pandas-ta/examples/AIExample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strategy Analysis with **Pandas TA** and AI/ML\n",
    "* This is a **Work in Progress** and subject to change!\n",
    "* Contributions are welcome and accepted!\n",
    "* Examples below are for **educational purposes only**.\n",
    "* **NOTE:** The **watchlist** module is independent of Pandas TA. To easily use it, copy it from your local pandas_ta installation directory into your project directory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required Packages\n",
    "##### Uncomment the packages you need to install or are missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install numpy\n",
    "#!pip install pandas\n",
    "#!pip install mplfinance\n",
    "#!pip install pandas-datareader\n",
    "#!pip install requests_cache\n",
    "#!pip install tqdm\n",
    "#!pip install alphaVantage-api # Required for Watchlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "Numpy v1.20.2\n",
      "Pandas v1.2.4\n",
      "mplfinance v0.12.7a12\n",
      "\n",
      "Pandas TA v0.2.74b0\n",
      "To install the Latest Version:\n",
      "$ pip install -U git+https://github.com/twopirllc/pandas-ta\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import datetime as dt\n",
    "import random as rnd\n",
    "from sys import float_info as sflt\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option(\"max_rows\", 100)\n",
    "pd.set_option(\"max_columns\", 20)\n",
    "\n",
    "import mplfinance as mpf\n",
    "import pandas_ta as ta\n",
    "\n",
    "from tqdm.notebook import trange, tqdm\n",
    "\n",
    "from watchlist import colors, Watchlist # Is this failing? If so, copy it locally. See above.\n",
    "\n",
    "print(f\"Numpy v{np.__version__}\")\n",
    "print(f\"Pandas v{pd.__version__}\")\n",
    "print(f\"mplfinance v{mpf.__version__}\")\n",
    "print(f\"\\nPandas TA v{ta.version}\\nTo install the Latest Version:\\n$ pip install -U git+https://github.com/twopirllc/pandas-ta\\n\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MISC Function(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def recent_bars(df, tf: str = \"1y\"):\n",
    "    # All Data: 0, Last Four Years: 0.25, Last Two Years: 0.5, This Year: 1, Last Half Year: 2, Last Quarter: 4\n",
    "    yearly_divisor = {\"all\": 0, \"10y\": 0.1, \"5y\": 0.2, \"4y\": 0.25, \"3y\": 1./3, \"2y\": 0.5, \"1y\": 1, \"6mo\": 2, \"3mo\": 4}\n",
    "    yd = yearly_divisor[tf] if tf in yearly_divisor.keys() else 0\n",
    "    return int(ta.RATE[\"TRADING_DAYS_PER_YEAR\"] / yd) if yd > 0 else df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[!] Loading All: SPY, QQQ, AAPL, TSLA, BTC-USD\n",
      "[+] Downloading[yahoo]: SPY[D]\n",
      "[+] Saving: /Users/kj/av_data/SPY_D.csv\n",
      "[i] Runtime: 476.9447 ms (0.4769 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 455.1703 ms (0.4552 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 460.0315 ms (0.4600 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 456.2752 ms (0.4563 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 451.6120 ms (0.4516 s)\n"
     ]
    }
   ],
   "source": [
    "tf = \"D\"\n",
    "tickers = [\"SPY\", \"QQQ\", \"AAPL\", \"TSLA\", \"BTC-USD\"]\n",
    "watch = Watchlist(tickers, tf=tf, ds_name=\"yahoo\", timed=True)\n",
    "# watch.strategy = ta.CommonStrategy # If you have a Custom Strategy, you can use it here.\n",
    "watch.load(tickers, analyze=True, verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Asset Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPY (7108, 12)\n",
      "Columns: open, high, low, close, volume, dividends, split, SMA_10, SMA_20, SMA_50, SMA_200, VOL_SMA_20\n"
     ]
    }
   ],
   "source": [
    "ticker = tickers[0] # change tickers by changing the index\n",
    "print(f\"{ticker} {watch.data[ticker].shape}\\nColumns: {', '.join(list(watch.data[ticker].columns))}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trim it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_200</th>\n",
       "      <th>vol_sma_20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-04-22</th>\n",
       "      <td>273.956662</td>\n",
       "      <td>276.564830</td>\n",
       "      <td>272.539388</td>\n",
       "      <td>274.694824</td>\n",
       "      <td>93524600</td>\n",
       "      <td>274.489117</td>\n",
       "      <td>263.075163</td>\n",
       "      <td>277.084857</td>\n",
       "      <td>293.063143</td>\n",
       "      <td>167661845.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-23</th>\n",
       "      <td>276.062859</td>\n",
       "      <td>279.458417</td>\n",
       "      <td>274.350332</td>\n",
       "      <td>274.675110</td>\n",
       "      <td>104709700</td>\n",
       "      <td>274.986145</td>\n",
       "      <td>264.664179</td>\n",
       "      <td>276.017570</td>\n",
       "      <td>292.996336</td>\n",
       "      <td>157925815.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-24</th>\n",
       "      <td>276.299118</td>\n",
       "      <td>279.222243</td>\n",
       "      <td>274.104305</td>\n",
       "      <td>278.503754</td>\n",
       "      <td>85166000</td>\n",
       "      <td>275.455618</td>\n",
       "      <td>265.735499</td>\n",
       "      <td>274.984586</td>\n",
       "      <td>292.941791</td>\n",
       "      <td>149302475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-27</th>\n",
       "      <td>280.619817</td>\n",
       "      <td>283.720094</td>\n",
       "      <td>280.127709</td>\n",
       "      <td>282.519348</td>\n",
       "      <td>77896600</td>\n",
       "      <td>276.576642</td>\n",
       "      <td>267.390459</td>\n",
       "      <td>274.038959</td>\n",
       "      <td>292.903932</td>\n",
       "      <td>141980245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-28</th>\n",
       "      <td>286.426668</td>\n",
       "      <td>286.800675</td>\n",
       "      <td>280.895376</td>\n",
       "      <td>281.220184</td>\n",
       "      <td>105270000</td>\n",
       "      <td>276.767578</td>\n",
       "      <td>268.575457</td>\n",
       "      <td>273.056781</td>\n",
       "      <td>292.853083</td>\n",
       "      <td>138675270.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-15</th>\n",
       "      <td>413.739990</td>\n",
       "      <td>416.160004</td>\n",
       "      <td>413.690002</td>\n",
       "      <td>415.869995</td>\n",
       "      <td>60229800</td>\n",
       "      <td>409.150995</td>\n",
       "      <td>400.666098</td>\n",
       "      <td>392.662884</td>\n",
       "      <td>356.918501</td>\n",
       "      <td>83970505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-16</th>\n",
       "      <td>417.250000</td>\n",
       "      <td>417.910004</td>\n",
       "      <td>415.730011</td>\n",
       "      <td>417.260010</td>\n",
       "      <td>82004500</td>\n",
       "      <td>410.815997</td>\n",
       "      <td>402.018999</td>\n",
       "      <td>393.396016</td>\n",
       "      <td>357.480658</td>\n",
       "      <td>82315105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-19</th>\n",
       "      <td>416.260010</td>\n",
       "      <td>416.739990</td>\n",
       "      <td>413.790009</td>\n",
       "      <td>415.209991</td>\n",
       "      <td>78498500</td>\n",
       "      <td>411.700998</td>\n",
       "      <td>403.305498</td>\n",
       "      <td>394.001630</td>\n",
       "      <td>358.021889</td>\n",
       "      <td>80601140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-20</th>\n",
       "      <td>413.910004</td>\n",
       "      <td>415.089996</td>\n",
       "      <td>410.589996</td>\n",
       "      <td>412.170013</td>\n",
       "      <td>81851800</td>\n",
       "      <td>412.306000</td>\n",
       "      <td>404.284499</td>\n",
       "      <td>394.516144</td>\n",
       "      <td>358.539468</td>\n",
       "      <td>81004800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-21</th>\n",
       "      <td>411.510010</td>\n",
       "      <td>416.290009</td>\n",
       "      <td>411.359985</td>\n",
       "      <td>416.070007</td>\n",
       "      <td>66345300</td>\n",
       "      <td>413.254001</td>\n",
       "      <td>405.612999</td>\n",
       "      <td>395.052841</td>\n",
       "      <td>359.052723</td>\n",
       "      <td>79787735.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "date                                                                    \n",
       "2020-04-22  273.956662  276.564830  272.539388  274.694824   93524600   \n",
       "2020-04-23  276.062859  279.458417  274.350332  274.675110  104709700   \n",
       "2020-04-24  276.299118  279.222243  274.104305  278.503754   85166000   \n",
       "2020-04-27  280.619817  283.720094  280.127709  282.519348   77896600   \n",
       "2020-04-28  286.426668  286.800675  280.895376  281.220184  105270000   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2021-04-15  413.739990  416.160004  413.690002  415.869995   60229800   \n",
       "2021-04-16  417.250000  417.910004  415.730011  417.260010   82004500   \n",
       "2021-04-19  416.260010  416.739990  413.790009  415.209991   78498500   \n",
       "2021-04-20  413.910004  415.089996  410.589996  412.170013   81851800   \n",
       "2021-04-21  411.510010  416.290009  411.359985  416.070007   66345300   \n",
       "\n",
       "                sma_10      sma_20      sma_50     sma_200   vol_sma_20  \n",
       "date                                                                     \n",
       "2020-04-22  274.489117  263.075163  277.084857  293.063143  167661845.0  \n",
       "2020-04-23  274.986145  264.664179  276.017570  292.996336  157925815.0  \n",
       "2020-04-24  275.455618  265.735499  274.984586  292.941791  149302475.0  \n",
       "2020-04-27  276.576642  267.390459  274.038959  292.903932  141980245.0  \n",
       "2020-04-28  276.767578  268.575457  273.056781  292.853083  138675270.0  \n",
       "...                ...         ...         ...         ...          ...  \n",
       "2021-04-15  409.150995  400.666098  392.662884  356.918501   83970505.0  \n",
       "2021-04-16  410.815997  402.018999  393.396016  357.480658   82315105.0  \n",
       "2021-04-19  411.700998  403.305498  394.001630  358.021889   80601140.0  \n",
       "2021-04-20  412.306000  404.284499  394.516144  358.539468   81004800.0  \n",
       "2021-04-21  413.254001  405.612999  395.052841  359.052723   79787735.0  \n",
       "\n",
       "[252 rows x 10 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration = \"1y\"\n",
    "asset = watch.data[ticker]\n",
    "recent = recent_bars(asset, duration)\n",
    "asset.columns = asset.columns.str.lower()\n",
    "asset.drop(columns=[\"dividends\", \"split\"], errors=\"ignore\", inplace=True)\n",
    "asset = asset.copy().tail(recent)\n",
    "asset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trend Creation\n",
    "A **Trend** is the result of some calculation or condition of one or more indicators. For simplicity, a _Trend_ is either ```True``` or ```1``` and _No Trend_ is ```False``` or ```0```. Using the **Hello World** of Trends, the **Golden/Death Cross**, it's Trend is _Long_ when ```long = ma(close, 50) > ma(close, 200) ``` and _Short_ when ```short = ma(close, 50) < ma(close, 200) ```. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TA Columns Added:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_200</th>\n",
       "      <th>vol_sma_20</th>\n",
       "      <th>EMA_8</th>\n",
       "      <th>EMA_21</th>\n",
       "      <th>EMA_50</th>\n",
       "      <th>PCTRET_1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-04-15</th>\n",
       "      <td>409.150995</td>\n",
       "      <td>400.666098</td>\n",
       "      <td>392.662884</td>\n",
       "      <td>356.918501</td>\n",
       "      <td>83970505.0</td>\n",
       "      <td>410.171168</td>\n",
       "      <td>402.758751</td>\n",
       "      <td>393.431087</td>\n",
       "      <td>0.010742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-16</th>\n",
       "      <td>410.815997</td>\n",
       "      <td>402.018999</td>\n",
       "      <td>393.396016</td>\n",
       "      <td>357.480658</td>\n",
       "      <td>82315105.0</td>\n",
       "      <td>411.746466</td>\n",
       "      <td>404.077047</td>\n",
       "      <td>394.365555</td>\n",
       "      <td>0.003342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-19</th>\n",
       "      <td>411.700998</td>\n",
       "      <td>403.305498</td>\n",
       "      <td>394.001630</td>\n",
       "      <td>358.021889</td>\n",
       "      <td>80601140.0</td>\n",
       "      <td>412.516138</td>\n",
       "      <td>405.089133</td>\n",
       "      <td>395.182984</td>\n",
       "      <td>-0.004913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-20</th>\n",
       "      <td>412.306000</td>\n",
       "      <td>404.284499</td>\n",
       "      <td>394.516144</td>\n",
       "      <td>358.539468</td>\n",
       "      <td>81004800.0</td>\n",
       "      <td>412.439222</td>\n",
       "      <td>405.732850</td>\n",
       "      <td>395.849142</td>\n",
       "      <td>-0.007322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-21</th>\n",
       "      <td>413.254001</td>\n",
       "      <td>405.612999</td>\n",
       "      <td>395.052841</td>\n",
       "      <td>359.052723</td>\n",
       "      <td>79787735.0</td>\n",
       "      <td>413.246063</td>\n",
       "      <td>406.672591</td>\n",
       "      <td>396.642117</td>\n",
       "      <td>0.009462</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                sma_10      sma_20      sma_50     sma_200  vol_sma_20  \\\n",
       "date                                                                     \n",
       "2021-04-15  409.150995  400.666098  392.662884  356.918501  83970505.0   \n",
       "2021-04-16  410.815997  402.018999  393.396016  357.480658  82315105.0   \n",
       "2021-04-19  411.700998  403.305498  394.001630  358.021889  80601140.0   \n",
       "2021-04-20  412.306000  404.284499  394.516144  358.539468  81004800.0   \n",
       "2021-04-21  413.254001  405.612999  395.052841  359.052723  79787735.0   \n",
       "\n",
       "                 EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                      \n",
       "2021-04-15  410.171168  402.758751  393.431087  0.010742  \n",
       "2021-04-16  411.746466  404.077047  394.365555  0.003342  \n",
       "2021-04-19  412.516138  405.089133  395.182984 -0.004913  \n",
       "2021-04-20  412.439222  405.732850  395.849142 -0.007322  \n",
       "2021-04-21  413.246063  406.672591  396.642117  0.009462  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example Long Trends\n",
    "# long = ta.sma(asset.close, 50) > ta.sma(asset.close, 200) # SMA(50) > SMA(200) \"Golden/Death Cross\"\n",
    "# long = ta.sma(asset.close, 10) > ta.sma(asset.close, 20) # SMA(10) > SMA(20)\n",
    "long = ta.ema(asset.close, 8) > ta.ema(asset.close, 21) # EMA(8) > EMA(21)\n",
    "# long = ta.increasing(ta.ema(asset.close, 50))\n",
    "# long = ta.macd(asset.close).iloc[:,1] > 0 # MACD Histogram is positive\n",
    "# long = ta.amat(asset.close, 50, 200).AMATe_LR_2  # Long Run of AMAT(50, 200) with lookback of 2 bars\n",
    "\n",
    "# long &= ta.increasing(ta.ema(asset.close, 50), 2) # Uncomment for further long restrictions, in this case when EMA(50) is increasing/sloping upwards\n",
    "# long = 1 - long # uncomment to create a short signal of the trend\n",
    "\n",
    "asset.ta.ema(length=8, sma=False, append=True)\n",
    "asset.ta.ema(length=21, sma=False, append=True)\n",
    "asset.ta.ema(length=50, sma=False, append=True)\n",
    "asset.ta.percent_return(append=True)\n",
    "print(\"TA Columns Added:\")\n",
    "asset[asset.columns[5:]].tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Trend Signals** \n",
    "Given a _Trend_, **Trend Signals** returns the _Trend_, _Trades_, _Entries_ and _Exits_ as boolean integers. When ```asbool=True```, it returns _Trends_, _Entries_ and _Exits_ as boolean values which is helpful when combined with the [**vectorbt**](https://github.com/polakowo/vectorbt) backtesting package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>TS_Trends</th>\n",
       "      <th>TS_Trades</th>\n",
       "      <th>TS_Entries</th>\n",
       "      <th>TS_Exits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-04-15</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-16</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-19</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-20</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-21</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TS_Trends  TS_Trades  TS_Entries  TS_Exits\n",
       "date                                                  \n",
       "2021-04-15          1          0           0         0\n",
       "2021-04-16          1          0           0         0\n",
       "2021-04-19          1          0           0         0\n",
       "2021-04-20          1          0           0         0\n",
       "2021-04-21          1          0           0         0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trendy = asset.ta.tsignals(long, asbool=False, append=True)\n",
    "trendy.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend Entries & Exits & Trade Table\n",
    "This is a simple way to reduce the Asset DataFrame to a Trade Table with Dates, Signals, and Entries and Exits. Gives you an idea what to expect before running through a backtester such as [**vectorbt**](https://github.com/polakowo/vectorbt)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current Trade:\n",
      "Price Entry | Last:\t385.9061 | 416.0700\n",
      "Unrealized PnL | %:\t30.1639 | 7.8164%\n",
      "\n",
      "Trades Total | Round Trip:\t7 | 3\n",
      "Trade Coverage: 81.35%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Signal</th>\n",
       "      <th>Entry</th>\n",
       "      <th>Exit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-05-19</th>\n",
       "      <td>1</td>\n",
       "      <td>287.361664</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-10</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>330.066162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-02</th>\n",
       "      <td>1</td>\n",
       "      <td>331.337799</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-27</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>335.684937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-04</th>\n",
       "      <td>1</td>\n",
       "      <td>340.965088</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-02</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>385.278137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-09</th>\n",
       "      <td>1</td>\n",
       "      <td>385.906067</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "date                                      \n",
       "2020-05-19       1  287.361664         NaN\n",
       "2020-09-10      -1         NaN  330.066162\n",
       "2020-10-02       1  331.337799         NaN\n",
       "2020-10-27      -1         NaN  335.684937\n",
       "2020-11-04       1  340.965088         NaN\n",
       "2021-03-02      -1         NaN  385.278137\n",
       "2021-03-09       1  385.906067         NaN"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entries = trendy.TS_Entries * asset.close\n",
    "entries = entries[~np.isclose(entries, 0)]\n",
    "entries.dropna(inplace=True)\n",
    "entries.name = \"Entry\"\n",
    "\n",
    "exits = trendy.TS_Exits * asset.close\n",
    "exits = exits[~np.isclose(exits, 0)]\n",
    "exits.dropna(inplace=True)\n",
    "exits.name = \"Exit\"\n",
    "\n",
    "total_trades = trendy.TS_Trades.abs().sum()\n",
    "rt_trades = int(trendy.TS_Trades.abs().sum() // 2)\n",
    "\n",
    "all_trades = trendy.TS_Trades.copy().fillna(0)\n",
    "all_trades = all_trades[all_trades != 0]\n",
    "\n",
    "trades = pd.DataFrame({\n",
    "    \"Signal\": all_trades,\n",
    "    entries.name: entries,\n",
    "    exits.name: exits\n",
    "})\n",
    "\n",
    "# Show some stats if there is an active trade (when there is an odd number of round trip trades)\n",
    "if total_trades % 2 != 0:\n",
    "    unrealized_pnl = asset.close.iloc[-1] - entries.iloc[-1]\n",
    "    unrealized_pnl_pct_change = 100 * ((asset.close.iloc[-1] / entries.iloc[-1]) - 1)\n",
    "    print(\"Current Trade:\")\n",
    "    print(f\"Price Entry | Last:\\t{entries.iloc[-1]:.4f} | {asset.close.iloc[-1]:.4f}\")\n",
    "    print(f\"Unrealized PnL | %:\\t{unrealized_pnl:.4f} | {unrealized_pnl_pct_change:.4f}%\")\n",
    "print(f\"\\nTrades Total | Round Trip:\\t{total_trades} | {rt_trades}\")\n",
    "print(f\"Trade Coverage: {100 * asset.TS_Trends.sum() / asset.shape[0]:.2f}%\")\n",
    "\n",
    "trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chart Display Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "extime = ta.get_time(to_string=True)\n",
    "first_date, last_date = asset.index[0], asset.index[-1]\n",
    "f_date = f\"{first_date.day_name()} {first_date.month}-{first_date.day}-{first_date.year}\"\n",
    "l_date = f\"{last_date.day_name()} {last_date.month}-{last_date.day}-{last_date.year}\"\n",
    "last_ohlcv = f\"Last OHLCV: ({asset.iloc[-1].open:.4f}, {asset.iloc[-1].high:.4f}, {asset.iloc[-1].low:.4f}, {asset.iloc[-1].close:.4f}, {int(asset.iloc[-1].volume)})\"\n",
    "ptitle = f\"\\n{ticker} [{tf} for {duration}({recent} bars)] from {f_date} to {l_date}\\n{last_ohlcv}\\n{extime}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trade Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nSPY [D for 1y(252 bars)] from Wednesday 4-22-2020 to Wednesday 4-21-2021\\nLast OHLCV: (411.5100, 416.2900, 411.3600, 416.0700, 66345300)\\nWednesday April 21, 2021, NYSE: 17:08:21, Local: 21:08:21 PDT, Day 111/365 (30.00%)'}, xlabel='date'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# chart = asset[\"close\"] #asset[[\"close\", \"SMA_10\", \"SMA_20\", \"SMA_50\", \"SMA_200\"]]\n",
    "# chart = asset[[\"close\", \"SMA_10\", \"SMA_20\"]]\n",
    "chart = asset[[\"close\", \"EMA_8\", \"EMA_21\", \"EMA_50\"]]\n",
    "chart.plot(figsize=(16, 10), color=colors(\"BkGrOrRd\"), title=ptitle, grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Long and Short Trends\n",
    "**Trends** are either a _Trend_ (```1```) or _No Trend_ (```0```) depending on the **Trend** passed into ***Trend Signals**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x61.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "long_trend = trendy.TS_Trends\n",
    "short_trend = 1 - long_trend\n",
    "\n",
    "long_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=colors()[0], alpha=0.25) # Green Area\n",
    "short_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=colors()[1], alpha=0.25) # Red Area"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trades or Trade Signals\n",
    "The **Trades** are either _Enter_ (```1```) or _Exit_ (```-1```) or _No Position/Action_ (```0```). These are based on the **Trend** passed into **Trend Signals** whether they are _Long_ or _Short_ Trends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x108 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "trendy.TS_Trades.plot(figsize=(16, 1.5), color=colors(\"BkBl\")[0], grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Active Returns\n",
    "**Active Returns** are returns made during the course of the _Trend_. They are simply the product of the returns and the _Trend_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x12d86cbb0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[\"ACTRET_1\"] = trendy.TS_Trends * asset.PCTRET_1\n",
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].plot(figsize=(16, 3), color=colors(\"GyOr\"), alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*) vs. Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x12da79790>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6IAAADjCAYAAACfFKnTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Z1A+gAAAACXBIWXMAAAsTAAALEwEAmpwYAAB8g0lEQVR4nOz9eZxc133feX/OXerW3vuClQB3iqJEmhS1mRJlSzafKLbsWB4pdrTY0Siex3riOCM/XibxyHHyyHmSTOxEmtiy43HsTEQniq1oFDlyxiZlrVwgcQEJEEuj0XtVV3XtVXc/80d1lxpEN9CNXgH83q9Xv9Bddevec6sPgP72Oed3lNYaIYQQQgghhBBitxh73QAhhBBCCCGEEDcXCaJCCCGEEEIIIXaVBFEhhBBCCCGEELtKgqgQQgghhBBCiF0lQVQIIYQQQgghxK6SICqEEEIIIYQQYldJEBVCCCGuQ0qp31ZK/cO9bocQQghxLSSICiGEuIRSalIp1VFKNZVSFaXUf1VKHXnVMT+glDqtlGoopZ5XSj3wqucfVUrNrHHuJ5VSH9npe3jVNfNKqd9USk0t39P55a+Hd7Mdr2rTk8vvrbPB4z+slPra6se01j+jtf71HWjb6u//glLqD5RS2Q2+dte/v0IIIa5PEkSFEEKs5Ye01lngAFAA/vWrnv93wL8A8sBPAJXdbd7GKKUSwF8A9wKP0W3vm4Ey8PAetekY8AiggR/eizZswMr3/37gAeCXd+OiSilrN64jhBBi70kQFUIIsS6ttQt8DnjNq54KgEnd9ZLWenIr11FKOUqpqlLqtaseG1kemRtVSg0rpb64fMySUuqrSqmN/B/2QeAo8KNa65e11rHWuqi1/nWt9ZeWr6OVUrevuu4fKKX+8fLnjyqlZpRS/1+lVFEpNa+U+hGl1F9TSp1ZbsuvbPJ2Pwh8C/gD4EOveh+OKKX+RCm1qJQqK6U+pZS6B/ht4M3Lo5TVNdp5Sin111edx1o+x/csf/0mpdQ3lt+/55VSj26koVrrBeDLdAPpyrnXPJdS6p/QDdifWm7np5RSx5bfX2vV63ujpssjvV9XSv1LpVQZ+MTyfX16eSS+oZR6Sil12/LxavnYolKqrpR6cXWfEUIIcf2QICqEEGJdSqk08D66wWnlMQU8Dfze8ujelmmtPeBPgL+56uH/AfiK1roI/M/ADDACjAG/QndE8WreCfw3rXVzC80bB5LAIeBXgd8F/hbwIN3g9Q+VUsc3cb4PAv/n8scPKqXGAJRSJvBF4CJwbPl6j2utTwE/A3xTa53VWvevcc7Pcul794NASWv9baXUIeC/Av8YGAQ+DvxnpdTI1RqqlDoM/L+Ac8tfr3surfX/AnwV+NhyOz+2wffjjcAE3e/rP1l+7P3ArwEDy9deefwHgLcBdwJ9dPtIeYPXEUIIsY9IEBVCCLGWzy+PvNWAdwH/bNVzvwik6YbBv1gJo0qpjyil/vOq4w4uj5r1PoDvvcI1/wPdALLiJ5Yfg+4I7AHgFq11oLX+qtZ6I0F0CJjfwHFXEgD/RGsdAI8Dw8Bvaa0bWuuXgJeB12/kREqp7wVuAf6j1voEcJ7ufUJ3qvBB4Be01i2ttau1/to6p3q1/wD88PIvDlg+52eXP/9bwJe01l9aHhH+78CzwF+7wvk+r5RqANNAEfhft3Cuq5nTWv9rrXWote4sP/anWuuntdYh3cB+//LjAZAD7gaU1vqU1nqr318hhBB7QIKoEEKItfzI8shbEvgY8BWl1Pjycz8H/LrW+v+kG1CfWA6jbwX+ctU55rTW/as/gCsFqyeAtFLqjcvnux/40+Xn/hndkbE/V0pNKKV+aYP3UaYbYLeirLWOlj9fCUqFVc93gA0V86E7FffPtdal5a//A9+dnnsEuLgcvjZFa30OOAX80HIY/WG+G+JvAX58jV8IXOl9+RGtdQ54lG7oWynsdC3nuprpNR5bWPV5m+X3V2v9l8CngE8DRaXUZ5RS+S1cWwghxB6RogBCCCHWtRzA/kQp9Tt0A8fn6P7fYS8//9tKqUHgyeWX/N2tXEsp9R/pTjEtAF/UWjeWn2vQnZ77Py+vCfxLpdQzWuu/uMpp/2/gHyulMlrr1jrHtOmO8K4YpzsNeFsppVJ0p5KaSqmVoOUA/Uqp19MNZEeVUtYaYXQjo78r03MN4OXlcMryef9Ia/0/brbNWuuvKKX+APjnwI9s4FyvbufKe54G6sufj7/qmI3c2+o2/SvgXymlRoH/CPwCINvYCCHEdUZGRIUQQqxruTjMe+iu1Tu1/PB/Av6ZUurW5SI0T9NdL+gB5hYv+R/orkn9Sb47oodS6q8rpW5fXp9aAyIg3sD5/ohuePrPSqm7lVKGUmpIKfUrSqmV6aTPAT+hlDKVUo8Bb9/iPaznR+i2+zV0R3vvB+6hu67yg3Tfx3ngN5RSGaVUUin11uXXFoDDqlsFeD2P011D+T+x6r0D/j3dkdIfXL7HpOoWYTq8wXb/JvCu5bB8tXMVgFtXXqi1XgRmgb+1fPxPA7dt8LqXUUq9YXnE3KYbcl021g+EEELsMxJEhRBCrOX/Uko16Y5i/RPgQ8vrIaE7MvlV4K+AKvAJ4EeB5+mOntrXelGt9VN0A8ZB4M9WPXUH3dHNJvBN4H/XWj8BoJT6M7VO5drlIkjvBE4D/335fp6mO9X0qeXDfg74oeV7+Ung89fafqXUTyqlXlrn6Q8B/4fWekprvbDyQXeq6U8CarkdtwNTdEdl37f82r8EXgIWlFKly08Ny2slvwm8BfjjVY9PA++hu6Z3kW4w/wU2+DPAcpj8Q+BXN3Cu3wLeq7p7pP6r5cf+x+VjynS30fnGRq67jjzdYlEVukWdyly6flkIIcR1Qm2s1oMQQgghhBBCCLE9ZERUCCGEEEIIIcSukiAqhBBCCCGEEGJXSRAVQgghhBBCCLGrJIgKIYQQQgghhNhVe7aP6PDwsD527NheXX5PtFotMpnMXjdD7FPSP8RGSD8RVyL9Q1yJ9A+xmvQHcSXb1T9OnDhR0lqPrPXcngXRY8eO8eyzz+7V5ffEk08+yaOPPrrXzRD7lPQPsRHST8SVSP8QVyL9Q6wm/UFcyXb1D6XUxfWek6m5QgghhBBCCCF2lQRRIYQQQgghhBC7SoKoEEIIIYQQQohdtWdrRNcSBAEzMzO4rrvXTdkRfX19nDp1alevmUwmOXz4MLZt7+p1hRBCCCGEEGI9+yqIzszMkMvlOHbsGEqpvW7Otms0GuRyuV27ntaacrnMzMwMx48f37XrCiGEEEIIITYujmPK5TKe55FOp8lmsyQSiSu+Rmt9XWemfRVEXde9YUPoXlBKMTQ0xOLi4l43RQghhBBCCLGGxcVFZmZmqNVqVCoVLMsik8mQzWYZHBwkl8uRzWZJp9O9nFSr1Zifn+e22267bmc+7qsgCkgI3WbyfgohhBBCCLE/NZtNJiYmWFhYIJFIMDw8jOd5NJtNqtUqFy5cwLZtstksY2Nj3HfffQRBwMTEBMVikUOHDkkQFUIIIYQQQgixviiKaLVaZLNZtNZcuHCBcrlMLpejr68PgHQ6zcDAANCdfttut6nVapw8eRLf98lmsxSLRYIgII7jvbydLdnXQfTpp5+m0Whs2/lyuRwPP/zwtp1PCCGEEEIIIaAbGhuNBmEYorXuPbby0W63KZVK1Ot1HMe5ZAldPp9f85xKKTKZDJlMhnQ6zZkzZxgcHCSKIlKp1K7d207Y10G00WjQ39+/beerVqtXPcY0Te677z7CMOSee+7h3/27f0c6nWZhYYG/9/f+Hs888wz9/f2MjY3xyU9+kg996EMATE1N0dfXR19fH8PDw/ze7/0e99xzD3fddRe+7/PQQw/xm7/5mwA8+eSTvOc977mkgNAv//Iv88lPfhKAhYUFTNNkZGQE6AbytRYr//RP/zRf/OIXGR0d5eTJk1t8d4QQQgghhBDXQmvN1NQUMzMzNJvNSwLoygdAGIZYlkWpVGJ2dhbHcRgbG9vQcrr+/n6UUtTrdcbHx2m32zt9WztqXwfRvZBKpXjuuecA+Mmf/El++7d/m5//+Z/nR3/0R/nQhz7E448/DsDzzz9PvV7vHfvhD3+Yv/7X/zrvfe97AZicnOS2227jueeeI4oi3vWud/Enf/InfOQjHwHgkUce4Ytf/OIl137f+94HwCc+8Qmy2Swf//jHr9jWD3/4w3zsYx/jgx/84HbdvhBCCCGEEGITtNZMT08zPT1NuVzuFRVa/QHdAa9kMolpmgC0222UUpta47ky8HUjkCB6BY888ggvvPACTzzxBLZt8zM/8zO9517/+tdv+DymafLwww8zPz+/re1729vexuTk5LaeUwghhBBCCLExvu8zNTXFwsIC5XKZkZERHMfZ0GvT6fQOt25/MzZykFLqMaXUK0qpc0qpX7rCcT+mlNJKqYe2r4l7IwxD/uzP/oz77ruPkydP8uCDD17zuVzX5amnnuKd73xn77GvfvWr3H///b2P8+fPb0ezhRBCCCGEENssiiJKpRKlUolqtUqpVGJ6epoXX3yRiYkJlpaWNhVCxQZGRJVSJvBp4F3ADPCMUuoLWuuXX3VcDvg54KmdaOhu6XQ63H///UB3RPRv/+2/zW//9m9f07nOnz/P/fffz4ULF3j3u9/Na1/72t5za03NFUIIIYQQQuwfURRRKBRYWFigWq3SbrexLAvDMPA8r1c06MCBAxjGhsb4xLKNTM19GDintZ4AUEo9DrwHePlVx/068E+BX9jWFu6y1WtEV9x777187nOf2/S5VtaIlkol3vrWt/KlL32ptw5UCCGEEEIIsT+FYUixWOwF0EajgeM4pNNpoigCuus1HcfBsmS147XYyLt2CJhe9fUM8MbVByilvgc4orX+r0qpbQuiuVxuQ5VuN3O+a/F93/d9/Mqv/Aqf+cxn+OhHPwrACy+8QK1W45FHHrnq64eHh/mN3/gNPvnJT0oQFUIIIYQQYp8Kw/CSEdBms4njOIyOjq65i4W4dluO70opA/jfgA9v4NiPAh8FGBsb48knn7zk+b6+vkv2Db3nnnu22rzLbGRf0rWO+aM/+iN+6Zd+iU9+8pMkk0mOHj3Kb/zGb/SODYKATqfT+7rZbBLHce/r7//+7+cf/sN/yJe//GWiKOKrX/0qr3vd63rn/4Vf+AV+5Ed+BADP87Bt+6pt/amf+im+9rWvUS6XOXToEL/yK7+yZgVd13Uve6/F/tNsNuX7JK5K+om4Eukf4kqkf4jVpD9cKo5jms0m7XabIAgwTZNUKkUikSCOYyqVyl438TJRFPHss8/2qvBup93oH2plT5t1D1DqzcAntNY/uPz1LwNorT+5/HUfcB5oLr9kHFgCflhr/ex6533ooYf0s89e+vSpU6d2JHzuF41G45pHZbfiRn9fbxRPPvkkjz766F43Q+xz0k/ElUj/EFci/UOsJv3huzzP4+WXX2ZpaYlGo0EqlaKvr29T26rshVqtxoMPPrgj27lsV/9QSp3QWq9ZyHYjI6LPAHcopY4Ds8D7gZ9YeVJrXQOGV13sSeDjVwqhQgghhBBCCLHXtNZcvHiRxcVFwjBkfHx83wfQG8VVg6jWOlRKfQz4MmACv6+1fkkp9Y+AZ7XWX9jpRt7MyuUy3//933/Z43/xF3/B0NDQHrRICCGEEEKIG0OpVKJYLOJ5HuPj41L5dhdtaI2o1vpLwJde9divrnPso1tvllgxNDR0WRVfIYQQQgghbgRBEBAEAel0elvOF4YhS0tLACilMAwDpVTvI5lMkkwmge7U1qmpKZaWlhgcHJQQusuk1rAQQgghhBBiR4VhSL1ep9FoYBgGqVSKdrtNoVCg0Wjwhje8YVtqqczOzjIxMUGr1bokgK6EUsMwGBoaIpPJUCqVWFpaIpVKkUqltuEuxWZIEBVCCCGEEEJsqziOabVa1Ot16vU61WqVTqdDu92m0+ngOA62beN5HvV6nWQyyVve8pYtXTMMQxYXF6nVar0CPnEc9/6M45hOp8OZM2ewLAvbtsnn82Sz2S3fr9g8CaJCCCGEEEKILWs0Gr3AWa/XabfbtFotPM9DKYXjOOTzeYaGhvA8jziOGRoaIpVKMTk5yX333bfuqKjv+ywtLdFutzly5MiaBYWKxSK1Wo1UKkU+n79iW33fx7IsmY67h/Z3EH3l0+DObd/5kgfhrp/dvvMJIYQQQgixjnq9ThRFvXWK6/2ptUZrTSKRQCm1182+Jq1Wi9OnT1MsFvF9H4BEIkEqlWJgYOCy4JhIJHqfDwwMUC6XefHFFy8ZFY2iiGq1SrlcZmlpiWazSbVaZWpqikceeeSS/TPjOKZQKNBsNhkbG7tqe1dfX+yN/R1E3TnI3LJ952td3NBhn//85/nRH/1RTp06xd133w3A008/zcc//nEKhQLpdJoHH3yQBx54gN/93d8F4OWXX+auu+7CNE0ee+wx7r77bn7hF36BQ4cO4bouf+fv/B0+8pGPAPCJT3yC3/3d32VkZKR3zV/+5V/mk5/8JADnzp3j0KFDpFIpXve61/GHf/iHl7WxXC7z3ve+l2eeeYYPf/jDfOpTn9rSWyOEEEIIIbZHEARcvHixF4xWr1F89brFleCptSaVSnHnnXfS39+/qet5nkehUODw4cN7MsIXRREXLlygVCqRSCQYHh7GsjYeM0zTZGhoiMnJSYaHhxkYGKDValEqlWg2mzSbTaIoIplMMjAwwMzMDE899RRvetObevdbKpWo1WrYti3br1wn9ncQ3SOf/exn+d7v/V4++9nP8mu/9msUCgV+/Md/nMcff5w3v/nNAHzuc5/jkUce4Wd/tjvCeuzYMZ544gmGh7tbqv7BH/wB73vf+/jUpz5FuVzmrrvu4rHHHuOee+4B4Od//uf5+Mc/fsl13/e+9wHw6KOP8s//+T/noYfW3PsVgGQyya//+q9z8uRJTp48ue3vgRBCCCGEuFwcx9TrdWq1GlprLMvqfaysi6xWq5RKJTqdDslkEq01cRwTBAFaa4BL/lwZFZ2bm2Nubo7jx48zMjJCLpcjm81ecZRUa83k5CQXLlwgDENuvfXWq95DFEXb82Ysm5mZoVgsEscxAwMD1zSqOzAwQLvd5tvf/japVArbtvF9H8dx6O/vJ5lM9s5rmibnz58njmPuv/9+ms0mU1NTNBoNBgcHt/XedosZNUh5ZzGjBoE1RGgNEpiDaCO57msM7e9iC7efBNFXaTabfO1rX+OJJ57gh37oh/i1X/s1Pv3pT/OhD32oF0IB3vve9274nENDQ9x+++0sLCz0guhWZTIZvvd7v5dz585ty/mEEEIIIcTaVsJnpVKhUqnQaDRoNpt0Oh0Mw8CyLEzTxDAMgiAgDEMymQzj4+OXTB/dyHWKxSKnT5/mlVdeIZfL0d/fz6FDh3qVXl9tcXGRYrFIsVjEtu2rBtFyucz58+ep1+ubfh9eTWvNzMwMs7OzNBoNxsfHr3lqsWmaHD16lCiKaLfbaK0ZGRlZc4Q3l8tx9OhRpqamqFQq9PX1Ua1WyWQyva1ZrieZ9nOk3VMkwgUSQQGICc1BQqufwBzBTRwhtIbx7ENowwEg6Z0j1XkWgtcCfXva/mslQfRV/st/+S889thj3HnnnQwNDXHixAlOnjzJhz70oWs+59TUFK7r8trXvrb32L/8l/+Sf//v/z3Q/Q3QE088seW2CyGEEEKI7dNoNHpbfKxMEV0ZpctkMgwPD/dGOsMwRGtNPp8nkUhc0xRZwzAYHx8HutNta7Uas7OzXLx4kb6+PoaHhzl48CBDQ0MkEglarRbT09NUKhUGBgYoFouEYbjutNh6vc7ExAQzMzPUajUuXrzILbdc2zK4OI6ZmJhgfn6+tw/nZqbjrsc0zQ1t45LNZrntttuYn5+nWq0yNDR0XYZQx58i475AypvEtwZoph+AOMSOyljBIo4/Tb79TSIji2sfpTjwNzF1i2z7OxjBWVTU2OtbuGYSRF/ls5/9LD/3cz8HwPvf/34++9nPXvO5/viP/5i/+qu/4vTp03zqU5+65C/HWlNzhRBCCCHE3ut0OszMzFAqlahUKvi+TyKRIJvNkk6nLwuZO1H4xnEcRkdHge9WjJ2cnGRiYoKBgQHS6TRRFNFqtUilUiSTSer1OgsLCxw+fPiy87Xbbc6ePUuhUKCvrw/XdfnWt76F4zi98LsZCwsLzMzM0Gg0GB0d3ZPiP5ZlceTIkV2/7lZY4RJ2uIhnHwJlkm1/G8efxrUPEVkD3YNMG988DCx/H3WEHRTJdp7D0B5e4haS/gS+jkFv7zTr3SRBdJWlpSX+8i//khdffBGlFFEUoZTiQx/6ECdOnOA973nPps63skb02Wef5Qd+4Af4vu/7vm3ZqFcIIYQQQuwM3/c5deoUxWIRz/PI5/PrThHdLYlEohcWO50OlUoF13V7e2GuFDcyDIPp6enLgqjneZw5c4ZisUgikaC/vx/Xdel0OnzrW9/ih37ohzY1hTgMQ+bn56nVansWQvclHZLyzqN0gCIGNGi9/HmMFdVIBLMkggU0Fq5zK45/kVilvhtC16JMgsQBGkaaXOc72GGRSKUJzetzSu6K/R1Ekwc3XOl2w+e7gs997nN84AMf4Hd+53d6j7397W/nne98Jx/84Ad597vfzRvf+EYA/uRP/oS3vvWtGyoP/dBDD/GBD3yAf/Nv/g3/4l/8i63dgxBCCCHEDczzPFzXJQiC3jTX1eI47oUoz/NIJpNkMhkcx9mW609NTVEqldBac/DgwX23z2QqlSKVSq35XC6XY3Z2tlcACboVfM+cOcPCwgJKqV4xH6UUBw4c4MKFC5w6deqSJWQra1UdxyGbzV5WhbZQKFCtVnEcR0LoCh3S1/oG6c7LJML55ccAYgAUoFFoI0Go+rDiCn3NvyKwBuk4d27oErHVRyP9BhLBPJ5zCzrcxm0u98D+DqK7vOfnZz/7WX7xF3/xksd+7Md+jMcff5zHH3+cj3/84xSLRQzD4G1vexuPPfbYhs/9i7/4izzwwAN84hOfAC5dIwrdLWOOHTu2qfYeO3aMer2O7/t8/vOf58///M95zWtes6lzCCGEEELsF6VSibNnz9LpdPB9H8uyuPXWW0mn03Q6HdrtNo1GA9/3e4EVIJ1Oc9ddd605JXUzKpUKxWIR13UZHx/fdyH0arLZLLVajXK5zPDwMFEUce7cOQqFAnEcMzo6ekkxoWQySV9fHy+//DK33357bxlZqVTilVdeodFokE6nyeVyDA4Oks/nSaVSLCwsbHi/zptCL4S+hBUt4SZuRSuDbvxU6OU/WQ6iAD6HQEcoHYHaeCSLzQyueftO3MWu299BdJetVTDo7/7dv9v7/Ktf/eq6r52cnLzk6w9/+MN8+MMf7n198OBBzp07Ry6X4xOf+EQvkK7lySef3FB7X31NIYQQQojrVRzHzM7Osri42JtyWq/Xeeqpp8jlcsRxTBiGmKbZe76vr48wDFlcXKTZbF5TEI2iiEKh0CsOVC6X6evr29RU1f0ilUqhlOLFF1/kjW98I7Ozs8zPz+N5HiMjI2tWtB0ZGeH8+fOcPHmyt3VgqVTqjXi2Wi0qlQrnz5/vjZCu7Okp+3WCHS6SbX2bpH8eK6rgJm7rhc2rUiZaXX/9bLtIEBVCCCGEEOtaqa5qWRbDw8P09/fvyHTMYrFIpVLBsqzeSNvg4CC+7+O6Lo7jYNv2uqOU8/Pz1Ot18vn8pq47MzPT284kjmPS6TTZbHbL97MXLMvi0KFDzM7O8pd/+ZdkMhlarRajo6PrBmvbthkaGuLs2bPccccdWJZFpVLBMAxGRkZ6x8VxTLvdptls9rZWuZmYYZWkPwmANhKo2MeK6zj+DAl/CpTaXAgVEkT3uy9/+cuXTRc+fvw4f/qnf7pHLRJCCCHEzUBrzfz8PFNTUywuLtJqtUgkEuTzeYaHhxkdHaW/v590Og10Rxar1SqVSoVUKsXY2NiGt/OIouiS4jerJRKJqwbflTWTs7OzmwqinudRKBSo1+uMjo729gO9nq1sazI7O0sYhhv6PgwODlKpVDhx4gS33XYb9Xq9931dYRgG2Wz2ug3p18oKK6S90yS9CySCOaxoCY0JKgE6AGXgWQcIrWG4xj1Ub1b7LoiuXlwt4Ad/8Af5wR/8wWt+vdZ6G1sjhBBCiJvF4uIiExMTlMtl8vk8Bw4coNVqUavVOHPmDGfOnKGvr498Po9pmr0iQvV6nXa7zejoKHfeeee602W11nQ6Her1OpVKhUqlsqHQuZZEIoHjOExPT3PPPfegtSaO46uGyvn5eSqVyrYWO9oPLMvilltu2fDP1aZpMjY2xvz8PLZt43keQ0NDu9DS/csKl1YF0HmMuIVvjuAlD6J0iAJiw0ErmZ58rfZVEE0mk5TLZYaGhiSMbgOtNeVy+brc3FcIIYQQeyeOYxYWFlhaWmJoaKg34rh6RMx1XarVaq8aq1KKRCLB4OAgAwMDFAoFvva1r/Hggw9yxx13AN2tUer1OvV6nVqtRrPZpNPp0Ol0ALZU/Cafz1MqlfB9v1f59sEHH1x3HaPruhQKBVzX5cCBA9d83f1sMz9P5/N5lpaWmJub6/1y4WZkhWXS7mmS/koA7eCbw4TJY6C608JlmGd77KsgevjwYWZmZlhcXNzrpuwI13V3PRQmk8ktV5ATQgghxM2lXC5TqVQwTXPdrUKSyWRvb8u1HDt2jPn5eU6cOIHruiilqNfrveq3YRj2RkBHR0exbXtLAxHpdBqtNS+88AKdToepqSmGhoZ6IXg113U5f/48lUqFbDZ704au1ZRSHDp0iEKhQF/f9b0/5bWwwiXS7ssk/UkS/jyG7uCbo4TJ470AKrbXvgqitm1z/PjxvW7GjnnyySd54IEH9roZQgghhBDr0lqzsLBArVbb0vTMlX0qFxYWeOmll3Acp1ftdmBgAMdxtnV7FMdxME2T2dlZoDvd9Pz585cF0UqlwsTEBIuLi0RRdNNPQV0tkUhw5MiRvW7GrrPCJQYa/x3Hu4ihPQJrGNeSALrT9lUQFUIIIYQQ26PT6TAzM4Npmpuaerq4uNgbDd3qTK6VMBoEAYZh7OjIo2EYDAwMUK1WOXDgAJlMhkKhQKPRIJfLobVmZmaGmZkZyuUyiUSC4eFhWQ52s9MhufYJHP8isXJwnVslgO4SCaJCCCGEENepKIqo1+tEUUQul8NxHDzPo1KpMD093dsPsr+/n3a7TavVIpPJrHmu1VVyq9Uqg4OD29bO3dpvcnh4mIGBAUzTJJFIUCgUuHDhAnfffTcTExMUCgWq1Sp9fX3kcrldaZPY3zLuKZLeBOgY3zkslW93kQRRIYQQQogd5Pv+tu676XketVqNarVKtVrtBcxkMkk6nSaKIjzPo91uk0qlOHbsGMVikUajwZNPPsmRI0c4duzYJducaK25cOECc3NzlMtl+vr61l0but+tjLratk0mk+H8+fNEUcTi4iK+7zM6Oroj+6CKa2OHixhxGy9xy7acz4wapLxXVr5Co0Ct/GkQGTk8uztDIOWdI+2exA6LdJzbJITusg0FUaXUY8BvASbwe1rr33jV8z8D/CwQAU3go1rrl7e5rUIIIYQQ142VqaCzs7MkEgnuuOOOaxqF01rTbDZ74bNer9Nqteh0OsRxjOM4OI5Du92mXq/31mEODQ31tiQ5fPgwpmmiteall15icnKSQ4cOcfz4cfr6+piYmGBubo5arcbw8PANU3G/r6+Pubk5pqenSSQSjI2Nbeu6VLFBOsQOyyTCInZQBDSBNYwVVXGCKRLBPIv9/wOes/VaMWn3JfKtb2CHZaAbLDUr33NFrGwCe5zAGiYRLGCHi/jWCNq4Mfr89eSqQVQpZQKfBt4FzADPKKW+8Kqg+R+01r+9fPwPA/8b8NgOtFcIIYQQ4poFQQB091lca22g7/s0Gg0GBgauObAEQUCr1WJhYYFCocDS0lJvveaBAwfo6+sjnU6TSqVIJpMkk8k1106GYcj8/DyLi4s0m01arRau62JZFo7jMDw8TCKR6N3HwMDAFdtlGAZjY2OMjY1RKpU4e/YsU1NTjIyMEAQBzWazV732RpHL5Xrv0+oRYLHzzKhGIihihwUSwTxWVMWKqphxEyN2AU1sZNDKxA4KDNa+xPzoz27pmkbUJOldwIwatJL3AqDQsPIRx1i6geNfJOmdJ7QGcJ1biY3rc/T/ereREdGHgXNa6wkApdTjwHuAXhDVWtdXHZ9BttcRQgghxD5TqVQ4e/YsnU4H0zRxHKcXBG3bJgxDyuUyjUaDsbEx7rvvvk1fY2ZmhunpaVzX7Y1Yjo+PY5omi4uLTE1NEYYhhmH0rp1IJMhkMvT39/eK6nieR6lUolKp0Gw2SSQSJJNJBgcHsaytrawyDIPR0VGGh4epVCrMzc2RSqUYHR3d8rn3G6UUw8PDe3Z9I+6gdIhWBhoTMNDKAMwbchpo0juPE8xihSWsqI4Z1bCiGuiI2EgTmn149hG0kUDpAKV9YpXGNgdJu6dx3At4yTVGRXWMHRZJ+hexwxK1zJuJrMvXMKe8cyTCBUJrsDfCeUkoMcAnh28fBK1vyO/B9URpfeXMqJR6L/CY1vojy19/AHij1vpjrzruZ4G/DySA79Nan13jXB8FPgowNjb24OOPP74tN3G9aDabvU2ghXg16R9iI6SfiCuR/rE+3/cpl8vEcYxt28RxfMmH1hqlFIlEAq01rusyPDy8qam0YRhSLBYBeuF2vSqxcRwTRRFBEBBFEWEYEoYhWuveSKxlWaRSqUtGPbciDMMbLmjuWzqiPzpLPpqgu3Lt1d8/hUZ1w6lSoDWKGNcYpmK9hlCtXVBqPYYOSMezNI2jG674ut39IRUtMBKeINIWvsriqxyuGiQ2UstTY9fvw0pHHAi+imcMUnDe1nvcjmtk4jnS8RyW7qA1oCNQJvPOOy55nwztc9B/Ap8MS9a9V7zeDSP2sDIHMKztn1a8Xf+fvOMd7zihtX5oree2rfdprT8NfFop9RPAPwA+tMYxnwE+A/DQQw/pRx99dLsuf1148sknudnuWWyc9A+xEdJPxJVI//gu13Wp1Wp4nodSiqWlJcIwJJFIXDaFVWvdC4YrU3ZnZ2fpdDrcddddOI6Dbdskk8nedNq1guFKURzLsujv7990m+M4ptPpEEURiUTiikH2WhQKBcbGxrbtfDczI2qSCBdQWhMbCbRKEKsEihgrLJP0p0l6F7DDebRK0A1FMaCXQ+fKdNEYpVdG7TR2/ByuOk09+7349qENr13MtZ4m2/42tWyadmpjI/nb2R+MuEN//Vtk3AUCc5jQzgKN5Y+Nsf2QtPdVhhMKN3EcK6qQCOewg0WsqEFspAjMQSIjTb7zLCOqzvzQR4it7i+LMp0XyDfrGHGJEecmCKFA1Jxi+LW/SH78tdt+7t34/2QjQXQWWL2z7eHlx9bzOPBvttIoIYQQQohrobXm7NmzLC4u9gr6RFHUmwq7VkBUSmGa5iWh7+DBg0xNTfHcc8/1Hl+ZSrtynnw+TyaTIZ1O90ZDPc+75m1PDMNYd2sVsfeMqIkTzOIEsySCOaywjBXViVWC2EiilQ0Yy2sgO8TKxnVu39T6QxW7pN3TjFT+E4E5QGgN4jq30nbuxrcPoo3Lq/0mgjlS3hnS7ktolbhqELXCErnWUzSicWAbgqiOybWfJelPEqsUoX1tU6EDexxPt8m2T5BrP0VkZEDZBEY/7dTh5fe3q5H6HnLtExwsf4Zy3w9jRRVS3mnscAnXuW3r9yR2xUaC6DPAHUqp43QD6PuBn1h9gFLqjlVTcd8NXDYtVwghhBBipxUKBRYWFqhUKqTTaUZGRlBKobXe1BRXwzA4duwYURShtSYMQ1zXxXVdGo0Gs7Pd38mnUinS6TSO41Cv18lms1KV9QZixB0cf+pV4bMGsLze8QBG7GNoDxU3UUoRGRl8e5xYpTa9BlEbSVrp+yEOSEQl7HCRlHeevPF1fPsw7eTddJzb8O1xUBYqdsm2T+D4U0Rmf3fbkuWpq2sxozp9za+R7TzPiD+C9ga3VKlWxT759lOk3FOYcZOOc+c1nwuluiHSuW15/Wi4boiPzSz19BvJuM8ztvT7+NYBrKiGZx+RwkPXkasGUa11qJT6GPBlutu3/L7W+iWl1D8CntVafwH4mFLqnUAAVFhjWq4QQgghxEZ4nke5XO5Ng/U8j06n09svMwxD8vk82Wy2NyJpmiadTofp6Wmq1SojIyO9rUu2YmU01LKsy7Y0WamO2+l0qNfrUpn1BqJin7T3Cin3lW4AjapoFJHVt1xlNd07NtqJBhg2vnEA3z4AWmOHiyTCOVK1VwjNfjz7MIE9ghXVsMISsUoQJEbIdF4k6Z3DTd51+SnjNn3Nr5F0zxKqLIHKcGTp/6Ccfzexura/K4mwSMo7gxnVcBPH1w3Am6WVfckI6JrHmEma6Ydx/IsY2qPj3LHmiLHYvza0RlRr/SXgS6967FdXff5z29wuIYQQQlxHoiiiUChQKpU4ePDgliqVzszMcO7cOYIgIJ1Oo5Si3W73CvtAt9CKbdu9bVByuRyWZfUC7HaE0KuxbZv+/v5rWg8q9i+lA/ob/zdJfwI7LBOa/ZeFz91tkCKwRwnsUYgj7HCBlH+BlH+eWDndEdjEETQKUGQ6L14WRFXsk299g5R3BgDPOUYpupMj8WmGq39KfJXQtz6DyEjhOrdfNTjuCKXwnGO7f12xLaR0mhBCCCGumdaapaUlZmZmKJfLlMtlzpw5w3333ccdd9yx6WmqruuyuLhIp9Mhm83SbrexLIt0Ot2rRKuUIo5jXNel3W5Tq9UolUqEYUg6nd7T7TrENtAxhnYxYpfQ7F+7CqwOsaIGRtwiMrNERn7D1WKvJt15iaQ/iRk16Dh3oo2d/6XGhhkmQeIQQeLQmk8H1hBZ9yRl3vvdB3VIvv1N0u5pjNil49wGShGrBM30G1Cxx1Z2XtTKkW1QxDWRICqEEEKIa9JqtZienu7td2maJocOHWJpaYkTJ07g+/6m9+IsFovU63Uymcxl1W1XMwyDdDpNOv3dUao4jgG2ZasTsTfsoEBf82uYcQ1D+0RGjnr6YSIzhxVVu1NRoypWWMaM2xhxC4DI7KOafQeec8uWrm+FJdLuKeywTMe5fX+F0A0IrJFu+4N5guVpvbn2s6Q7pzDDOm7ytsumz15v9yhuHBJEhRBCCLEpvu8zOztLoVBgaWmJKIro7+/vhcIDBw5gmiYnT57k8OHDVwyUq61Unu10Ohw4cGDT7ZIiQdc5rcl2XugW3CFGY5GMJkh3TuInDmHELYzYw9ABsbKJlUOsEhjaJ+lfxA4XmRn7hWu4bkwimMOMWyT9SZxgCt8cuS4DWmR21yj3N56g1P9jpN1TpN2XscMSHee2vZk+K8Q6JIgKIYQQYsPCMOSll16iVCrRbrfJ5XLk8/nLRiGHh4epVqucOHGCt73tbczNzREEAbfeeutle2NqrWm32xSLRWq1Gslkclv3zxRbY0Y1Mu7LRCqFbx8ksIa3bRrsak4wRcKfBqDj3NOtogpYQREzbhIafcR2Zrka7aXXj/00Ke8cZlQlMvs3dd20e4pc6ykSYRGlfWLlECZGtumudldspHCd28i3nsIKK8RWFsefxXWOX5fBWtzYJIgKIYQQYl2VSoVyuczx48cxTZOFhQWWlpYIgqA38rkWwzA4cOAAMzMzPPXUU7iuS6lUYmFhgTe96U1oranX69TrdarVKq1Wi1arhed5jI6O7vJdivUk/Bny7adJeudJBAv49ii+NU4neSeefaS3jcgKM6ziBDNEZh+efWjjgVXHpDunSARz+PahS9YchvYoIVfuE6HZB2jSnZdpZN+y4ftTsUfaewUnmMa3xoiNdHf7j+t4ereXOEJg9pNxTxKHSdzEHhZaEuIKJIgKIYQQYk2VSoWzZ88yPT1NpVLh/vvvZ2FhgWazydjY2FVHLbPZLPl8noWFBfL5POPj40xNTeF5Hul0urclSxiGJBIJkskk/f392LZMH9wPEv4s/c2/wvEvEBk5GqkHSYTzpLyzZN0XCIx+AnscL3FLd4ps3CERFbGDImbcou3cRS37CH7i8PoX0SGJcBHHn8YJptGGRWT1bbqtsZFBK4dM+4VNBdG0d4ZEMEdk5AjtG+cXILGZo5F5M0r7aCVbmoj9SYKoEEJcZwqFAoVCgde97nV73RRxg1laWmJ2dhbP8+jr66NarVIsFrEsizNnzqCUolqt9qrXXo1SikOHDhFF0SX7cRYKBTqdDolEgoGBAZLJpBQY2m+0Ju2dwvEnCc1hArs7VdUzj+NxHOKQRFQg4c+S9M6hUGgMYjNDYPSjTZtc+wQZ9yUKg3+LTvLu5fPGWFEVOyySCAsk/HmsuI4VVTCiDh3n1mtrr1L49hip4CzEQXeU05+ikvtBMNb+hYmKXVLuK1hhmY5z57Vdd5+TECr2MwmiQghxHYnjmNnZWSYmJjhw4AAjI9fnOiaxv7Tbbaanp1lcXKRareJ5Xm+UMp/P09fXx8zMDBMTEziOw/j4+KbOv3rkNJ1Oc/z48e2+BbHNEsEcjj8D6F4IvYRh4RuHutNotV5zKqtnHybTeY6xpX9Hqf9voHREIpjHCitYUQUzbqLQhEaWwBggShzbUjGd0OzH8acYaP4ldrhItvMdAmuMZubBy45VsU+u/SyJYI7QzMv6SSH2gARRIYS4jrRaLbTWNBoNSqWSBNEd4roulUqF0dHRG7poThAEzM3NXbLus7+/n0wmg9aaMAx7I58HDx5kYWGBbDaLZcmPDze6tPcKiWCewBy7+sHrjWYrg1bqfjKd5xiufI7YyHWLARnpbvh0xrvrMbdJaOYBg2z7OygCVOyRaz91WRA1wyr51rdI+eewohqd5B3b1gYhxMbJ/yRCCHGdCMOQVqtFFEU4jkOxWOSee+7Z62bdcMrlMpOTkxSLRXK5HA8//DCJxI0xvS0MQ3zfxzAMarUas7OzLC0t0W63yWQyjIyM9KbIKqUumX67skeouH50C/GcIVYOrrPxUejuaOgU6JjQ2tjWO+s3wqCVegArWkKrBJGR2ZGKu91rWfj2GHZYpJ24g8jJkfbOYEQNYjMHQNK7QLb9LEn/AgCd5J2ypYkQe0SCqBBCXCcKhUJvxMo0Tcrl8l436YYSRRHT09PMzc1RLpdRSnHx4kU8z+PNb35zb4/M69np06cpl8torYnjmGaz2ZtqeyOP/N7ozKiB0mG3cqwyQGvssECufaJb7TZcwE0coxPejYr70EZy3XMl/BnyradJBHME1uj2VI9VitAa2vp5NqDj3ImXOExsZIjjFklvgmz7BPXs95LtPEfaPUXSu0hg9hHYB6/r6rhCXO8kiAohxHWg2WwyNzeHaZr09/fTbDap1+u4rksyuf4PlWJjOp0OExMTFAoFGo0GAwMDZDIZBgYGuHjxIl/5yld4y1veQl/f5qt57hfNZpNqtUq5XMZxHAzDYHh4GMeRtXHXHR1jhyUS4TwJfx47KmJGDSIji28fwIrqmHGdRFAgxsKzj+L4FxkIfPrLL9JIv4F26l5iI3PJadPuKbLt7yxXyc0TWoN7dINboBSx6t5XbGSIzBx9rW9gEJJyz2KHJTz7EJHVv7ftFEJIEBVCiL2mte5tiZFMJkmlUr0/TdMkCALOnz/P4uIimUwG27Z7U0WXlpY4ePDgHt/B9W1xcZGLFy9SKpWIoojx8fHeGshkMsmtt97KxYsXefLJJ3nd615HLpfDcRxs28a27etmJLFcLtNoNOjv77+uA/X1JulNkGk/R2CP00zff837OarYJREukAgWSPhz2NESVrSEEbe6lVG1QUIXyLiniFWC2EgTmEOE9jAAgT3Kgr6F0eDzjFYex2sepZF5kFbqdURGnoz7ApnO8yS9i/jWWO911zvfOkjKe4Vs+9ugYzrO7VKYSIh9QoKoEELsIa01k5OTzM7OUigUiKKIZDJJMpnEcRxSqVRvPejqNXsro1ilUkmC6DXSWnPhwgUWFhYolUqkUimGh4cv20bEtm2OHz/O9PQ0Tz/9NKlUilQqhWVZWJbFbbfdxoEDB/b19iNxHFMqlfA8j6Gh3Zkied3SMWZU3/KImRE1SXunSbunSHnnsVp/Ra79DM3U/QTWEJGZ6446mjlQ6/w4pmMcf4qkP4kTzGJGte42J7FPZKQJzT6ixC2XrnFcp4ItQKiytNIPYMQtkt55hqt/Qr71LTrOXVjREo4/jZc4SrS8nvJG4NsjmHGFWDn4iUM7tz5VCLFpEkSFEGIP+L7fmyZZLBap1Wq9dXqu69LpdKjVapTL5V44HRsbo1QqAd29GBOJBMVicY/v5Po1PT3NzMwM1WqVgYGBK64BNU2TY8eOEQQBnU4Hz/PwPA/XdZmfn+fOO+/kNa95zYaLGrVaLYrFIo7j7EqIrVarNBoNEonEdTOCuxOscIl86+uYcZvIyBEaGWIzg1YOsUqitEfSv4AdFGmlXkcz84ZNXyPpXSDTeR4rqi4HxzqufRSduI2Ud5bB+hcBi9DMEBm5bgVZcxDfHiGwRgnNAUBjxk1S3nkS/gyJYB5FTGhk8e1DREZ2/UC1gb4UGxnaqddB7JH2ztPXfJLQ7MdNHCM2s5u+531NWXSSr9nrVggh1iBBVAghdlmj0eD06dPUajXa7TYAo6OjvdFO27bJ5b47IqG1BrgsrGQyGSqVClrrfT0atx+VSiVmZ2epVquMjIxsOECuTMddrVwu89JLL1EqlXjggQeuOOLo+35vGnC1WqVer3P33Xdz3333YRg7N1JTLpdpNpvk8/kdu8Z+Z8Rt8q2vk3ZfxoyaKGKUDtDKAG0SGwm0clDaw4w7ZLxTBOYgXvK2DV9DxS7Z9ndId15AGwkilbpkKmgrfT9ojYpdzLiOFTUwozpJ/yKq7aGxCK0hIiONEXcw4w4aEz9xZGdGKQ2Hduo1oGMgXn9kVgghdoD8iyOEELsoDEMuXLhAsVjsFYtJJBJXDJLrPec4DpVKhVarRTZ7g41i7KBms8mFCxcolUr09fVteWuWoaEhMpkMs7OzPPnkk9x7773ccccdmKZJpVKh2WySyWRQSjE5Ocni4iKdTodcLkd/fz8nT56k1Wrx0EMP7cg2MUEQ9EbWb4TKvxumQ+ywhBm30Jik/HOk3HNoLFqp+7sjh1oDEYbu7jmpdEBk5tHKJts+wXjlDyn2/zjaSBKr5PJ02iyotUeV0+5pEsEMkZXHSxxbu11Koc0UoZkitFft0ak1RtzCDksYcRttpPCs4d2ZJqsMQKasCiF2lwRRIYTYRRcvXmRxcRHDMC7Zs/FarFTLPXv2LA888MB2NfGG5vt+r/BTOp3etgC/UtSoUChw4sQJCoUCo6OjlMvl3lYw2WyWdruNZVkcPHiwNwLqOA4XLlyg3W7z5je/mUwmc5WrbU61WqXVapFMJm+akfNM+zlS3jmsqIIVLaG0BjQahevc/t3pq0oBFrGywEhdco5W6vXk2k8zVvkssZEixiY2M0RGBt8aw7cPEJoDhNYAkZHDiNukvVewowrt5F2bb7RSxGYW70abGiuEEOuQICqEELug0WiwsLBAoVCg3W4zNja25VCQTCYZGhri1KlT5HI5br/99m1q7Y0pjmPOnz9PoVDAMIxtrxyrlGJ8fJxcLsfs7Czlchnbtunv7ycMQzqdDplM5rLpsblcjmPHjjE1NcUTTzzBm9/85m0tKLQyan6zFCly/Cky7gskvfPERobQyKFQaCCyBjdcrEYbCeqZt2JGTcDHjD2MqIkVlkm5ZzB0QGjmCc1+IrOP0Owj4c/im4PdKrZCCCGuSIKoEELsEK01tVqNhYUFlpaWqNVq+L7P4ODgthWMGRkZIQxDnn32WRKJBEePHt2W894IwjDENM1e4J+fn6dQKOB5HuPj4zs2OpjJZLj99tvxPG/Do5Crt4n5yle+whve8AaOHDmy5baEYdhbR3w97ReqYh87LBKZ+eXRxhZWVMWKalhxDTQE1iCh2U9o9qON5PLrXLLtb3erv9q3bH2vSKWIrO7U2GiNNporbQqXSOsOkZHGk8I4QgixIRJEhRBim2mtWVpaYmFhgUqlQr1eJ4oiMpkMw8PDWy5KY8RtrKiGbx8AYHx8nJmZGb71rW8RRRHHjx/fjtu4rpXLZS5cuEAmk+Gee+4hjmOKxSLVapXx8fEdLQwEYBgGqVTq6geuYlkWx48fZ2Zmhm984xvceeedHD9+nP7+/mtux8q0XMdxdmVaruNP4wQztJ27Ca2Baz5Pxj1JrvU0ioDI6AbBbr+vY2gXI2qhlUVodUcjA3MIzz6IoQOS/hSxSm09hF6FNhKExiihPbrqwfW3ThFCCHEpCaJCCLFNVvZqXFhY6FVEBchms2Sz2W0LArn2CTKdF1gY/CCxmUMpxeHDh5mdneWpp54iCALuvPPOdV9fKpVIp9MbLlwTBAFTU1NUq1UOHz7M6Ojovl1rqLVmdnaW6elp5ubm8H2fw4cPEwQB9XqdRCJxWdXb/cQwDI4cOUKpVOL06dNMTU1x7733XvO065UgOjBw7aFwI6ywQqbzPEl/kqQ3QZ/xBKW+H6GT2vzooIpdkt55EuEckUphh2Vi1a1oG5iDRGYWrRLLwXQJK1gk4c+Qaz2NNhLEKnltazS3wz79eyGEEPvRhoKoUuox4LcAE/g9rfVvvOr5vw98BAiBReCntdYXt7mtQgix59baKiWKIhYXF5mfn6dWq1Gv1zFNk76+PlKp1LaGNidewvEnSbmnSXnnaKW7RYqUUhw6dIiFhQVOnDhBGIbcc889l117pViP67q8/e1vv+r1qtUqk5OTlEollpaWmJiY4OjRo9x///17NtVTa02hUCCVSl2yzjOKIiYmJnpToQcGBlhYWODFF19kcHCQer2+pdHF3aKUYmRkhKGhIS5evMgLL7xwTUE0iiKWlpYIw7BX2Gq7qdgl454k5Z7F8WdQeLiJw6T8i4wv/QGL/T9GM/PGTZ0z5U+QCBcIjAF855Z1j4vNLP7qwj467labVbZsQyKEENeBq/5LrZQygU8D7wJmgGeUUl/QWr+86rDvAA9prdtKqf8J+P8D79uJBgshxG7RWuP7Pq7r0ul0qNfrVKtVEokEd9xxB7Zts7i4SKFQoFqt0mg0sG2boaGhHfvBvy86R8Kfw9QuSe9CL4hCN8AcOHAAwzB47rnnCMOQ++6775IwurS0RKPRYH5+nsXFRUZGRta8jud5TE9PUywWWVpawjRNjh07Rr1e59y5c7RaLd7+9rdv21rXjYrjmAsXLjA3N0e1WuXRRx8ll8vhui7nzp2jUCjQarUYGRnBcRyCIGBycpIoitBab3q67F4yDIP+/n6KxSKdTmfTba9UKrTb7Z2plqtDUt45Mu7LJPwZrKiKbw4T2sdBGTStYdKdk4xU/4SOc9fGp8nqkKR3DitcouPcsbk2KYNYKs4KIcR1YyO/MnwYOKe1ngBQSj0OvAfoBVGt9ROrjv8W8Le2s5FCCLHdarUa586dI5lMMjAw0AtUQRD0gmer1SIIAsIwxPM8fN8niiI6nQ7T09MMDg7Sbrd7W2OMjo7uyD6QK+xwESNexNABvjVK0r+w5nFjY2OYpsmLL75IGIbcf//9vTWRpVKJZrOJUopXXnnlsiAaxzGFQqFX9dXzPPr6+nrbnAwMDJBIJJiamuI73/kODz744K5N042iiLNnz7KwsECtVqPZbPKNb3yDN7zhDUxOTlIsFonjmPHx8d73c2BggKWlJQqFAgMDAxtuqxE1cYIZXOe27gjbHnEcB6015XKZw4cPb+q1i4uLNBqN7Z+Wq0P6G0+Q8i5ghwtEZo5O8q7L3qeOcye59jcZqn2e4uAHSHkTKO3RTr5mzcq1KvZJeWdxggViI90rQCSEEOLGpLTWVz5AqfcCj2mtP7L89QeAN2qtP7bO8Z8CFrTW/3iN5z4KfBRgbGzswccff3yLzb++NJtN2XRerEv6x86J45goirAsC6UUWmsWFxfxPA+tNXEcX1K8RimFYRiYptn7sCyrV4E1jmPa7TZxHJNMJrFte+fDmI4ZC76FiposWa+nPz6DE1eYTv0QsPa12+02jUajVyQpDEMWFxdJJBLEcUyn0+HIkSO90Oa6LvV6Hd/3MQyDdDq9brButVo0m02GhoYu245kO8RxTLVaxff9Xvgtl8u4rksymSSVShEEAZVKpfd9zWaza7bXdV3CMNzw3690NMdgeBJTd/CNPAX7zcRqb0JRFEWUSiUGBgY2NK145d8R3/dZXFzEtu0t/7uSiGuk4gI183ZQBrnoAgPhSarqOB3zIJr1Cz/lokn6orMExiAmHVTs0TEPU7QfAhQJXSMZl0jFJRK6iiIkIEXJfACtdne0/WbgxkmShrvXzRD7hPSHG0DsYWUOYFjb/3/Udv1c+o53vOOE1vqhtZ7b1kUUSqm/BTwErLnwSGv9GeAzAA899JB+9NFHt/Py+96TTz7JzXbPYuOkf1w7rTWe5xEEAb7v43le76PdbuO6LkEQkEgkeOihh6jX67z88svUajXGx8fxPI8wDIHudEjbtnvhZrcoHWDELSIju+b6tkzneXKtEhc6t3JH5ix2WCLtvoweeDdB4uC6561Wq8zPz5NMJjlw4ABxHGPbNul0momJCQYHBzl69CjVapVisdir7js4OHjV0d3Z2Vk8z+MNb3gDmUxmy+/BilarxcTEBFprisUirusyPj7ee250dLQXnnO5HJVKZXsCsQ7Jdp4n7Z7C8acARSI8yZhZoTjwE0TW9u47ulGe55FOpzf078PKvyMr05ETicSW1sVa4RJ9zZdJuy9TT/vUc29joP4U2fYcfY5DbNSufAKtybZnUcwQmP2AiRP834zZNSIzixUuYUdVzLiBRhEbGQLTYNA6fc1tFut7pX0vd6Vf2utmiH1C+sP1L2pOMfzaXyQ//tptP/du/Fy6kSA6C6zezOzw8mOXUEq9E/hfgLdrrb3taZ4QQlyZ7/ucPXuWpaWl3jTalSm0URShlOqNZNZqNcIwpL+/n0ql0puquVPrOTfKjGr0Nb+GE8ygMQnMIQJ7mNAcIDJzKB2Q6ZwkESzQMb8XVI3I6Fa8TQZTVwyi/f39mKbJhQsXaDabdDqd3j6muVyOs2fPUiwWCcOQKIrI5/MbrvA7NjbG+fPn+fa3v80jjzyyLe/F4uJirziS1prjx48zNzfHqVOnyGQyl4TQlfvbjgJEZlQj33qapHcOOyzhWwcI7UG86BC5znc4UP49FgZ/ktAe3/K1NiudTvf2At3I9yUMQ0qlEp7nMTQ0tKlrmVGVjHsKdEhoDpDyzpHyzmBFdYbqX0QR4/izxEaa2NjALx+Uopl6EEO3e+s3IyND1n2eSKWJjTShmcOzD8hUXCGEuMlsJIg+A9yhlDpON4C+H/iJ1QcopR4AfofuFN7itrdSCCHW0G63e0Gq0+lgWRa2bZPP53ujmqun3OZyOS5evEiz2cQ0zQ1vX7JjtMYOC+Rb3yLlncOIO4DG8Scx2h5gEZpZIiOHGTfwrXF00L2f2EijlUXSPU8j86YrXiaXy3HkyBFmZ2d7wRS6+4/Wat0RrUwmQzqd3lTxIcuyGBsbY2pqisnJSW655ZZ1g5Lnedi2ve7+nVEUMTU1xfz8fG97mf7+fpRS3HLLLbiui2VZWNb2V0N1vEly7WdJ+pOgQzrO7WijWxE4NnPUUw+T65zgYOkzLOX/GoE9QmRkiFWS2EjueIXWZDJJpVLpFcNaWlri4MGDa77XYRhy8eJF6vU6yWRyw99PFXtk3JdJea/g+DMkwgIxFrGZJlJZGqkHyXa+TV/zr9DKxnVu2/gNGAYx353eFSTGCVb23lxjragQQoibw1X/99Rah0qpjwFfprt9y+9rrV9SSv0j4Fmt9ReAfwZkgf+0/B/jlNb6h3ew3UKIm9xK9dbFxUW01r1qsVeSy+U4cOBA7wf5PaMjMu5JHH8KOyyTCBaIDWe5iMtyuNAaFbuYcR0rahCYQ4T2EATL51AGkZnrhqcNyGQy3H777ayuC2CaJoODg1u6lb6+Pmq1Gs888wyLi4vccccdl41Quq7LyZMnSaVS3HvvvZedo9PpMDExQbFY7BXXefUvCXZk1FrH5NonSHmncLwpIrMPP3H8sr0gtZmknn6YbOcFRqp/TGj2ERk5tOEQK4d6+s10Undvf/uWrUyRXlxcpN1uMzU1Rb1e55577ukd4/s+8/PzvYJNnU6H0dHRq59cxyT9CTKdkzjBDFawRGANUU+/ESPuoHRAZPaBUrRS95FxTxIag8TGFqsPSwAVQoib3oZ+jau1/hLwpVc99qurPn/nNrdLCCHWtbS0xPnz5ymVShiGwfDw8IbXc27XVM6tyHReJNd+BsefJjKSBOYgof2q0KAU2kwRmilCe2zN84RGP8lgChX7aOPq1XqvFtSvhVKKo0ePUi6XOXfuHDMzMxw9epTbb7+dvr4+4jhmYmKit63K3XfffckoXafT4eWXX2ZxcZEoihgbG9uRUc+1ZNwXSXdewAnm8OxDV95ixLBpZh5ERS5mXMOMW5hhGyuqk3ZPU8s+QiX3zg1PLzXDKin/HLGRoe3cfVn4Xc1xHJRSnDt3Dtu2aTQaPP/884yPj5PNZllYWGBhYYFqtYphGL1tfNYcDdUa0KAM7GCBbOcFHH+KRDBHpDJ0UneiVbcvxealU2+1kaSZfmj5HEIIIcTWyI7PQojrhuu6zM7OUiwWKZfLJJPJ3vTN60UimO/uvRgs0EnetaWRpcjMgB+T9M7TSd1z9RfsEKUUw8PDDA4OUi6XOXPmTC+Q9vX19aZOB0HAwsIChw4d6r22UChQKpVQSjE2NrZr30vHnyTTeREnmMN1jhMbG5umrc0koZkkXH0u7yIDjf9O0p+k1PfD+Imj677eiDtkO98h6V0gEcyRCBepZB+lkv+Bdaf4GoZBKpWiVqvhOA633HILU1NTfOMb32BsbKy3X2g6nSafz19xlLuv9TUcfxKFBh2TCObRgJs4tvE9OK+jv29CCCH2LwmiQoh9LQgCqtUq1WqVpaUlKpUKvu+Tz+fJ5XJ73bxNMcMq2fazOP5FfGt0y9MbQ7MfrWyGa19gNnGY2Nzb98MwDEZGRhgaGmJxcZHTp0+TyWR6U6cvXrzI9PR0L4gGQcDi4iKdTmfdNY87wQrL5FrPLH8fDmw4hK7Hc27Bt4bIui9ysPQZKrl3Us++Fa1sEv4MdrREYA6CMsi2T5D0JrCiGr45jLYMBuv/DSuqUOr/sXVHVPP5PIVCgbGxMRKJBIcOHeLixYsEQUAqlWJ8fBzLsigUCuu204xqOP4kKfc0WjloZRKYI4TWkIRLIYQQu06CqBBiSzZayXMzPM+jWq1SqVR6oz3tdpsoisjlcgwNDe3INNOdYoeLpNxXSPpTJIJZYpUgtEe2fmJl0Ug9QL7zNGPlP2Bh6H9Em3tfedQwDMbGxhgZGWFpaYlkMkkymSSfzzMzM9PrM8VikWq1SiqV2lSRpC21Le6Qb32TpD9BaPQR2ltbI7tCm1ka6TeR8l5huPqnJL3zuM6tJP2LJP2LxMokNIexoiqxsmkn7wFlEgKRkSXf/hZWVKU48DeJrMvb1N/fTy6X671PqVSKO+64A631hqcyJ/0p7HAR3zpwxUrLQgghxG6QICqEuGbFYpHp6WmOHDmyscIoV+H7PhMTEywtLdFqtWi320C3UM3g4GBvrdx1QWsS4Twp9wxOME0iKGDE7eWtWdZe83lNlzFTNJIPkOucYKzyRxQGP7BvtsFYWb+7IpvNUqvVKJVKDA0NUSwWabfbjI1t3/txRTrshlDvfHebHPvA9p5fKTrJu/GtMTLuS6T8SSLDwbMOYmgXM1paLjp16S8hQnuEhvEGsu3vcLD0OxQHfxJvjem9rw7rmwrvOsbxJzGjOr6zc4WVhBBCiI2SICqE2LQgCJiZmWF+fp7Z2VlmZmZ497vfvekiM67r0mq1GBgYII5jzp49y+zsLK7rkkwmGRkZwXGcHbqLHaJjnGCatHuGRDCLHRQwCAjMIdzEsR2pFhpbeZqp+8l2nme8/PsUBj945fV+Wu/JVMxUqjsV+dy5cywtLVGtVkkkEti2vSPXUzpAY/XuNe2dIeWexYzbdJzbd+w9iKwB6um3YMYtIjO7oevEZpZG5o1kO99mvPS7LA78OO3U67atTXZYxA6KaJXcUGErIYQQYqdJEBVCbIjv+5TL5d56zZURy8HBQebn53nppZd4/etfv+Hzaa2ZmJhgZmaGTCZDf38/8/PzBEGwoa1Y9h0dkvQnl0dA57GDBVBqeQ3e4I4Hv8gaoJH+HnKd7zBe/rcUBj9MZPWt0c6YgcZ/JzCHaGYe2tE2vZplWWSzWaanpymXy0RRtC0j6Wtx/GlyracJrEFquXeAjkh657DDBTrOHaB2eCqwYRAZm1uzq40EjfTDZDovMLb076lnH6GefgOBNXz1Fy9TOgIdXvZ40r+IHZYIzKFNtUkIIYTYKRJEhRDriqKIarVKuVxmaWmJRqPRmy6bSqV6W214nsepU6c4duwYfX2Xhx+tNfV6nUajQX9/P9lslsXFRUqlEq1Wi2q1yuzsLOl0mtHR0f0ZQrXGiirY4SKhNUhgLU+v1CEpb4KU9wqOP4cdFomVjZ842N1/cRfFZp5G6iFy7Wc5UP5d5od+isi6NHjY4SIJf5Y+/yu0Uveit7of5CaNj49TqVTIZDKkUqntn2qtNWn3JbKdF0i5p7DiJq3kfZi6QyIoEBupfTN1eU3KoJV6PY5/kb7GE2Ta38GzD204ODt+RP/SWtu2xJhxB9cZ2OYGCyGEENdGgqgQNznf9wFIJLrT9bTWNJtNyuUypVKJZrNJo9EgjmNSqRSjo6O9Y1cMDw9Tr9f55je/ySOPPNKrlFqv16lUKiwtLdFsNqnX62iteeihh3r7Ho6OjpJMJnFdF9u2d61ojdIBjj9DaPYRmv3fnTKrw+4ekXELM2pixt0PK6xgRUvYYRmlfRrphwnsEZLeBImgsBxAk7iJWza+DcYOiM0M9fTD5DonOFj6DPNDP33JPqRJf4pEWMAOS+RaT1PPvX1X22dZFiMj21CoaQ1KB+Taz5ByT+P4s/j2QSzvFQbq/w0/cRg7LOJb27wudCcoheccw7OP4gQXSQRzKDYW2Bt8D2P+t9c6KZ49viNTw4UQQohrIUFUXLfCMNy1je9vVL7v89JLL1GtVjl48CD5fJ5SqUStVqPRaOB5Ho7jMDAwQDKZXHf0yjRNjh49yuTkJE8++SR33303tVqNZrNJs9nE8zwSiQTpdJpyuczXv/51crkcjuOQTHZHp1b+3C1p92XyzW9ixG1Ca5DI6IZHQ7uo2OsWl4mbGLGH0gEKCI0MsZHF1D5D9f8L3xpD6YDIyOA6t255G5Dtos0UjdQbyHWe5WDpMywM/hS+c3g5fE9hxC6BNUp/86u7HkR3ihE16Wt9k6R3Bjuq4jrHiI0MHe2Sbz9LU3soHe/6KPWWGAaec3xTL2no22in3B1qkBBCCLF95Kd4cd1pt9vMzMxQKpU4evQohw8f3usmXZfiOOb8+fMsLi7SaDRYWFggl8sRRRGmaZLJZBgeHt7wNFnHcbj11lu5ePEizz33HIZh4DgO6XSakZGR3nny+Txzc3O0Wq3efpLbTmsM3cGMWxhRa3lUs4Vvj+MlbsGI26TcM9jhPLFK4XgXUOjuS5WFVgliZRMafcRWGm04aLW6oM5BOvGtWFGFyBpAq/1X/EWbDo3Mw+TaJzhQ/l0Whj4EyuhOLTbzRGaOTOckKfcVOsm79rq5W2IHC+Rb3yLln4c4oOPc3vt+BfZBkv4UKe88rn1Y9ssUQggh9gkJouK64fs+s7OzFAoFKpUK9XqdmZkZ3vKWt0gYvQbT09MUCgV83+fo0aPEcUyz2SSdTl829XajbNvm9ttvp9PpkEgk1pxmq5Ti0KFD27r/aMKfJRHOY8QuZtzCCisY2u1+xB2MuI0RuygiFgY/hBW3cII5InMQL3Hk2i5qJAiNXdp25BppZVNPv4Fc59scKP9bGuk3YEclPPswkZFFK5vB2pdohIt73dRrptAkglmS3gVilcRzbr9k+qlWNm3nLpxgjtDeeNEfIYQQQuwsCaJi34uiiIWFBebn56lUKrTbbbLZLMePH2dmZoZvfvObvOlNb+LIkWsMFDegKIowDGPdoNdoNJibm6NWqzE2NoZhGBiGQX9//7Zcf2WbjivZrhCack+Ta38bx59YDpsxsUqAcoiUhVYOvnUArWzS3mnGl/6QdvI1mGGVTuom2E9RmTRSD5JpP0e+9U0iI92t5qoUHed2Ut45ErXCXrdyS2Jl41mHCBNrV+AN7VFCe2eq8wohhBDi2kgQFftauVxmamqKSqVCo9EglUpx4MCB3kjb0aNHmZ6e5hvf+Ab33nsv99xzz64Vu9kLcRxTKpVIp9Nks2sXxFlZ9+m6LocPH2Z0dPSSvTi11kxPT7O0tEQ+n9+xPRx3nI7Jdp4j7b5M0pvEt0YJnX5Q6/+z1ky9nlz7GTKdF3DtQ6+abnsDUwat9P0k/UnC5RAKENhjBNYNEtBkyq0QQghxXZEgKvatMAw5f/48CwsLJBIJxsbGLgtNSimOHj1KsVjk+eefx/d9vud7vmePWrxztNaUSiXm5uZYWlrCdV3e8Y53kEwmaTQalEolDh48SCKRYHJyksXFRarVKhcvXmRwcJCDBw9y6NAh+vv7WVpaolwuE8cxudzm9jncN3RIvv00KfcMiWAWL3FoY0VolEUj/TCJYIHAHt/5du4nysB1bl3jcQlwQgghhNh9EkTFvlWv12k2myQSiatu9zA6OkoURUxMTNxQQVRrTaVSYXZ2lkqlQrVaRSlFrVbjmWee4YEHHuDMmTPMzMxw9uxZbr/9dgqFAq7rcvz4cXzfp1wu8+KLL3Lu3DlGRkZIp9NUq1UGBga2fw/HXWBGdbLtb5N2X8GOSrj2kc1tl6JM/MQOFUkSQgghhBAbIkFU7Fu1Wo12u00+n9/Q8YlEgkajQRAE1+9001Xq9Tqzs7OUy2UqlQqGYTA0NEQymSSbzXLx4kWgu94zkUhQqVR4/vnnMU2ToaEhDMMgmUxy6NAh4jimWq0yPz9PGIbk8/kNrePcT8ywSso/113T6M9ixD4d51a04Vz9xUIIIYQQYl+RICr2Ja011WoV3/c3HJgsyyKOY1zXva6DaKvVYnZ2llKpRKVSQWtNX18fmUymd0w+n6fRaDA7O8vAwABDQ0MMDw+zuLhIKpW6bE9OwzAYHBxkcHCQMAyvj5FQrbGiMk4wu1wVt4gVLmHGTQJrEC9xFNSNux5YCCGEEOJGJkFU7Evtdptms4njOBvex9Kyut252Wzu2trHdruNbdvbEnzjOObChQssLCxQrVYJgoB8Pk82m10zOB46dAjXdXEcB6UUSinGxq6+ncjK+7QdlA5w/It4iVu2rfCPHS7i+NMkghnsoIQdlTHiJlolCY0cfvKum6fIkBBCCCHEDUqCqNiX6vU67Xb7spG9K1kdRDeqVqsxMzPDgQMHGBwc3PDrwjBkZmaG+fl5DMPgjW9844Zfu5Z2u02pVAK6U21zuRwjIyNXHbnczPuz3cyoTr71TZLeOTz7EEv9P7Llcya9c+RbT+EEMxhxi1ilCc0+vMRRCZ9CCCGEEDcQCaJi34iiqDeaWavVcF2X0dGNby1hWRZKKer1+oZfs7CwwNmzZ3nllVc4fvw4+XyeOI4ZGhq6LJiGYUi9XqdWq1GpVKhUKpRKJcIw5P77779ki5TNqNfrnDlzBt/36XQ6jI+Pb+uo5bbSEXZYIhEukPLOk/QuYIWLpN2ztFIP4Dm3bOp0KfcVkt552sl7QBnkWs/g+BOExhBB8vgVt2IRQgghhBDXL/kpT+wb09PTTE5OYhgGlmWhtSaRSGz49Suv2+iIqOd5LC0toZQilUrxyiuvYNs2URRhmib33Xcfhw8fviR8tttt2u02QRCQSqUYHx9nZmaGubk5jh8/vul7rtVqnD17lkKhQC6XY2xsbF+u37TCJRx/Cse/SCJcxIqWMKMWgTVAM/U95NrPMFL9HDOjPw/qClOpddRb12lETTKdF8i1T9DX+hpe4hhWuEhgjhHaw7t0Z0IIIYQQYi9IEBX7QqfToVAosLS0BEAQBPT392/qHEopbNvecBAtl8s0m03S6TSDg4OMjIwQxzEAhUKBZ599lpmZGcIwpNPpoLXGcZxexVnDMNBaY5oms7Ozmw6irVaLM2fOUCgUSCaTvXWe+4URd3D8KZL+RRLBPHa4iBE3lqfL9l+yLrSTvJtM5zn6mk9Sy33fJedRsYsTzOAEszj+LL41RjX3drLuCzj+NJ59CFDd/UCtcQmhQgghhBA3gQ0FUaXUY8BvASbwe1rr33jV828DfhN4HfB+rfXntrmd4ga3sk9mPp9nYGCgFwg3K5FI9ELjlUKd1ppSqUS73e4V+FFKYZrd0bqDBw/29jFNJpOMjo6uOTqrlCKXyzE/P4/WmlarxdzcHLfffvtViyzNzMxQKpVIJpMMDAxQKBSu6Z63Ku2+jIp9Os7txEaaRDBH0p/E8aexo0WssIpWJqExgJc8suZazdAawLcPMlT7IqBoZN5EIphbDp8zWNESVlhBaZ9c9C0SwSwohRm3aCfv7u7tycHdv3khhBBCCLEnrhpElVIm8GngXcAM8IxS6gta65dXHTYFfBj4+E40UtzYGo0GxWIR3/cZGhoCuGqIs8IlnGCWtnPnJftI2rZNvV4nDMMrVrJtNBrUajVM01z3uHw+v6E9TDOZDNVqlcXFRRYWFpicnMS27SuOkFYqFRYXFwnDkJGRkateY6ckvQmy7RNkOifxrTH8xCHMqN4d/dQBodmH69xKbKSveq5O8i60azJc/S+kvbOgA+ywAkRERh43cQuxkcEKF8m1nyU0B/Dsw7IFixBCCCHETWgjI6IPA+e01hMASqnHgfcAvSCqtZ5cfu7ahrHETSsIAiYnJ6lWq+RyuasGUCNqknFfIuWdx/EnydljFAY+gDa6o5Ure4m22236+voue30cxywtLbGwsECj0SCbzW75HlYq17788svEcUylUmFycnLdIBrHMTMzM1SrVfr6+vZsOq4Vlsm2T5D0LuImbsGOSmQ6L3a3SLHGiMx+2GTb3OTtRGYGK1ggNnK4iaPERuaS84T2KHUjgx3VCO2hbb4rIYQQQghxPVBa6ysfoNR7gce01h9Z/voDwBu11h9b49g/AL643tRcpdRHgY8CjI2NPfj4449vrfXXmWazuS3B50ahtaZcLuO6Lul0+opbkRg6IB+dJxtNYuiAphonUBmGopfwjGEKie8lVjau61Kr1Th48OAlVWyjKKLVatFutwnDEIBUKkUqldqWeymXy0RRRDKZRGuN53nccsstl4XMKIqo1Wq02+3Lrh+G4a5Vy1U65EDwVYzYpWi+fkMjnmJ/cOMkScPd62aIfUr6h7gS6R9iNekPN4DYw8ocwLC2fzu/7cot73jHO05orR9a67ldLVaktf4M8BmAhx56SD/66KO7efk99+STT3Kz3fNqWmt836fdbtPpdKjVakC3aM/o6GhvfealL4pJ+hOkOy/hBNPYYZnQHCRnt0H5mGGSbOfrjFoNFvvfSzvqp9PpcOutt3LHHXfQbDYpFouUSiXiOEZrjW3bvYJD28VxHIrFIuPj4xiGwfT0NHfccQeHDx/uHbMyUqq1xrIsRkZGLll3WigUeutVtyrlnkUrCzdxZM0tUNKdl+hrVjCjBn3OxKZHPsXeeaV9L3elX9rrZoh9SvqHuBLpH2I16Q/Xv6g5xfBrf5H8+Gu3/dy7kVs2EkRngSOrvj68/JgQV9VsNllaWqLT6dBoNHBdt7dfZhAEGIbB2NjYOiFU0998kqR3nkQwT2hk6bxqTWhkDdJM3U/WfRGrVGK+72/29hJdXFzk3LlzVKtVPM8jk8kwNjZ2xbWj16q/v59cLodpmsRx3Aujhw8fJgxDpqenmZ+fZ2lpCcuyGB8fX/uer0THJP1J0u4pIiNDLffo8uMaQ7e7U2ABx79Irv0tUt55PPsgrdTr6Th3EloDABhxm7R7CjtcpOPcLiFUCCGEEELsuo0E0WeAO5RSx+kG0PcDP7GjrRLXJa01MzMzGIZBLpejUqn0wpfrur3tVUzT7E3FtW173TWSVlTF8adIBPO4zvFe0Hq1yBqgnn4TufazHKj/J85Yf4NqtYpSisXFRbLZLMPDw1ddf7pVK8Fy5f5XKgFPTU1RKpVotVr09fVtfpqD1jjBDOnOyzjBNI4/hRXXCcwB2qnXkWs/Q9o9RTt5D+3kPWTb3ybpXyQ08jj+NGn3NL59gI5zB63U67DDRZxgltDsQxvbP5VDCCGEEEKIq7lqENVah0qpjwFfprt9y+9rrV9SSv0j4Fmt9ReUUm8A/hQYAH5IKfVrWut7d7TlYt9ZmXq6sLBANpvFsiza7Tb5fJ7h4eFNjwDaYQErXCIwB9cNoSu0kcC3x7GDBRK2ydLSUm/fz7WKFu20bDZLrVbj+eefp9lsYprmNY2C2sECGfclHH8aJ5glxsBN3EbSP8do9T9RjlukvdOk3DNkOs/TSr0OK6wQGln8xFE8jkHskfIv0tf6Grn20/j2Icyo1t02RQghhBBCiD2woTWiWusvAV961WO/uurzZ+hO2RU3Ka01c3NzVKtVhoaGCIIArTXj4+PXXIAnESxgxY3u9NENiJWDQYhjadqdgFarxYEDB67p2luVTqexLItarUZfXx+5XG5Tr7fC8nIAnSThz6OI8KwDRFY/AG3jXvLtb9LffBKlI9qp12KFS2Q7z+GbI3SSd333ZIZDJ3knHe7ECookwiKedWDNtaNCCCGEEELsBvlJVGyLarVKpVIB2JYRSBX7JIJ5NBAbGysqpI0E6Jis7bKkFfl8fvPrMLeJaZrceuutaK031QYzapBe3p4m4c9haBffGiO0hi5Zy6mNBM3k63GCadzEcWIjjZ9I49sHUMSg1p6GHNqjhPbolu9PCCGEEEKIrZAgKrbF/Px8b/RvO9hhESuuXXVK7mqx6lagHcl0sPpeu7GiRDrEDpcIrJFNF+1Z2dM0MIdxk7dd/vwm16RmohkG6pM4/hRm3MC3Rgmt4+uGysjqp708QtqjTDR7E76FEEIIIYTYKAmi4pppralUKr3tUaA7JXU7JMIFrLBCYG189E4vB1ErKJNIJ65ydFfGPUWu9U1Ca4ha9m3EKgk6IjLz6wZAI27j+FNkOidJ+hcw4xYXx3913eOv3vCYbOc7OOHzpNw5IjNPO3kPKAmUQgghhBDixiRBVGxaEAQsLi5SLBap1WrU63W01gwODq5bAXcj7KBA2n0J3zpIIpjH0B1CM7/h18fKQSuLRFTc2At0jONfIOlNYnROkXJPE1ijKCICc4ilvr/WHZHVMVa0RCJYIBHMd0NyVMMMKyhirHCJRDCNn7hl8zetI3LtZ8h0TjLDGL6tiZa3WRFCCCGEEOJGJUFUXKJYLNJoNDh27NhlaxubzWZv9LNer9NqtbBtm/7+flKp1JZCKDom236OfPtbGHGbwBomUsnNjQoqg1g52GF5Q4cnwgUSwSKh2YebegAnuIgVllHEpN1TOP4M9eybSAQFrLCMFVWw4iYxFpGRwXOOozGxw2+S7pzafBDVEfnWt0i7L5EIitSttzJuBZs7hxBCCCGEENchCaKiJ4oipqenmZiYoFgs8vDDDxPHMbVajcXFRZaWlqjX6/i+TyqVYmxsbGPrMDcg6V/ACaaIVALXOUwiLBJY45s+T2ymsaOlDR3r+FPY4SKBOQyGiefc2nvOjW4h5z7HUO3/QiuLWKUJzTxt+xDacC45T2jmybovUu17DHSMGdV71W2vJOWdI+2ewg6LdJxb0e7O7nMqhBBCCCHEfiFB9CYWhiEXL15kbGyMbDZLuVymVqthmibnz5/HdV2SySSdTodWqwVAJpNheHh404V4rkTpgLT7MnawgJe4hdjM0rnG6amxSmGH86DDK25PomKXpD+F0i7hGqFRmynqmTdjxC1ilbri+s/QHCEZTKCiFmnvLNnOcyzlHyOw1w/SKnZJuy+TCOZxneNoI7mp+xRCCCGEEOJ6JkH0JjY5OcmFCxd45ZVXeNe73kWxWKTZbDI+Pt5bB5pIJEgkEgwMDJBKbWwblc1Ku6dx/Gm0kSI2s1s6V2w4GDrEjNpE1jrrS7Um5U9ghYuExvpFibrnu3rV3tDKg6/pa32DRLhItv0cgTnAUv971n1Nxn0Zx58mMrLExvYUeBJCCCGEEOJ6IUF0BwRBQKvVor+/f6+bsq7FxUUKhQKNRoN2u81TTz0FdLcccRwHx3HIZrcWCjfC8S+S6byIHZboOLdv+XwrlXPNaOmyIKp0gONf7O7RGcxjh2Vc5/iWrxkZObSyyLVPLLfBINt5Yd0gaoVLpNwzWGGVTuquLV9fCCGEEEKI640E0R2wsLDAuXPnuOOOOzh8+PCWz9doNJicnCQMQ6C7bYrWuvf5wMAAt912+T6W63Fdl4sXL1IulxkZGaHT6XDx4kVyuRz5/Mar1G6JjkmEBXKtp3H8C/jWwW2ZnhorB9DY0RI+x4Dufp8p/zxJb4JEUMAOi2hl4VsHN7VP6bqUQWANkwgW8BIHcRO3kvLOYAUlQnv4u8fpmJR3lkznBZLBRQJrEK22Z42tEEIIIYQQ1xMJojugVqtRKBRYWloin89vOdzNzc0xNTWF53m9x1Yq1IZhyLlz5zhw4MCG9vCM45iJiQlKpRKpVIp0Ok0qlcJ1XeI43pFRUKUDzKiGtfojXMSMmySCIqHZT2gPbsu1YpUAFFawiBF3yLa/TdK/iB0WMKMakZHFdY5vTwBdxUvcgsbEs4+iCMGDTOcFavb3AWBGDbLtEyS98zjBHIHZT2Af2NY2CCGEEEIIcb2QILrNPM+jXq+TSqXodDp8/etf513veheWdW1vdbvdZmlpiSiKOHr06GVbpPi+z8TEBBMTE7z2ta+96vnm5uYoFouEYcjwcHe0TinFoUOH0FpvbQsWQMUeWlmgTIy4RbbzAknvAkbcwoybmHFr+RiTWCUJjD5Ce2xL11xNqwRaWTjhIrr9bbLtE1hRhdAapJO8Z8dGIGMjhZu8o9sGEkRGhqz7PLXcO0h558h0nifpX0TFLq5zbNuDsBBCCCGEENcTCaLbrF6v0263SaVSDA0NMTk5yfnz57nrrmtbC1gsFqnVamQymTVDYiKRIJ1ObyiI1ut1ZmZmqNVqjI6OXna+rYZQI24zWPtvmHENzz6CFdVJBBexowaRShIbKTz7CJGRumJF2y1RBrHhkAwugNJYUY128jWb2490GwTWGEl/kv7GX+AEUySCWSKjHz95yxWLIwkhhBBCCHEzkCC6zVaC6NDQUK/oz/T09DUF0ZXKta7rMji4/tTV/v5+5ubmKJfLDA0NrXlMGIZcuHCBUqlEPp8nkUhsuj1Xk3LP4ATT2GGBtPsysZEiMIdoJe/Z1SAYG2msqIrjz+Bb47seQoHuljB+TK71FCjw7Fu2XBFYCCGEEEKIG4UE0W2ktaZarRJFEY7joJQim81SKpWIomjT51sZDU2lUpjm+mEqk+lO87xw4cK6QXRycpLFxUVM09yRgkRG3CHlncWMqrRSr0djAdHOjXxeQaxSqLiItkxCe+33Y6dFRg7XuRWNgW8flFFQIYQQQgghVpGfjrfIdV3Onz/P3NxcbyuUlRAKkE6niaKIxcXFq55rdVj1PI/5+XlarRZ9fX1XfN1KuLxw4QJxHF/2fLFYpFAo9EZqd0LKO0simCc0+7vrMJXakxAK4Nuj+PYonr31isXXTCm8xFH8xGEJoUIIIYQQQryKjIheI601xWKR6elpSqUStVqNsbExXNfFcZzecalUCugWCbqSRqPB6dOnyefz3HnnnczMzLC0tEQqlcK2r15gp6+vj3q9zuzsLEeOHAG6U3unp6dZWFigXC4zMDBwxZHVa2WHi6Tcs1hRhY6z9/tixkaGTvI1e90MIYQQQgghxDokiF4D13V7U10rlQqpVIqRkRHm5+exLKsXBKE7WplOp5mdnSWXy615Pt/3OX/+PAsLC5w5c4ZGo4Hv+7iuy4EDG9viI51OY1kWr7zyCkeOHCEIAk6ePEmpVKLT6dDX17eh7V02TIck/WmS/nkcfxY7WCA082hj+9eeCiGEEEIIIW4sEkQ34dWjoEEQMDQ0RDKZBCCfz+N53mUjmNlslmKx2FvLuSIMQ3zfZ2pqimKxiG3bjIyM8Morr5DL5cjn8xjGxqZ1KqUYGhqiUCjQaDQolUq9No6Pj294JFTFLkqH6xbWMaImKf8CSe88iWABOyyhlSIwhwit4Q1dQwghhBBCCHFzkyC6QZ7nceHChUtGQYeGhi4JikqpXihdbWV67tLSEufPn8fzPNrtNp7nEYYhnufh+z5jY2MYhkEikcDzPLLZzVVZzeVyFAoFXnjhBQzDoN1uc+DAgU1Nx823nyLlvkIl9wN4zrHug1pjh0VS/nkc7yKJsIgVVYiMDF7iCJG59kivEEIIIYQQQqxFgugGTUxMMD09jed5DA8PX7IO9Gocx8GyLFqtFi+88AJxHGMYBpZlYZomlmUxPDzcC7W5XG7dabxXYlkW+Xye6enp3ojqZkKoGVZx/CkynZMk/WkWB34cgEQwTyKYxw4KmNolMPtpO3fLNFwhhBBCCCHENdlQEFVKPQb8FmACv6e1/o1XPe8Afwg8CJSB92mtJ7e3qXunUqlQLpfxPI/x8fENT5ddYRgGt956K8VikaGhISzL6lXV3W4DAwPU63WATYfZlH+ORFCk7dyJE8wxUnmc0OjD1C1ilSIwB3GtIakCK4QQQgghhNiSqwZRpZQJfBp4FzADPKOU+oLW+uVVh/1toKK1vl0p9X7gnwLv24kG7zatNXNzc1Sr1U2t2Xw1wzBQSm2oAu5WpFIpbr311t71NkrFHklvEjNq4KaOENgHSIQFYkw86xa0ktFPIYQQQgghxPbYyIjow8A5rfUEgFLqceA9wOog+h7gE8uffw74lFJKaa31NrZ11+g4xu9UUEpRq9WolmYwdYdcKo+K29d8XlN3MLbw+o1KrnxXY3/jr/EuYIcLBGa+t/+nb4/vQOuEEEIIIYQQN7uNBNFDwPSqr2eAN653jNY6VErVgCGgtN5JX3nlFR599NFNNXa36DjEq00Rhy5o0MSYSm95Om2obSwVbFMrt58iQqsEGpl6uxc6uo+Uqu11M8Q+J/1EXIn0D3El0j/EatIfbgA6xM6fxkxkrn7sJlWrVfr7+7f9vKvtarEipdRHgY8C2LZNtVrdzctvgoYoiV5+e5ShiLZhSWeMQaTirZ9oh8TYaLXx4kZie8UoOmpwr5sh9jnpJ+JKpH+IK5H+IVaT/nADUOC2fWhv/0BXFEU7ntU2EkRngSOrvj68/Nhax8wopSygj27RoktorT8DfAbgoYce0s8+++y1tPm69eSTT+7bUWCx96R/iI2QfiKuRPqHuBLpH2I16Q/iSrarf1xpRulG5mA+A9yhlDqulEoA7we+8KpjvgB8aPnz9wJ/eb2uDxVCCCGEEEIIsbOuOiK6vObzY8CX6W7f8vta65eUUv8IeFZr/QXg3wJ/pJQ6ByzRDatCCCGEEEIIIcRlNrRGVGv9JeBLr3rsV1d97gI/vr1NE0IIIYQQQghxI5LyqEIIIYQQQgghdpXaq6WcSqlF4OKeXHzvDHOFLW3ETU/6h9gI6SfiSqR/iCuR/iFWk/4grmS7+sctWuuRtZ7YsyB6M1JKPau1fmiv2yH2J+kfYiOkn4grkf4hrkT6h1hN+oO4kt3oHzI1VwghhBBCCCHErpIgKoQQQgghhBBiV0kQ3V2f2esGiH1N+ofYCOkn4kqkf4grkf4hVpP+IK5kx/uHrBEVQgghhBBCCLGrZERUCCGEEEIIIcSukiAqhBBCCCGEEGJXSRAVQoh9Riml9roNQgghrm/yf4nY7ySIbjOl1KG9boPYv5RSP6yUum2v2yGEEEKIG5618omEUvFqSqm7lFJ7mgUliG4TpdQ7lVIngJ/Z67aI/We5f3wT+LfAgb1uj9iflFI/pJT6LPBLSqlb9ro9Yn9RSv2IUurX97odYn+S/iFWKKUeU0p9GfjnSqkfBdBSnVQsU0q9Syn1FPAR9jgLWlc/RKxn+bdLNvCbwFuAT2itP7/6efmLf/Na7h8Z4LNADvgHwN8DbgG+ppQytNbx3rVQ7CdKqXcC/xD4VeANwP9HKfWE1vq/Sl+5uS3/xvqngV8CblFK/bnW+qt73CyxDyz/P2MAP4X0j5vaqp9J/3/Am4F/ChwGflwpdVJrfXYv2yf21nL/sOj+nPE3gV/UWv/J6uf3IrPIiOgW6C4fSAOf11p/XillKKVev/L83rZQ7KXl/tEE/r3W+lGt9V8AXwbes/y8BAux2juBL2qt/xvwO3R/efHTSqmM9JWb2/L3/yzwAPD/BmTUSwC9/2ci4BzSP25qq34m/W/A27XWXwC+AQTAhT1tnNhzy/0jAGLgcyshVCn1iFLK3qt2yT6i10Ap9XeBg8B3tNZ/vLzm7zPAd+j+MDkNzAP/WWv95b1rqdgLq/rHCa31f1r1uEH3t1DfA/yK1trboyaKfWBVP/m21vo/KqV+GPhZ4D1aa1cp9Vt0R8//Qmv9r/eyrWL3KaXeC0xrrZ9a/tpe/iECpdQzwG9rrf+tjJbfnJb//bgPeEpr/XurRzOkf9xcXt0XVj3+14BPAUXgr+j+TPLHMlvv5rKqfzyjtf6MUmoc+A1AAw8Bk0AF+Mryvxm72j9kRHQTVNfPA+8DngU+oZT621rr88DngbuXn/sJ4CTwo0qp4b1qr9hda/SPf6SU+rBSagR6oxoXgHdLCL15rdFPfk0p9SHgNDAH/Eel1BNAHvgvQG6viwmI3aOUGlVKfQX4V8Avr/reh6s+/1Xg7yulBiRk3HyUUh+m+3PGfwY+oJT6ZeDWVYdI/7hJrNEXfkUpdfvy0yXgMa31m4An6M6wOSYh9Obxqv7xk0qpfwB4dDNLAvhx4IeXn/8bSqmju90/5IebTVj+5rwD+Ada688BPw+8Xin1PyyPWLxfa/2K1roBPEf3B8n2njVY7Kr1+gfw2KpjvgHMLI9+iZvQGv3k7wP30+0rHwH+V+Cfa61/CvCB4/LD5M1Da12k+wuIx+jOrPk7y08prXW8/NvqPwNOAR9VSuWUUj++R80Ve+P7gX+6PI3/fwaSwE+uPCn946by6r6QYLkvaK2f1lqfWT7uFLAIhHvSSrFXXt0/HODvLNez+ajW+vTyzyQvAFW607h3lQTRDVr1m+hngUcAlr+xp4AHlVJ3La8HXPEuuiHU3dWGij1xhf5xBrhXKXX38nF5uiNfu/6XXey9dfrJn9HtJ28Abtdaf0dr/V+Xj3sQeGrXGyr2xKr+8a+Bl4E/B96tlDqwHEINvvv/9i8Cn6S7dnR81xsrdt2q/vEd4K8DaK2fBb4JHFJKvXXV4dI/bmBX6AvfAg6+qi8AfJhuPZPybrVR7J0r9I+vA8eVUm/VWrdWveRDQIruFN1dJUF0HUopc/lPBZcUljlHd6rcfctff4XuyGdu+fj3K6VO0l3b9SsyknFj2mT/6AOyy8fV6VaxG9vVBos9scl+kuO7/478NaXU03T/HfnPu9posWvW6x9a60BrHdItNHIa+Lsrz2uto+W6BP+G7vSq75E1xDeu1dPyV/378XXAUEq9bfnrk3RHzw8uv+Z24H9H+scNZRN9YY7v9oUPLv9Mehz4n7TWnV1ssthF1/hvxY8ppZ7/f9q7+5gr6zqO4+9vgPQALZtlFOuJP1pqZrmg1Ux8qrXFYrnWqoU2JsMtp3+YrQecBq1/0mWt9bAMnM2eLBuxnpZrSaZpoIysFAwt0UBkIo3NNfj2x+934Q2xixP3fV/n5jrv18bYOdc5935n57Oz63v9ftf3R1naf2lmdj55ZiF6mIh4Z0TcBHwuIl465ub/pqPUPZSlDe+OiOmZ+RfgVZQbfgEepXyZS+oSK/XIBOQDyhLuNV2OW90aR07eVo9vAZZn5oWZ2fkVSk2ulnxMa4rSahewFnhDRMyNiJPqqopdwCcy8wOZ+Xj3n0CTKSLm1wYjh3RXH3OiuQV4APhQREzLzMcoFzdfW4/vwXz0wjFm4RWUwhPKkstlmXlRZu7ocOjqwDh+K5p8PEQ511gyrHxYiI4REa+nXEX8LWUmYmWUrmM03QozcytlWd08yp5dUG78fbQevyvdv6uXxpmPR5q/M4wrTurOROQkM7dk5sZuR64uHCUf+zMzI2JmRMysj++gnEj8GVgPnJyZe8bc+6UeiYgrgNsoFyneW5+bBoecaO6lZGEm8KV6getE6rLLzHwy3TPyuDfOLOyqr7u/9qZQz0xQPjZn5l0dD/0QFqKHmg/8tc5WXUlpOLQoIuYARMSqiLgR2EDpaDg/IjYAuyn7Q6rfxpOPXw9lxBoGf0fU5mj5+DzwbaB5vJzSsOibwOkWGL23jXJP16XUi1RZ9gkFICKuBW6hzHquoJxUrq+Pb+p6sJpUZkFtepGPkd5HNCIWUa5I/ykz765Xqm8GPpyZ/4iIU4AlwA7gXspG0VfX2QwiYhYwPTOfHsoH0KQyHxqEOVGbCcjH+cAjzWP1yxHyMa0emgH8BPhlZn6lLrU7Ffg0sCLLtnHNErwXZenWr+OYWVCbvuZjJGdEI2JORPwMuIpyhWB1RLwnM/9O6T7XtDp/kLIk6sXA5sz8SGZubdZeZ+a/PXnsH/OhQZgTtZmAfDRLrH5jEdo/LfnYDxyot3BcByyNiJNqo6omHw+P+f04MNVOLPX/MQtq0/d8jGQhSmkcsz4zz8rMlcANwLJ6bD3wpohYUL/k7cC7MnMPlCsKaSfcvjMfGoQ5UZvx5mP/Ef+q+uLwfHwZWA4H9xqGch/x3cBlUBqT1P/D349eMQtq0+t8jEwhGqWF9cKImAncTlka1XiK0jkKyp599wHX1yVzpwKPRsQL4dCuVOoP86FBmBO1MR9qc5R87KbsS36w42XNwSrgUxGxB3hrPbEc3XuqesIsqM0o5WP6sAcwmSIiKG2sbwEOAA8DlwCXZ+YTETEjSxfLOZTpbjLzX8ANEfEa4DuU9dhLMnPfMD6DJo/50CDMidqYD7U5xnwcqO+bB6ym7AV4RWZuHsZn0MQwC2ozqvno7YxolP1ykrJB/PbMPI/SWWo38K36suaq8wXArfV9L6/PXQUszcwFmflgdyNXF8yHBmFO1MZ8qM0x5OPH9X3N3rLPUBpXnXc8nVjqf5kFtRnlfPRuRrQ2eFgJTIuIn1MaQOyH0tY4Ii4HHo+IszPzdxFxAvAk8FBEfAF4X0QszLKJ/JS7qVfjYz40CHOiNuZDbSYoH+dk5k5g55A+hiaAWVAb89GzGdGIOJuyN9+JwFbKl/sf4JyoN+7WddTXANfWtz0fuJiyBns2cH49OVDPmA8NwpyojflQmwnMx+5OB64JZxbUxnwUfZsRPQBcl5k3A0TEW4DXAVcDXwfOjHJj70+BcyNiLvBK4LvA9Zl5/zAGrc6YDw3CnKiN+VAb86GGWVAb80HPZkQpVxZ+GM9t8non8OrMXEOZ9r6sXl2YS9l757HMvCczl/TlC1Ur86FBmBO1MR9qYz7UMAtqYz7oWSGamfsy89l8bv+1CyhrqQE+DrwxItYB36MEoOlSpRFgPjQIc6I25kNtzIcaZkFtzEfRt6W5wMGbfxM4GVhbn94LfAY4DdiWmdvhkM1gNSLMhwZhTtTGfKiN+VDDLKjNqOejVzOiYxwAZgC7gNPrFYUVlKnt3zdfqEaW+dAgzInamA+1MR9qmAW1Gel8RA+LawAi4u3AH+q/1Zl545CHpCnEfGgQ5kRtzIfamA81zILajHI++lyIzgU+Ruks9eywx6OpxXxoEOZEbcyH2pgPNcyC2oxyPnpbiEqSJEmSpqa+3iMqSZIkSZqiLEQlSZIkSZ2yEJUkSZIkdcpCVJIkSZLUKQtRSZIkSVKnLEQlSZpAEXFNRFzZcnxxRJzS5ZgkSZpqLEQlSerWYsBCVJI00txHVJKkcYqIzwIXATuBfwIbgD3AMuAEYCtlw/IzgHX12B7gwvonvga8DNgHXJKZf+tw+JIkdc5CVJKkcYiIM4E1wAJgOrAR+AawOjOfqq9ZBezIzK9GxBpgXWbeWo/dDizPzC0RsQD4Ymae2/0nkSSpO9OHPQBJko5zZwG3ZeY+gIhYW58/rRagLwFmAb86/I0RMQt4B/CjiGienjnZA5YkadgsRCVJmhxrgMWZuSkiLgYWHuE1zwOezswzuhuWJEnDZ7MiSZLG5w5gcUS8ICJmA4vq87OBJyJiBvDRMa/fW4+Rmc8A2yLigwBRvLm7oUuSNBwWopIkjUNmbgR+AGwCfgHcWw+tAP4I3AmMbT70feCTEXFfRMyjFKlLI2IT8ADw/q7GLknSsNisSJIkSZLUKWdEJUmSJEmdshCVJEmSJHXKQlSSJEmS1CkLUUmSJElSpyxEJUmSJEmdshCVJEmSJHXKQlSSJEmS1Kn/AukacFRFQJMTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].cumsum().plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\"), title=\"B&H vs. Cum. Active Returns\", alpha=.4, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "* All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.\n",
    "\n",
    "* Any opinions, news, research, analyses, prices, or other information offered is provided as general market commentary, and does not constitute investment advice. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from use of or reliance on such information."
   ]
  }
 ],
 "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": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}