I4dO2A2mzF//nxs2bJFdJ9EIkFaWlqP02A9sVgsSEpKwoYNGzBz5kwAwPHjxzFhwgS0tLSIPg0XFRXhgQcewPXXX88/dvjw4Xj22WdxxRVX4P7774dGo8Ebb7zBP2bSpEm49dZbcdddd7nUHo1Gg6ioKLS3t4t+Nglue/fuRWNjI3974cKFAamC3NXVhX379qG9vR0cx2H+/PlQKpV9Pu7AgQOora0FAEydOhWJiYm+bqpX7d+/n1/0IJFIcPHFFwe4RYSQocbV92+35gNmz54NAHjiiSfwm9/8pn8t/J9jx47BYDBg+vTp/LHRo0cjJiYGBw4cwLx58/jjZ86cwciRI/nbEokEU6dOxf79+3HFFVdg8+bNePTRR0XXnz9/Pvbu3ety4EMGJmGQk5CQELCtH8LCwjBz5kzU1tZCqVS6FPQAQFpaGh/4nDt3bsAFPsKkbcYYGGM+r5xNCCGe8CjH54knnsCZM2fw9NNP44477uCPnzt3zukeRb0pLy9HZmamw8qdrKwsfuNJm5SUFJw+fVp0rKmpiV9FU15e7pBn4ew6QgaDARqNRvRFBp7MzExwHAe5XI5x48YFtC1SqRQZGRkOhRZ7k5iYyC8Dr6+vF9X6GQiEOT6MMb6AIyGEBBuPAp+vvvoKM2bMQGVlJd58803++PPPP9/nzu32dDodVCqVw/GwsDDRiykA3HbbbXjsscewf/9+aLVavPLKK9i9ezefyOrsWs6uI7RmzRpERUXxXxkZGW61nwSHuLg4nHfeeZg/f35A8nv6SyKR8Pt0mUwmUb2fYMcYc/jAY7/7PCGEBAuPAp/HHnsMn332Gd58801RIuNdd92FL774wq1ryWQypxs6GgwGh2mCBx54ADfeeCMuu+wypKam4sCBA7j44ov5aQFn13J2HaGHH34Y7e3t/Fd1dbVb7SfBQ6FQBGQ1l7cIl8P3NkoZbEwmk8MIFQU+hJBg5VHgU1paimnTpgEQF5NLSkpyqOrcl7S0NNTU1Dgcr66uRk5OjuiYVCrFk08+iZqaGmi1Wrz11luorKzka7s4u5az6wjJ5XJERkaKvggJhLi4OH57jsbGxgEzXeRsepsCH0JIsPIo8Bk1ahS2b9/ucPyLL75AVlaWW9cqKiqCTqcTFT07deoUOjo6MHHixF4fe/jwYZSUlPDbZMycORObNm0SnbNp0ybMnz/frTYREgi2MhGAdcWiux8iAsXZVDIFPoSQYOVR4PPCCy/g1ltvxYsvvggAWL9+Pe6++24sW7YMq1evdutaSqUSS5cuxYoVK1BbW4v6+nosX74c9957Lzo6OjB79myUlpYCAE6ePInS0lIYDAbs2rUL11xzDdatW8fndCxfvhxvvvkmfvrpJ+j1erz44otQq9W44oorPHmahPjdQJzuosCHEDKQeBT4zJ49G7t27cLp06dRVFSENWvWoLGxEVu2bMG1117r9vXWrVuH/Px8FBQUYPTo0Zg0aRIef/xxdHZ24uTJk/w+RiUlJZg9ezYiIyNxxx134LHHHsOtt97KX2fKlCl49dVXcdtttyEmJgbffPMNvv32W9o0kQwYUVFRfIJ+S0tLr4n5wcLZVFdnZ2cAWkIIIX1zq4AhYF3B8dRTT+Huu+922CV7MKAChiTQTp8+jZKSEgBATEwMJk+eHNQ7tp84cQLl5eWiY6GhoVi4cCHV8iGE+I2r799uj/hwHIcXXnjBoe4OIcQ7MjMz+dVparUaJ0+eDHCLetfe3s5/b9uVvbu7e8AkZxNChhaPopc1a9bg0UcfpeFsQnxAqVSKKpl3dHQEsDW9s1gsaGtrA2Btd2xsLH+fs3YzxnD27FlUVFTQnl6EkIDwqOjJv//9b9TU1OCdd95Bbm6uQ9FA2hGdkP6Jjo5GSEgITCYTTCZToJvTI41Gw9fwiY2NRXh4OH9fR0cHYmJiROe3traKVnD2VmqCEEJ8waPA58477/R2OwghdkJDQ2EymZwW+LSn0+lw9uxZpKamOgQbvtTa2sp/HxMTw9chApyP+Ni2lwGsmxFnZ2dTHhAhxK88CnxuueUWb7eDEGInNDQUXV1dLo342LZxqa6uxoUXXuiH1lmp1Wr++9jYWFEQ4yzwsQ/impqaBtyGrISQgW3g1vcnZJCzlWEwm80wm82QSqVOz2OMQavVArAmFZtMJr9s3cEY40d8QkJCEBERAYvFAo7jwBhDU1MTfvnlF/58iUSC+vp60TVqamoo8CGE+BUFPoQEKWH9KZPJ1GPgY1/rx2Aw+CXw0ev1/M+OiYkBx3GQSqUICwtDZ2cnjEZjn5utBnPiNiFkcKI16YQEKWHgYzQaUVxcjGPHjjksE9fpdKLbzgoK9sVgMODw4cMO9Xh6Y5/fY5OTk+Ny3g5VeCaE+Fu/PhbW1NSgqqoKM2bM8FZ7CCH/Iwx86urqcObMGQDWqshTpkzhgwtvBD7Hjx9HbW0tACA+Pt6l4p3C/B5h4JObm4vMzEzRju01NTVO6xEZDAZYLBaqC0YI8RuPXm3OnTuHWbNmIT8/H3PmzOGP/+lPf8IXX3zhtcYRMpQJp6uEq6EaGxtRUVHB37bl99h4EvjYgh5AXJCwNz0FPoC17XK5nP/qLY+HRn0IIf7kUeCzfPlyTJ8+HVqtFhaLhT++aNEirFmzxmuNI2QoE474CKeVAODUqVN84UBvjPgIuTJNZTKZ+AApIiKiz/3whPV9AIi24KDAhxDiTx4FPtu3b8eqVasQEhIiepGcNGkSPxxPCOmf3oIJi8WCgwcPwmQy9TvwsV8u70rdoPb2dr7ysrBac084jhMFP3Fxcfz3FPgQQvzJo8AnLCyM3zFdqKSkhHZCJ8RLnP0tRUZGIjo6GoB1RdS+ffscAh13Ax/7wMmVwKenxObeTJw4EREREUhPT0dqaip/nAIfQog/eRT43HnnnbjjjjtEwc/hw4dx66234uqrr/Za4wgZypwFPtHR0Zg4cSKf/+PsA4i7gY99jpArgU9v+T09iYyMxNy5czFhwgQolUr+OAU+hBB/8ijwefzxx7FgwQIMHz4cjDGoVCpMnToV06dPx/PPP+/tNhIyJPU04qNUKjF27FjR8ZCQEH5lVH9HfPp6PGOMD3xkMpnDXn2uCAsL47+nwIcQ4k8eryF96KGHUF9fj2PHjmH37t1oaWnBP/7xD9ELGiHEcz0FPgCQlpaGzMxM/nh6ejofgBgMBrd2PrcPfOrr67Fp0yacPn3aoWYQYJ1is40K2QoXuis0NJQvyEiBj/c0NDRg7969olWAhBAxjwKfgoICPPPMM2hubsaoUaMwduxYh1UbhJD+sQ98JBIJn98DAKNGjUJGRgaSk5NRUFDAr5SybXHhKvvAB7DWCiopKcGmTZtQUlIiSoDWaDT8955uiMpxHD/d1dnZ6VZ7iXM6nQ779+9HY2Mjjh07FujmEBK0PAp8/vKXv2D//v0oKCjAhRdeiE8++cSlvABCiOvst6iIiYkRHQsJCcH48eMxefJkyGQy0RJxV6e7GGO9jrh0d3fj9OnT2LJlC7+9hPBvvT8jvLbVYBaLBS0tLR5fh1j/H48ePcqXFxGOyhFCxDwKfK666ip89tlnqKurww033ID33nsPmZmZuOuuu7Bv3z5vt5GQIcl+Cik+Pr7X84VBSGNjo0s/w2Aw9DjaEhkZybdBr9fj3LlzAMSBj0wmc+nnOJOQkMB/T1Mz/VNVVeUQPNonrRNCrPpVJz48PBw33XQTvvnmG3zxxRc4dOgQpk2b5q22EUIEhLVvnElLS+O/LysrExUX7UlnZ2eP940ZMwbTp0/nb9umxISjSf0JfOLj4/nAigIfz+n1epw6dcrhuHBKkhDyq34FPidOnMCf//xnjB07FpdffjkmTZqEn3/+2VttI2TIEwY7feXTREZGIikpCYA1YbimpqbP6/cW+ISHh4uSl7VaLcxms9dGfEJDQ/mcJa1WS0nOHjp+/DifhB4VFcUfp8CHEOc8Xs5eWFiI6dOno7i4GGvXrsW5c+fw97//nUZ8CPGi0aNHIz09HVOnTnVpI8/8/Hz++9LS0j5XdwmDDWFtHcAa1EgkEn61mEajwbfffiva16s/gQ8gnu5yVpOI9K6+vh51dXUArP8XkydP5gNVCnwIcc6jwOfgwYN47LHHUF9fj/fffx+LFi1ySMQkhPRfZGQkJkyY0Osmn0IxMTF8LlBHR4coSHFGOOLTUz2enlZsSiSSfv/dU56P50wmk2j11qhRoxAWFsYHsFqtlhKcCXHCo8Bn48aNuP766x0+IRJCAk846lNSUgLGGMxms9OaPMLAR7gbvFBERITT4zKZzKMaPkIxMTH8z21qanKr/tBQd+rUKej1egBAYmIin+Nlmz40m83YsWNHvzetJWSwcf5KZ+c3v/kNtm3bxt+ePn16ry94u3bt6n/LCCEeiYuLQ0xMDNRqNbRaLSorK/laPDNnzhTlgdgCn9DQUOTm5vLTJqNHj+bP6WnER7h83lMcxyEhIQF1dXUwGo1ob28X1SoizrW2tuLs2bMArGUPxowZw78mDx8+HM3NzTAYDOjs7ER5eTlGjhwZyOYSElRcCnweeOAB0e0777zTJ40hhPQfx3HIz8/HL7/8AsCa/GpTVVWFMWPGALDWz7Hl+CiVSsTExGDs2LEwmUzIzs7mH9NT4NPf/B4bW+ADWEd9KPCx1uXp6cOlrWaPbXRsxIgRotH38PBwzJo1C1u2bIHFYkFVVRWGDx9O6QiE/I9Lgc8ll1wiun3LLbf4pDGEEO9ITExEVFQU2tvbRceF010NDQ38m2d4eDg4jkNWVpbDtSIiIhAaGuowVebNwMemqalJNFU3FJWVlaGkpASZmZkYOXKkQwBUX1/P1+iJjo5GTk6OwzWUSiVSU1NRU1MDo9GI2tpaZGRk+KX9hAQ7j3J8evrk0NLSIqolQggJDI7jMGrUqF7Pqaio4L/v7U1RKpViypQpDn/b3gp8lEoln1jd2toq2h5jKCovL0d3dzfKyspw8uRJh7wn4f/biBEjehwZEo7aVVRUUP4UIf/jVuBjNBr5DRC7u7thNBr5L71ej127dvVaF4QQ4j9xcXGiNz/g1+KDGo2Gr/QbHh7eZ1Xo2NhYhx3hvRX4AL+O+jDGhvT2FYwxUTJyeXk5zpw5w9925/8tOjqanzZsb2+HWq32TaMJGWBcDnzKy8uhUCigVCrBcRwUCgXCwsL4L5VKhd/97ndYtWqVL9tLCHHD6NGjMW7cOP62bXmzcNQgJyfHpdVZ9qu+fBH4ANYpuKGqu7vbYWSmpKQEJSUlACAKCrOysnr9f+M4TjQNJvw/tzGZTDQSRIYcl3J8ACA3Nxdnz56F2WxGbm6uwx+RRCJBYmKiV1Z6EEK8g+M4ZGZm4syZM9Dr9fwIrW3frZCQEKSnp3t07Z6Wv3siPj4eUqkUZrMZ586dQ2FhoVevP1AI6+4oFAp+ufrp06ehUChEo0E9JZ0LpaSk4OTJkzAYDKirq4Ner4dCoQAA1NbW4uDBg4iNje1zpS4hg4lbU10ZGRnIzs7GO++8g6ysLNFXRkYGBT2EBCnb6IzRaERVVRW/MWlmZmZQBBghISF8DpHJZHJpu43BSBj4pKamipahnzhxQpSs7srrrVQqRWZmJgDrNJptCTwAHDhwgJ9abG1t9UbzCRkQPHrFu+WWW1BVVYWDBw86LYt+880397thhBDvsQU+FosFpaWlAKyjQfY5QH0ZO3Ysjh49ipCQEJerSbsqJycHVVVVAIDKykq32zZQdHd3QyqVOt2CxH4ftGHDhkGn06G6uhrd3d1obGzk77eN3PQlKyuL377k7NmzyM/P50eSbJqamvrcBJeQwcKjwOftt9/GsmXLMGzYMBQXF2PixIkoKysDYwyFhYUU+BASZIT5OLZl6QkJCT1uU9GTzMxMflsEb+b4ANbtOWJjY9Ha2gqtVgu1Wo2IiIigGJHylrq6Ohw4cADh4eGYMWOGQx862wC2sLAQ9fX1onICHMe53P9hYWFITk5GXV0dDAYDNBqNwwhPY2MjRowY4enTImRA8Wg5+9NPP43//Oc/OHHiBBISErB161bU1tbiqquuwk033eTtNhJC+snZtIiz+i994TgOiYmJLuWXeCIlJYX/fufOnfjhhx/4mjWDQXV1NRhj0Gq1OHTokENisbPARyaTITIyUnSeu9uFCEdz1Go1XzDSpr29nba2IEOGR4FPU1MT5s6dCwAYNmwYysrKEBoair/85S9YvXq1F5tHCPEG+9EBhUIhWkkVLJKTk0W3LRYLn4g9GOh0Ov77xsZGfrWWjbPAB4DDvoju5lPGxMTw3zc3Nztd2k6bxJKhwqPAZ8SIEThy5AgAYNKkSdiyZQsA61JLquNDSPCxD3xiY2ODchWPUql02BTVvvq02WwWBRADhdlsdnh9LC4uFgUcwlEXbwY+kZGRfE5RfX09P9Ik3LdNmD+k1+tpBIgMWh4FPvfffz++/PJLAMAf/vAHPP7447j00ksxf/58XH311V5tICGk/+wDn2DeD2vYsGGi28Igx2KxYMeOHdiyZYvTujTBrKOjgw84QkNDAVhXWh06dIhPNhaO+AiDm/4GPhKJxGG6DLD2ta0tTU1NYIxBo9Hgp59+wk8//UQfZMmg5FHgc+2112Lt2rUArIl3e/fuxbx587Bu3Tq8+uqrXm0gIaT/BlLgk56ejrlz5/J5RJ2dnXxib1tbG5/zI9x8NVh0dHT0OBolPJ6Xl8evijMYDDh27BiAXwMfjuP4gASwJigLeVI6RDjdZRMfH89XfzYajWhra8OxY8fAGIPFYnGYiiNkMPDKconhw4dj+PDh3rgUIcQHBlLgA1g3Ro2Pj+eDBY1Gg7i4OHR0dAS4ZT1rbm7Gnj17AFg/EObm5vL3GY1GVFdX87cjIiKQlZWFLVu2wGg0orm5mT8PsI4ICaci+zviA1g3rhWOkkVGRkImkyExMZFPdm5sbBQlkw/1fdPI4ORS4HPddde5lQ/w4YcfetwgQoj32b9R9rTRcDARTs1otVrExcU51A1jjAVFrpLZbMaRI0f4qawTJ07AaDSioKAAFosF27ZtE9XOCQ8Ph0wmQ0REBFpaWmAymdDW1sZPLTlLRhfyJPBJSEhAQUEBiouLwRjjV9AJk9wbGxtFwc5A+D0Z6hhjfEVu+78Fk8mEM2fOQKFQIC8vL0AtDD4uBT5U34GQgU0mkyEuLg4tLS0YM2ZMoJvjEmHgU11djZSUFIfAx2AwuFzIz5fKy8sd8mFKSkpgNBqRlpYmCno4juNHcIRt37FjB/+9feBj/4bmSQ0ljuMwfPhwJCYmQqfTITU1FYB1Gi0yMhIajQbt7e2iJfa2Ct8kOFksFuzduxfNzc0YMWIE8vPzRfdXVlaivLwcgDWRva/NiIcKlwKfJ554wtftIIT4EMdxmD59OoxG44DZWiYyMhJyuRwGgwFtbW3Yvn27w9RLV1dXUAQ+wpVZthIftkrJwm0iAGtejW2FVU9t7yuw6c9IjHDXdpuEhARoNBqHukK0siu4lZeX89OkpaWlDoHPqVOn+O+rq6sp8Pkfj5KbbRsd9vRFCAk+HMcNmKAHsL65T5kyhQ8O9Hq908BHSKvVYseOHTh8+LCo0rEvMcbQ1tYGwJqLM3LkSEyYMMHplhQ5OTkoKirib/cU+MTGxjocs428y+Vyr+do9bT9CL2eBy+9Xo/i4mL+tslkctiKRFj1nP4vf+VRcrOzuUQhGh4lhHhDdHQ05syZgwMHDqClpcXhfvvppTNnzqCtrQ1tbW1oaWnBnDlzRKujfEGr1fKvebaAJC0tDQaDASdOnBCdO2LECNGbkf1qLQAoKirip6GE8vLyEBkZiYiICK/n3sTGxiIkJMQhsKQRn+BVW1vr8F6rVqv53C370TvbNGYw5MQFmkcjPhUVFSgvL+e/SktL8f3332P+/Pl4//33vd1GQsgQJpfLMX36dKfJmcIRH7PZLCrC19nZKVpJ5SvCKsjCJeP2VahVKpXDvmPOkpbT0tKcvjlJJBIkJSU5rPDyBolEgvT0dIfjRqMRFovF6z+P9F99fb3DMdvII2D9vxMGsgaDwWFEaKjyaMQnKyvL4VhOTg6mT5+OCy+8ENddd12/G0YIITYcx6GwsBDp6eno7OzEvn37AIgDn8bGRodPwMI3Am/SaDQ4evQoAHHwIpyCUiqV4DiO/+TtbHTHPvBxd9NYb8rPz0dlZaXDcaPRGBR5VORXBoOB32hWOFInDMKd1ZNSq9VOfw+HGo9GfHoSHh7OJ1oRQoi3RUZGIikpic+fEU51OfsEbL/dhTfU1NRg586dUKvVog0/OY4TbQEBiEeAnAUP9jlXvhjNcZVCoXBIjgVouivYWCwWnDp1ig+os7Oz+WCmra2NP+6s5tXx48cdVkYORV5Jbtbr9Th79iweeughj7LGLRYLVq1aheTkZISHh+OGG27ocUfmd955ByNHjoRKpcLkyZOxc+dO0f3r169HQUEBFAoFZs2ahdOnT3vyFAkhQYrjOP6Fvquri68y3NDQAMD6Cdi2FL6jo8NrRfgsFguOHz+OQ4cOOc1jjIqKcsi9GT16NDiOA8dxooKGNvYJ0IEc8QGAgoICzJgxQzSq70lSrFqtRnV1NeV7+kBxcTE/hctxHNLS0vgA22w28++dzkZ8DAYDdu3axY8WDVUeBT4KhQJhYWH8l0qlQk5ODnbu3Ik333zT7es999xz2LhxI/bs2YOysjLU1dVh5cqVDud98803eOihh/DWW2+hsbERN954IxYvXsxHsLt378ayZcvw5ptvoqWlBdOmTcPixYup+ighg4wtQDCZTDAajWhpaeFXcSUlJfFvBLa9p/qLMYa9e/eKKh/bBy22pFKhqKgozJs3D/PmzXMYDXImkCM+gPWNNC4uTrRRrLsjPgaDAbt378bhw4edTp2R/rEF+BzHYdy4cYiMjBSNLNqmu4SBz5w5c/hzuru7sWfPHv46Q5FXkpsrKyvR2dmJn3/+2e1ihxaLBevWrcNLL72E7OxsJCUl4aWXXsIHH3zg8IL1ww8/4Oqrr8aMGTOgUqlw9913w2Qy8Uv6nnvuOdx7772YPXs2VCoVnnnmGeh0Ovz444+ePE1CSJASjox0dHTw002ANQARBhnemO7q6urip/ElEgnGjRvnkOton8wsbKurIznBUm5A2A53A5+amhp+pOfkyZNebddQxxjjp7BUKhUyMjIAiHPL1Go1DAYDX1tKJpMhMjIS06ZN46t0m81mHDhwYMgmO3sU+GRlZYm+MjIyPE5+O3bsGAwGA6ZPn84fGz16NGJiYnDgwAHRucOGDcMvv/zC/1EdPnwYEomEn5fesmULFi5cyJ8fEhKCOXPmYO/evR61jRASnISBhE6n4/N7pFIpEhISvB74CN/8MzMzkZmZ6VD7xrapqrvGjx8PwPqc4uLiPG6jN/Un8Bmqb6be1NnZCbVaDYvFgsbGRv7/wGAw8O9/wr+BqKgofgSyra0NVVVV/Gq8zMxMcByHkJAQTJkyBUlJSQCswc9QnfLyaFWXxWLBJ598gj179qC5udmhXoA7e3WVl5cjMzPTYdg4KysL586dEx2744478MMPP+DCCy/EJZdcghdeeAHvvPMOoqKi+ETD7OzsPq8jZDAYRH/YlPhFSPATvuifO3eO/xtOSEhASEiI6H5vvBELiyHaqirHxcUhPDwcOp0OY8eO9fjaGRkZiI2NhUKhcFr0MBCEgY99kqxWq0VtbS3S09OdjmQJp1iC5fkMJAaDAdu2bROlaCgUCsyePVv0fyHse6lUisjISLS1tUGr1aK0tBSAdTpMODIpkUiQmprKT3MN1SDVo8Bn2bJl2LBhAy677DIMGzasX7/cOp3O6R9PWFiYw3+KQqHAH/7wB6xcuRL19fXIz8/H5MmT+esAjsmBYWFhomFwe2vWrMGTTz7pcfsJIf4nzIURriS1TTeFhIRAIpHAYrF4ZVWSMMHXFvhIpVLMmTMHer2+30nJgU5qtqdSqRAaGoru7m6o1Wq+8J3FYsHu3bthMBjQ0tKCGTNmiB7HGBONsNmW81PRPNc1NTU55KXq9XocPHgQaWlp/DH7fLCYmBi+fIPt8fHx8Q7nCZez21c+Hyo8CnzWr1+P7du3Y/To0f1ugEwmc7pqwGAwOPyH/fOf/8TLL7+MAwcOIDk5GX/7298wbdo0HD16lH8xMhqNov9YZ9cRevjhh3HffffxtzUaDT9vSggJTvY1cgDrm6xtGJ/jOMhkMuj1eq+U6hdeQ1gJWiqVBl3Q4g0cxyEmJoafZuns7IRKpUJ9fT0fSDqrpK3X60WBptlshtlsdijcSHrW04rmlpYW0Wia/e+ds21MnB2jwMfDHJ+oqCg+Saq/0tLSUFNT43C8uroaOTk5omN/+ctf8Oyzz/Kf6u655x7k5OTgww8/RHx8PGQymcO1nF1HSC6XIzIyUvRFCAluEonEoRBbXFycaHNP23SNwWBwmI53l7OprsFOuF9Yc3MzWlpa+CkUG2fbItgbqtMpnrJPt5DJZPyImTCotA98hCu7bJytJBRuOeVq4NPQ0IAjR444XSI/EHkU+DzzzDO49tpre6xn4Y6ioiLodDq+Cipg3VG2o6MDEydOFJ3b3t7ukEAYGxsLo9EIqVSKadOmYdOmTfx9ZrMZ27Ztw/z58/vVRkJI8LF/4bff38oW+DDG+l3SwtlU12AnDHyOHj2KXbt2OQQ29v3q7EMsBT7uEQY+U6ZMwfnnn4+RI0eKzhHWsrJRKpUOv5vOAh+JRML/bbgS+Oj1evzyyy+oqqoaNKv0PAp8Zs2aBZ1Oh0mTJkEmk0EqlUIqlUIikbi9eZ5SqcTSpUuxYsUK1NbWor6+HsuXL8e9996Ljo4OzJ49m/+Ucckll+Dhhx/GmTNn0NHRgffffx9bt27FxRdfDABYuXIl1qxZgwMHDqCjowMPPfQQ8vPzMXXqVE+eJiEkiAmH8VNTU5GZmSm6X/gm0N88H+GIj683PQ0W0dHRfeZvCgPCzs5Op9WzqfKz64T7acXFxfFVynNzc0XlEpRKpcP/DcdxDlNbPW1PYTtuMBhgsVjQ0dGBbdu2Ye/evQ7BrLB21WCp/ePRxOt1112HuLg4/Pe//0Vqamq/E9fWrVuHFStWoKCgAHK5HLfeeisef/xx1NfX4+TJk2hubsawYcPwyiuv4MEHH8Ts2bNhNBoxbtw4fPXVV3w0fNVVV+Hs2bN8UcMLL7wQn376ab/aRggJTnl5eeA4DuHh4U5fh+wDH0+XmwNDc8RHKpUiNzcXZWVlkMvliI+PR0JCAurr6/kFI0ajkR95q6io4Ke+IiIi+FwVGvFxnTC/R5h2wXEcxo8fj507d0Kn0/G5bPbs81l7em8OCwvjCx12dXWhuroaGo0GGo0GpaWlfD0+k8mEs2fPih5rsVgG/Go9jwKfAwcOoKqqyms1J8LCwvDWW2/hrbfeEh1PS0sTJdBFRETgtddew2uvvdbjte6//37cf//9XmkXISR4hYaGoqCgoMf7hUuy+5vgbBvxsdVDGSpGjhyJgoICftsNwDqyIwx8AOsbZFVVFQBrwFRQUID9+/cDoBEfdwinuezzTUNDQzFnzhy0t7c7TVoGrFXLbdWy7Uu7CNknOAuXyZeVlSEjIwMqlQqtra2i0U7b+QM9od+jsG3OnDn8XiGEEBKMvBn42B4fGho65JZmSyQS0XMWjnjZ+qWqqoqfIklPTxdteUEjPq4T/p46m6aSSqWIjY3tccQlISEBeXl5SElJwfDhw3v8OcJr6/V60Wa/FouFz+VxlszsbPPTgcajjy7XX389br75ZixZsgQjRoxw+AR0wQUXeKVxhBDiKW/m+NjekIbKNFdv7AMfxpgoDyQnJ0dUyd9W5NY+YKT6Po6Ei4XczZcFrCOShYWFfZ4n/P/R6XQOSc719fVobGwUBUQ2zo4NNB4FPqtWrQIA/P3vf3e4j+M4lJeX969VhBDST/3ZdkHIYrHwoxlDJbG5N/aBT319Pf9mmJiYyI/2hISEwGQywWAw4ODBgygqKhIto969ezdCQkIwffp06tf/sW0zAXgW+LgqOjqar4N19uxZPrCXSqV88HXixAmnW1EN2cBHGN0TQkgwcjYl44mhWMOnN/b9WlZWxt/Ozc3lv8/OzuZX5NbW1mLYsGH88urS0lJ+yqSkpMSlUYqhQDji48sE4rCwMCQmJqKhoUH0t5GSkoLOzk60trZCp9M5neoaDIHPwE7NJoSQHnhrqqunqs1DlbBfGxoa+NVBkZGRiI+P5+8bOXKkqHisbbdwAKLNMRsbG33Z3AGlv1Nd7nBW2FepVGL06NEOU5ARERGi5PaBzuPl7L3NzbqzSSkhhPhCSEgIP91CIz7e01NAmZub6/C+kJOTw88QNDY2YtiwYQDEASQlP//Kn4FPfHw8VCqVKFk5LCwMUVFRDjsqhIeHw2w2o7OzEx0dHTAajQP6b8GjEZ8RI0agoKCA/8rPz4dEIsG3334r2kSNEEICSbiHn6eGYg2f3kgkEocFLXK53KFyNmCtrm1b+tza2srnSgmTabu7uyn4+R9/5fgA1nxc+/drWx0g+/0qVSoVv4TeZDLhwIEDorYONB6N+DzxxBNOj+/du9dpwjMhhASCbWTBvhaJO4RD+xT4WMlkMlGF3+zs7B7fqBMTE/nihhUVFcjLy3NYRaRWq5GSkuLTNg8E/hzxAaylB4qLi/nbtsDHvkafXC5HVlYWWlpaYDAY0NzcjOPHj2PMmDGifcS6u7v7VSjUX7ya4zN16lQcO3bMm5ckhBCP2UYmLBaLx/sKCnNTnG0EORTZv0H3ViwvPT2df3M8c+YMampqHDY3Feb8DGW2fhUWjPQllUrFF0oMDQ3lV3FxHCdKVI+NjYVSqcTkyZP5pOuzZ8/y05gGgwGbN2/Gli1bRH8vwcqrgc+xY8cGReITIWRwEE7JeLJRqdls5qvHKxQKUWG+oUz4ppyZmdnrSFh0dDTy8/MBWGv3CDektnG2q/tQZAt8/DHaYzNp0iRkZWWhqKhItJJsxIgRyMvLw+jRo/lprpiYGIwbN44/5+TJk2hqakJ5eTn/9+Xs/zfYeCW52WKxoKGhAXv27MH//d//ea1xhBDSH8IkWpPJJKrt44rW1lb+zSghIYEK7v1PdnY2Tp8+Dblc3uu2ITbDhw+HWq1GU1OTw2gPYA18qKDhrzk+/gx8VCoVxo4d63BcKpU6LTOQnp4OnU6HkpISMMZQWloqqvczELYo8SjwsW1gZiORSDBv3jy8+uqrDvcRQkigCEd8PMnzEQ7bJyYmeqVNg8GwYcMQExOD8PBwl5b4cxyHCRMmYPv27aJEZlvBPJPJhM7OzgG/B1R/BWLExxMFBQWoqqqCwWCATqcT/Q4Ee9sBLyc3E0JIMOnvVJcwCbenjSGHIo7jRDV7XCGXyzFx4kTs2rWLH/VJSUnhl023t7dT4DNAAh+O46BSqWAwGKDX60VL4oO97YAbOT7//ve/8e233/Z6zvr16/Hjjz/2u1GEEOIN9lNdvXE2BSN8DBUv7L/Y2FiMGTMGUqkUSUlJoiXwlOczcAIf4NcVYIB4V3lPPmD4m8uBz1NPPdXnJ57IyEj85S9/6W+bCCHEK1yd6qqsrMSPP/6IM2fOiI4LH2Nfu4Z4JisrCwsXLsSUKVP4LSwACnwsFgsffPtyuwpv6Wl0rru72+MVlP7icu+eO3fOaQKU0MSJE/nt7AkhJNBcneoqKSmB0WhEcXExqqur+eO2wCckJGTIJ956k21EQy6X8yvCtFptIJsUcP6u4dNfvU1LBnuCs8uBj0wm6/MPPzIycsj/8hJCgocrU11ms1mUcHvs2DF+6N4W+NA0l2/YckUA69YVwT5S4Ev+rNrsDb0FPsFeidvlwGfcuHHYsWNHr+ccOXLEodQ1IYQEiitTXfa1x8xmM/bv3w+TycQHSxT4+I4wV8S+ovNQQiM+/uNy4LNs2TI89NBDouxtIbPZjMceewxXX3211xpHCCH94cpUl/A1zTaq3dHRgUOHDvFvRhT4+I4w8Onp/WUoEAY+AyHHp7e/CeGIj1arRV1dXVCN5rncu9deey2mTZuGyZMn46uvvhJFdLt378b555+P+vp6PPzwwz5pKCGEuMuVqS7hiM/w4cP5x9TX1/PHKbHZd4QjB0O58v9AG/EBrKv0bJKSkvjvOzs7UV1djZ9//hlbt27F/v37ceLEiUA00Sm3wsrXX38d999/P+69915EREQgMTERSqUS5513HoYPH44dO3YMiA3KCCFDg7tTXfHx8Rg/frzDOTTi4zvCER8KfKwGSuAzYsQIxMTEoLCwUFS8uLy8HIcPHxbtwdbY2BiIJjrl9seYpUuXYunSpaioqEB9fT2USiVGjhxJuxYTQoKOK1NdwjdbpVKJmJgYcBwnqutDIz6+Q4GP1UBLbgasu7jPmjULQM95Pba/pa6uLuj1etH2FoHi8V9zTk4OcnJyvNkWQgjxKolEwm+L0NOIjy2vRCqVQi6Xg+M4yOVyUZ4Cjfj4jkKhgEQigcVioRyf/xkIOT72ZDIZwsPDodPpIJVKkZaWhszMTNTX16O0tBQA0NbWhuTk5AC3tB+BDyGEDAQhISH8flD2GGP8KINSqeSTmxUKBQU+fsJxHJRKJXQ6HTo7O4fsZqUDcapLiOM4zJw5E21tbYiJieH/ZoR/R8ES+Ay8sJIQQtxgewF2FvgYDAZ+ikE45WK/iztNdfmWre/NZvOQreA80AMfwDrqk5iYKPqgINzxoa2tzf+NcoICH0LIoGYLWkwmk8N+XMLpL2Geon0eAo34+JZwFKC8vDyALQmcgZjj4wqFQsF/kGhra3O6J56/UeBDCBnUbIEPY8yhlogw8BEGNxT4+Fd6ejofeNbW1g7JQoaDYcTHGY7jEBMTA8D691ZVVRXwmj4U+BBCBrXeavkIbwuns+wDH5rq8i2pVIrs7GwA1gC1oqLCrccbjUbs2bMH+/fvF42cDCSDNfABrKu/bI4ePYpNmza5/X/sTRT4EEIGNWHgY7+HEI34BI/s7Gx+NVNVVVWvm8raO3HiBJqamlBXV4dz5875qok+NdBXdfUmPj5edNtgMAQ0l2tw9S4hhNiJioriv29qahLd19OIj31yMwU+vieXy5Geng7g1ykRV9XU1PDfD9Tk6MGa4wMAERERopV6HMdh+PDhAWsPBT6EkEEtMTGR/96+eqww8OltxIemuvwjNzeX//7EiRPYunUrTp8+3etj7JNlB2rQMJinuoR5PoA1mV24itLfKPAhhAxqSqWS30pHrVaLpreE3wuDG/tK9IPtjShY2bZCstFqtSgpKel1t2/7ROhg3xm8J4M58AGA/Px8ANaRvcLCwoC2hQIfQsigZ3szZYyhubmZP97TiM9QLKAXLISjPja9VXS2rw1jn8c1UAzmHB/A+je4YMEC/OY3vwnoaA9AgQ8hZAhISEjgvxdOd/U04gMAEydORFRUFCZMmOD7BhJefHy8aBUQ0PseXvaBz0Ad8RH+Lg7GER/AOvpqnz8XCDRxTQgZ9OLi4vg9uxobG2GxWFBfXw+1Ws2fY5/AnJqaitTUVH83dcjjOA5TpkzBmTNn+GKGvdX10Wq1otsDbcSHMYbi4mJ+JDIkJIRyynyMRnwIIYOeVCrlRxH0ej2OHDmCAwcOiKZQ6M0meISEhPArvIDeR3yMRqPD7YFSy4cxhuPHj6O4uJg/Nnz48EE51RVMqHcJIUOCMGlWuPwZsOZU0JtNcBHmgbgT+AADY7qLMYZDhw6hsrKSPzZq1Cjk5eUFrlFDBP2lE0KGBGHgYy8kJIQSmoOMcMpnMAY+wmKLHMdhwoQJThO7ifdR4EMIGRJUKhVUKpXT+2iaK/hwHMeP+nR1dTnd3NJsNjut8DwQ8nw0Gg3//ZgxY0RTe8S3KPAhhAwZwtVdQlSZOTjZAh/GmNNgxtloDzAwRnyEy9cjIiIC2JKhhwIfQsiQ0dN0F434BKe+8nyEgU9YWBj//UAY8RnMW1QEOwp8CCFDRlxcnNMkZhrxCU7CqUn77UYAceAjHDXpbfl7sBjslZqDGQU+hJAhIyQkBBkZGU6Pk+CTkpIi2rFdGCwA4sBHuBdUb8nQwYICn8ChwIcQMqSMGTMGCxYsEO3HNVDqvgw1crmcLyJpNBpRW1srul8Y+AirAve2xUWwGOxbVAQz6m1CyJBiWy0knN4SbhdAgktmZib/fWtrq+g+YeAjk8n4nCC9Xu8wOhRsaMQncCjwIYQMSRT4DAzh4eH89/ZJy/aBjzAnKNinuyjwCRwKfAghQ9KwYcP476labvCSyWR8cUn7ZerC2/aBT7BPd9kCH4lEQsUz/Ywy+gghQ1JycjLGjh0Ls9mMlJSUQDeH9IDjOMjlcuj1+j5HfITL34M98LHlldFoj/8FxYiPxWLBqlWrkJycjPDwcNxwww0OO+5WVlaC4zinXw899BB/3tatWzF+/HgoFAqMHz8eu3bt8vfTIYQMABzHISsrC7m5ufSJO8gpFAoA1kBHWMHZFvhIpVJIpdIBOdVFgY//BUXg89xzz2Hjxo3Ys2cPysrKUFdXh5UrV4rOyc7OBmNM9NXR0YGoqCjccsstAICKigpcfvnlWL16NdRqNZYsWYLFixc7JMQRQggZOGyrtRhjouktW+Bjmw4biFNdFPj4X8ADH4vFgnXr1uGll15CdnY2kpKS8NJLL+GDDz4Q7WXizCeffILRo0ejsLAQAPDyyy/jqquuwmWXXYawsDDcc889yM3Nxccff+yPp0IIIcQHbCM+wK8JzowxUeADWBPWbTWZKPAhPQl44HPs2DEYDAZMnz6dPzZ69GjExMTgwIEDvT72jTfewG233cbf3rx5MxYuXCg6Z/78+di7d693G00IIcRvbCM+wK8JzQaDgZ/2sgVGwlGfrq6uoK3PxBgTJTcT/wp4j5eXlyMzM9PhPz8rKwvnzp3r8XHHjx/HyZMn8bvf/U50rezsbLeuYzAYoNFoRF+EEEKCh7MRH2Gis/B+W+DDGAvarSton67ACnjgo9PpRPOyNmFhYb1uNPfGG2/g+uuvF2XxO7tWX9dZs2YNoqKi+C9n5ewJIYQEjrMRH+HrunCD0oGQ50M1fAIr4IGPTCYTLUm0MRgMoqBGSK/X47333hNNc/V0rd6uAwAPP/ww2tvb+a/q6moPngUhhBBfcWfEZyAsaafAJ7ACXscnLS0NNTU1Dserq6uRk5Pj9DHr169Hbm4uJkyY4PRa48aNc+k6gPWThPDTBCGEkODS14iPs6kuIHiXtFPgE1gBH/EpKiqCTqfD0aNH+WOnTp1CR0cHJk6c6PQx9knNNjNnzsSmTZtExzZt2oT58+d7t9GEEEL8Ri6X87WWdDqdQ/5OT4FPsI74UI5PYAU88FEqlVi6dClWrFiB2tpa1NfXY/ny5bj33nvR0dGB2bNno7S0lD//9OnTOHjwIK6//nqHay1fvhxvvvkmfvrpJ+j1erz44otQq9W44oor/PmUCCGEeJFEIkFERAQAa+Bz5syZHkd85HI5H0zQiA9xJuCBDwCsW7cO+fn5KCgowOjRozFp0iQ8/vjj6OzsxMmTJ9Hc3Myf+8Ybb+Dqq6/m/wiEpkyZgldffRW33XYbYmJi8M033+Dbb78VbUZICCFk4Bk9ejQ/6lNSUoK2tjYA1sDBVrsHsC5pt+X5dHR0iCo9BwsKfAKLY8H4WxFAGo0GUVFRaG9vR2RkZKCbQwgh5H9KS0tx6tQp0TGVSuWQzrBv3z7U19cDAM477zzRqq9g0NDQgF9++QUAMGLECOTn5we4RYODq+/fQTHiQwghhPQlLy8PSUlJomPCaS6bYF7Z1d3djbq6Ov42FTD0P+pxQgghAwLHcRg/frwosHE2mhPMCc579uwRlU2hqS7/o8CHEELIgCGTyTBx4kQ+YIiPj3c4J1iXtFssFj43yYYCH/8LeB0fQgghxB3R0dGYO3cuurq6EBsb63B/sI74dHd3OxyjwMf/KPAhhBAy4CiVyh6r8oeFhYHjODDGgmrEx9kuBRT4+B9NdRFCCBlUelrSzhhDQ0MDWlpaAtIuGvEJDhT4EEIIGXRs010mk4kfabEtI9+9ezfa29v93iZnIz60qsv/qMcJIYQMOs6WtNuCHcYYX+fHn2jEJzhQ4EMIIWTQcbaySzjiItwRwF8o8AkOFPgQQggZdJyt7BIGPm1tbaKtI/yBkpuDAwU+hBBCBh1nU13CEReLxYLW1lYwxlBdXY2Ghgaft4kCn+BAy9kJIYQMOkql0mFJu33g0dLSgu7ubhw+fBgAMGfOHERFRfmsTc6muoQbrBL/oBEfQgghg45UKuX38XI21QVY83xsQQ8AlJeX+7RNwsAnKSkJEydOpFVdAUChJiGEkEFJqVSiq6sLRqMR3d3dDiMubW1tfI0fwFr/x5dsgRfHcZg8ebLPfx5xjkJNQgghg5IwwVmr1cJkMonuFwY9/mALvGQyGQU9AUSBDyGEkEFJGPgINwftaXpJr9f7tD22EZ/Q0FCf/hzSOwp8CCGEDErCwEetVvPfJyQkOD3fl4GPxWLhR5wo8AksCnwIIYQMSuHh4fz3wuXqERERiIiIcDi/q6vLZ20R5hfJZDKf/RzSNwp8CCGEDErh4eEICwsDAFGxwtDQUMTHxzucbzKZHPKAvEUY+NCIT2BR4EMIIWRQ4jgOycnJDsdlMhni4uKcPkaj0fikLcKl9BT4BBYFPoQQQgat3gIfZyurfv75Z5SUlHi9HbYiigD4USgSGBT4EEIIGbTi4uIccmpCQ0Mhk8mc5vkAQFlZmdfbIQx8hEnXxP8o8CGEEDJocRyH3Nxc0TFbIJSXlweJROKwvL27u9ujXJ+Ojg4cPnwYdXV1Tu+zocAnsCjwIYQQMqjl5OSIbtsCn/T0dCxatAjz5s1zmPYSBiqu2rdvH6qrq3Ho0CGHnd+F1xNuoEr8jwIfQgghg1pISAgmTJgAiUSC1NRUyOVy/j6JRAKlUomJEyeKpsR0Op1bP6OzsxNarRaAdQWZ/dJ4W+ATFhZGO7IHGO3VRQghZNBLT09HWlpaj/enpKSA4zjs27cPgPuBz7lz50S3u7q6+DpC3d3d/KouGu0JPAp8CCGEDAl97Y8lLHhoG71xhclkQlVVleiYcMSH8nuCC011EUIIIbAGJbZEZ1dHfBhjOHDggGjVFiAOfGhFV3ChwIcQQgiBdUTIFpjodDrU1NT0uYN7c3MzGhsbHY4L9/1qaWnhv6fAJ/Ao8CGEEEL+JyYmBoB1JOfQoUPYt29fr5uX1tTU8N+PGTOG/9424mMwGPhpsJCQEKdbZRD/osCHEEII+Z/CwkJREnRDQwO2bNnidFTHZDLxNXtCQ0ORmZmJkBBr6qwt8CkvL4fFYgEAZGVl0XYVQYACH0IIIeR/QkNDUVRUhMmTJ/PL3k0mE86cOQPAGtCo1WowxlBfX8/X60lNTYVEIoFCoeDP6+7uRmVlJQDrsnn7QookMGhVFyGEEGInOTkZcXFx2Lx5M4xGIwwGA4xGI7Zu3QqTyYQJEyaIprnS09MBWOv06HQ6mM1mFBcX8xWgMzIy+KCIBBYFPoQQQogToaGhUCgUMBqNMBqNaGho4AOZQ4cO8cvjlUolnxsk3IC0vLwcgDVpetiwYX5uPekJTXURQgghPbBVczabzQ5JzrYVX+np6aIgyF5qaioVLgwiFPgQQgghPRBuY9HW1ub0HGEytC3XR4hGe4ILBT6EEEJID/oKfKKjo0UVn1UqFYYPH87fTk5ORmRkpE/bSNxDOT6EEEJID4SBj7N6PrakZqG8vDx0dnaio6MDo0aN8mn7iPso8CGEEEJ6IAx87HEc53TjU4lEgnHjxvmyWaQfaKqLEEII6UFvgU9aWlqv95PgRCM+hBBCSA+cBTbp6enIyMjgl7CTgYUCH0IIIaQHzgKfqKgo2nNrAKOpLkIIIaQHzgIfqskzsFHgQwghhPTAWeATGxsbgJYQb6HAhxBCCOmBVCoV3Y6MjKSE5gGOAh9CCCHERXFxcYFuAuknCnwIIYQQF1HgM/BR4EMIIYT0IiUlhf+eAp+BLygCH4vFglWrViE5ORnh4eG44YYboNVqnZ7b1dWFBx98EKmpqZDL5Q7lwNevX4+CggIoFArMmjULp0+f9sdTIIQQMkiNHDkSGRkZmDRpEuX3DAJBEfg899xz2LhxI/bs2YOysjLU1dVh5cqVTs+95pprUFpaih07dqC9vR1vvfUWf9/u3buxbNkyvPnmm2hpacG0adOwePFimEwmfz0VQgghg4xKpcL48eNFIz9k4OIYYyyQDbBYLEhKSsKGDRswc+ZMAMDx48cxYcIEtLS0iHa13bhxI/74xz/i9OnTCA0NdbjWlVdeiaKiIjz66KMAAJPJhPT0dLz99tu46KKLXGqPRqNBVFQU2tvbaUddQgghZIBw9f074CM+x44dg8FgwPTp0/ljo0ePRkxMDA4cOCA69/3338cdd9zhNOgBgC1btmDhwoX87ZCQEMyZMwd79+71TeMJIYQQMqAEPPApLy9HZmYmJBJxU7KysnDu3DnRsb179yIuLg5z586FUqnE2LFj8f333wMA1Go11Go1srOz+7yOkMFggEajEX0RQgghZHAKeOCj0+mgUqkcjoeFhUGv14uO1dbW4h//+AdWr16NhoYG3HPPPbjssstQUlICnU4HAA7XcnYdoTVr1iAqKor/ysjI8MKzIoQQQkgwCnjgI5PJYDQaHY4bDAaH/VAkEgnuvPNOzJ07FxEREbj11luxYMECfPzxx3ymvf21nF1H6OGHH0Z7ezv/VV1d7YVnRQghhJBgFPDd2dPS0lBTU+NwvLq6Gjk5OQ7nZmVliY4NGzYM9fX1iI+Ph0wmQ01NDaKiokTXGTNmTI8/Xy6XQy6X9/NZEEIIIWQgCPiIT1FREXQ6HY4ePcofO3XqFDo6OjBx4kTRuVOnTnVIVD516hSGDx8OqVSKadOmYdOmTfx9ZrMZ27Ztw/z58337JAghhBAyIAQ88FEqlVi6dClWrFiB2tpa1NfXY/ny5bj33nvR0dGB2bNno7S0FACwcuVKvPjii/j222+h0Wjw6quv4siRI7jlllv4+9esWYMDBw6go6MDDz30EPLz8zF16tRAPkVCCCGEBImABz4AsG7dOuTn56OgoACjR4/GpEmT8Pjjj6OzsxMnT55Ec3MzAOuIz0svvYQVK1YgISEB7733Hr777jtER0cDAK666io88MADWLx4MRITE1FRUYFPP/00gM+MEEIIIcEk4AUMgw0VMCSEEEIGngFTwJAQQgghxF8Cvqor2NgGwKiQISGEEDJw2N63+5rIosDHjm1XeCpkSAghhAw8Wq1WVNbGHuX42LFYLKitrUVERAQ4juv39TQaDTIyMlBdXU05Qz2gPnIf9Zl7qL/cR33mHuov93m7zxhj0Gq1SE1NddgGS4hGfOxIJBKkp6d7/bqRkZH0x9AH6iP3UZ+5h/rLfdRn7qH+cp83+6y3kR4bSm4mhBBCyJBBgQ8hhBBChgwKfHxMLpfjiSeeoP3AekF95D7qM/dQf7mP+sw91F/uC1SfUXIzIYQQQoYMGvEhhBBCyJBBgQ8hhBBChgwKfAghhBAyZFDgQwghhJAhgwIfQoIMrTfwDPUbIcQVFPgQEkSqq6thsVgC3YwBo6amBk8//TRaWlq8ssXMUEQBIxlqKPBxk8lkwqFDhwLdjKDHGMMrr7yCL7/8EidOnAAAekPvBWMMd9xxB7KysrBp06ZANyfoMcawdOlSZGZm4pVXXkFnZ2egmzQgMMbw+OOPY+3atfjss88AgALGXtDrvXsGSn9R4OOG6upqXHzxxVi0aBHq6uoC3Zyg9emnnyI5ORkffPABXnjhBVx44YU4ffo0JBIJfbp04pVXXkFUVBSKi4tx9uxZXHDBBYFuUlD7xz/+gfDwcNTU1OD48eOIjo6GTqcDQKMXvTl48CDS09OxefNmVFZWYsmSJVi1ahUqKioAUN/Zo9d79wyk/qLAxw0ffPABUlJSIJFI8MwzzwS6OUGptrYW77//Pv72t7/h559/xueff44LLrgAd911FwD6dGnv5MmTWLFiBdatW4ctW7YgIyMDAI2O2WOMQaPRICEhAevWrcOGDRvwww8/oLCwECNGjOBHyej3q2dffvklbrzxRvz888949dVX8fnnn+P06dN48cUXAVDf2aPXe/cMpP6iwMdFJ06cwK5du3D77bfjyy+/xD/+8Q8cOXIk0M0KOiqVCnfddRcuvvhiMMYQHx+P66+/HsnJyejq6qJPlXYKCwtx9dVXY8OGDfwxnU4HvV7PBz/UZ9Y35cjISLz99tuorKzE+eefDwDo7Ozk7wMoYOzNsWPHoFKp+NsLFy7E/PnzsW3bNnz//fcA6HfN5tSpU/R674aB9v5IW1b04OmnnwbHcRg2bBiuueYamM1mGAwGKJVKAMCll14KvV6PH3/8McAtDSxbP+Xn5+Pqq692es6TTz4JrVaL5557zs+tCz7O+quqqgojR47E+vXrceTIEXz88cdISEhAVFQU3nrrLURHRwe20QFk66/c3Fxcd911/PHu7m5IpVJIJBI88MADOHPmDL7++usAtjS42L9+GY1G3HjjjZg1axZuv/12KBQKAMBnn32Gm2++GZdffjnefvvtIbvP1P79+zFp0iT+tslkgtFopNf7Hgz090ca8bFTWVmJESNG4Ouvv0ZzczN+//vf45FHHkF5eTmUSiW6uroAAG+99RY2b94s+qQ+lNj305IlS/Doo4+ipKREdN5rr72GtWvXor6+HlOmTMEjjzyCxsbGALU6cJz11yOPPILi4mJkZmbij3/8IxYvXowvv/wSzz77LG655RaUl5fjzjvvRGVlZaCb73f2/bV06VI88sgjKC0tBQA+6AGAyZMnIyoqCu3t7YFsclBw9vr10EMPQa/X44ILLsBHH32E7du38+eXlJTg+uuvh1wux+7duwPY8sBoaGjAVVddhfnz56O8vJw/HhISAqVSie7ubgD0em8zaN4fGRH597//zW699Vb+9k8//cQuu+wyduedd/LHDAYDY4yxhx9+mOXn57OOjg5msViYxWLxe3sDxZV++vjjj9mkSZPYu+++y0pKSth//vMflp+fz15++WVmNpsD0eyAcdZfv/3tb/n+MhqN7JdffhE9prKykhUUFLBPP/3Ur20NBn31F2OM/x2y/Z4R5/12ySWXsLvvvpsxxtjKlStZTk4Ou/LKK1lhYSGbNGkS27ZtG5s3bx7bsmULY4wNqdexv//97+zGG29kOTk57Oabb3Z6Tnd3N2NsaL/e2wyW90ca8bFz+PBhaDQaANb57gULFuCmm25CaWkpXnvtNQDgP2n+9a9/RVtbG/72t7+B4zhwHAeTyRSwtvtTb/30yiuvAAAWLVqEffv24ZZbbkFOTg4uv/xyLF68GD/++CPfh0OFs/66+eabUVpaildffRWhoaGYPHkyGGMwm82wWCzIysrCmDFj8N133wW49f7XW3/Z/g5t+TznnXcempubB8QyWl9z1m9LlizBkSNH8P777+Oll17Cu+++i3nz5uGee+7Bvn37MGfOHERGRmLPnj0Ahk6Sc2VlJbZs2YJrr70WP/74I9577z3RaJiNVCoFMLRf720Gy/vj0Hr3cUF0dDQyMzOh1Wr5F4AFCxbg/PPPx8cff4zm5maEhITAYDAAAF588UW88MILaG1txeOPP47bb78dzc3NgXwKftFbP3366adobm5GZGQk/0bO/pdKZjabkZKSEsimB0Rv/fXJJ5/wvzOMMf6F1mw2Q6vVYvjw4fx9Q4Wrf4cAoNVqMW7cOP5vcijrqd8uvPBCvPnmm2hqasKcOXOwbNky3HbbbQAAtVqNpqYmFBUVBbLpfpeZmYl3330XF198MYYNG4ZbbrkFDzzwAMxms+g84Rv2UH29txks748U+PyP7U0lNzcXW7duhVqt5u+LiorC/PnzkZCQgE8++QQAEBoaCgC44YYbIJVKER8fj08//RT33nsv4uPj/f8E/MTdfuI4DmazGSEhIfjkk0+wZ88e3HTTTQFpeyC4218SiQQGgwESiQTr16+HTqfDpZdeCmBofBJ3t78AIDs7G6dOnUJxcbHoGkNJX/22YMECJCQk4NNPPwUA0Yjrt99+i6ioKIwdO9a/jQ4wiUSCiIgIPqh5/fXXceLECfzrX/9yONf2YWSovd7bDLb3Rwp8/sf2pnLDDTdAq9XinXfeEd0/cuRIZGRkoL6+Ht3d3ZBIJKioqMC4cePAcRy+/vprnDlzBmPGjAlE8/3GnX4ym804dOgQnnvuOUycOBH33XcfHn74YcycOTMQTQ8Id/rLZDLh7NmzeOedd1BYWIj7778ff/rTn1BYWBiIpgeEu3+HtuTTGTNm4PTp06JrDCXu9ptOp8PWrVsxZswYPPDAA1i5ciWSk5MD0fSACwkJgclkgkwmw1NPPYVHH32Uf2O3TadyHIfy8vIh93pvM+jeH/2dVBQIBoOBPfroo+z5559n//nPf5ye093dzSdLfvHFF0ylUrFTp06JznnxxRfZBRdcwBhjzGQysQ8//JCtWrXKt433I2/20/nnn88YY0yv17MNGzawN99807eNDwBf9Fd3dzfbtm0be+ONN3zb+ADwxd+hzZEjR3zT6CDgi98zs9nMDh06xF599VXfNj4AXO0vIWHibU5ODnvggQf427Z+/eijjwbV672N0Whkb731FtuxYwerqalhjDGHxSeD7f1x0Ac+GzZsYKmpqey8885jK1euZGFhYez1119nWq2WMWb9DxL+0u/evZsxxtjixYvZNddcw86cOcPf9/bbb7MbbriB/6MJpiz1/vJlPw1G1F/u8UV/mc3mQb860Bf9ZjKZ/Psk/Mjd/tq7dy/r6OhgjP0aDH3//fdMqVSyc+fOsTVr1rBrr72WNTQ0+P/J+MEbb7zBYmJi2KxZs9i4cePY3Llz+edq+/sajO+Pgzrw0Wq17OabbxYtB3711VfZ/PnzWXl5uejcjRs3stjYWHbppZcyxhirqKhgixYtYueffz776KOP2Ndff83y8/PZv//9b78+B3+gfnIP9Zd7qL88Q/3mHk/664orrmDt7e2MMfEb9fDhwxnHcSwzM5N/sx9sjh49ys4//3y2ceNGxhhj+/btY1deeSVbvny5w7mD7fdrUAc+u3fvZn/6059YQ0OD6NN0SkoK++677xhjjHV1dbGVK1ey0NBQ9vLLL4seX1lZyVatWsUWLVrE8vLy2Ouvv+7X9vsL9ZN7qL/cQ/3lGeo39/S3vxhjrK6ujs2YMYNFRUWxTz75xG9tD4Ti4mL27bffikYAX3rpJfboo48yxqyjYwaDYVD+fg2qwOfZZ59lb7zxBvvxxx8ZY4x1dHSwzs5O/n6j0cgYY+zKK69kn332GX/cdr6N/ZSDbZh0sKB+cg/1l3uovzxD/eYeb/WX8I1/w4YN7E9/+pMvmx0w9v3lbGp96dKl7MUXXxQdG4y/X4Mi8Pnmm29YZmYmmzlzJrvxxhuZXC5nH3zwAT90aT/XOHr0aIcquYw5/0UYTKif3EP95R7qL89Qv7nHl/0VzHkpnuqpv+zz49atW8dUKhW7/fbb2dy5c9lLL70kun8w/X4N+MBHp9Oxm266iX3wwQf8sZdeeomNHDmSn7sVOnHiBJs0aRJTq9X8J4KhgPrJPdRf7qH+8gz1m3uov9zTW39pNBr+2DPPPMNGjBjBPvroI7Z37172yiuvMLlczrZu3coYG3wB4YCv47N3717Exsbiwgsv5Cturly5EhqNBjt37uTPs9VjOHbsGBQKBVQqFV9kiQ2BgmfUT+6h/nIP9ZdnqN/cQ/3lnt76a8eOHfx5t99+O06dOoVrr70WkyZNwrJly3Deeedh/fr1AAZfbayQQDfAXa+88gpiYmIwcuRIjB8/HtOnT8eUKVMQHh4OAPz2CBMnTkRYWBj/ONsv+7Zt2zB16lT+j+D+++9HUVERrrvuukG1fxT1k3uov9xD/eUZ6jf3UH+5x9P+ioqKAgC++KDFYoFUKkVmZmZAnofP+XmEyWNHjhxhGRkZrKioiF1wwQUsISGBvffee/y8o31tilGjRjmd17322mtZcXEx+/TTT1lcXBwrKChgFRUV/ngKfkH95B7qL/dQf3mG+s091F/u8VZ/2bz99ttszpw5ojo9g8mACXxWrVrF7r//fv72q6++ykaOHMk+/vhjh3OPHj3KJkyYwDQajeg/vKSkhKWkpLCYmBgWGxsrqvcwWFA/uYf6yz3UX56hfnMP9Zd7vNFf27dvZ6tWrWLjxo1jmZmZDqu5BpOgHeszGo3o6OgQzdXaNjdjjOHOO+/EBRdcgA0bNvBzu7Y5zIMHDyIxMRFhYWH85nIAEB4eDrVajccffxwtLS343e9+5+dn5X3UT+6h/nIP9ZdnqN/cQ/3lHl/01/jx45GcnIzly5fj7NmzOP/88/38rPwnKAOfNWvWYMyYMbjuuutw2223wWw2Q6fTISUlBYD1Px2wJmmZTCb8+OOP6Ojo4P8Td+3ahaKiIoSEWFOYHn30UXz55ZdITk5Ge3s77r333sA8MS+jfnIP9Zd7qL88Q/3mHuov9/iiv7755htERERg2bJluO222wLzxPwpgKNNDmxL72bOnMk2bdrEPvroI5aTk8P+/Oc/s5dffpkNGzaMP9e2vO6VV15hV1xxBdu3bx9/329/+1tWVlbGfvjhB5aamsrS0tLY8ePH/f58fIX6yT3UX+6h/vIM9Zt7qL/c48v+OnHihN+fTyAFVeBz/Phx9oc//EG0IdyBAwdYWFgYO378OMvLy2MfffQRY8y6Ay9jjLW2trKioiL25ZdfMsYYO3z4MMvMzGSpqaksPDycvf322/5/Ij5G/eQe6i/3UH95hvrNPdRf7qH+8p6gmurSarWYM2cOEhMTwaxBGUaPHo158+ahvr4eS5cuxerVqwEAMpkMJpMJMTExmD59Oj7//HMAQGRkJNRqNW6//XZotVr8/ve/D+Az8g3qJ/dQf7mH+ssz1G/uof5yD/WXFwUi2nKFbaiupaWFZWRksLKyMtbU1MRGjx7NVq5cKTr3rrvuYs8//zx/u6Ojw69tDSTqJ/dQf7mH+ssz1G/uof5yD/VX/wRtAUOO42A2m6HRaJCeno7w8HDEx8fjrbfewsKFC6FSqfC73/0OOp0OO3bswBVXXME/VqlUBrDl/kX95B7qL/dQf3mG+s091F/uof7qp0BHXn357rvv2IIFCxhjjOn1esYYY59//jm74YYb2KRJk1hiYiJ7/fXXA9nEoED95B7qL/dQf3mG+s091F/uof7yDMdYcG9ccscdd0CpVOLFF190uK+kpAT5+fkBaFXwoX5yD/WXe6i/PEP95h7qL/dQf3kmqJKbhcxmM0wmE44ePYprr70WAPD6669DIpHg3XffBQD6TwX1k7uov9xD/eUZ6jf3UH+5h/qrf4I2x0cqlUKtViMtLQ2lpaW4/fbb0dbWhg0bNuDSSy8NdPOCBvWTe6i/3EP95RnqN/dQf7mH+qufAj3X1psff/yRcRzHIiIi2NNPPx3o5gQt6if3UH+5h/rLM9Rv7qH+cg/1l+eCOsfn7NmzWL9+PVasWAGFQhHo5gQt6if3UH+5h/rLM9Rv7qH+cg/1l+eCOvAhhBBCCPGmoE1uJoQQQgjxNgp8CCGEEDJkUOBDCCGEkCGDAh9CCCGEDBkU+BBCCCFkyKDAhxBCCCFDBgU+hBBCCBkyKPAhhBBCyJBBgQ8hhBBChgwKfAghhBAyZFDgQwghhJAhgwIfQgghhAwZ/x8moPKozlVAIAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pf.plotting.plot_rolling_returns(returns, factor_returns=benchmark_rets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "881421c7-d50a-4011-94e8-55a769b4b564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Rolling volatility (6-month)'}, ylabel='Volatility'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyfolio.plotting import plot_rolling_volatility\n",
    "plot_rolling_volatility(returns,\n",
    "                        factor_returns=benchmark_rets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b62c491b-b2be-4566-8379-8aa0f70434fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\"><th>Start date</th><td colspan=2>2022-01-03</td></tr>\n",
       "    <tr style=\"text-align: right;\"><th>End date</th><td colspan=2>2022-12-30</td></tr>\n",
       "    <tr style=\"text-align: right;\"><th>Total months</th><td colspan=2>11</td></tr>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Backtest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Annual return</th>\n",
       "      <td>-0.188%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cumulative returns</th>\n",
       "      <td>-0.184%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Annual volatility</th>\n",
       "      <td>3.14%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharpe ratio</th>\n",
       "      <td>-0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Calmar ratio</th>\n",
       "      <td>-0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stability</th>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Max drawdown</th>\n",
       "      <td>-2.803%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Omega ratio</th>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sortino ratio</th>\n",
       "      <td>-0.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skew</th>\n",
       "      <td>-2.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kurtosis</th>\n",
       "      <td>32.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tail ratio</th>\n",
       "      <td>1.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily value at risk</th>\n",
       "      <td>-0.396%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gross leverage</th>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily turnover</th>\n",
       "      <td>13.204%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alpha</th>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beta</th>\n",
       "      <td>0.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Backtest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Annual return</th>\n",
       "      <td>-0.188%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cumulative returns</th>\n",
       "      <td>-0.184%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Annual volatility</th>\n",
       "      <td>3.14%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sharpe ratio</th>\n",
       "      <td>-0.044307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Calmar ratio</th>\n",
       "      <td>-0.067148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stability</th>\n",
       "      <td>0.069493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Max drawdown</th>\n",
       "      <td>-2.803%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Omega ratio</th>\n",
       "      <td>0.984833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sortino ratio</th>\n",
       "      <td>-0.056837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Skew</th>\n",
       "      <td>-2.710954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kurtosis</th>\n",
       "      <td>32.746757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tail ratio</th>\n",
       "      <td>1.230304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily value at risk</th>\n",
       "      <td>-0.396%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gross leverage</th>\n",
       "      <td>0.118736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Daily turnover</th>\n",
       "      <td>13.204%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alpha</th>\n",
       "      <td>0.012851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beta</th>\n",
       "      <td>0.055337</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Backtest\n",
       "Annual return          -0.188%\n",
       "Cumulative returns     -0.184%\n",
       "Annual volatility        3.14%\n",
       "Sharpe ratio         -0.044307\n",
       "Calmar ratio         -0.067148\n",
       "Stability             0.069493\n",
       "Max drawdown           -2.803%\n",
       "Omega ratio           0.984833\n",
       "Sortino ratio        -0.056837\n",
       "Skew                 -2.710954\n",
       "Kurtosis             32.746757\n",
       "Tail ratio            1.230304\n",
       "Daily value at risk    -0.396%\n",
       "Gross leverage        0.118736\n",
       "Daily turnover         13.204%\n",
       "Alpha                 0.012851\n",
       "Beta                  0.055337"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pf.plotting.show_perf_stats(\n",
    "        returns,\n",
    "        benchmark_rets,\n",
    "        positions=positions,\n",
    "        transactions=transactions)"
   ]
  }
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