pandas-ta/examples/TA_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TA Analysis with **Pandas TA**\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 v1.20.3\n",
      "Pandas v1.3.0\n",
      "mplfinance v0.12.7a17\n",
      "\n",
      "Pandas TA v0.3.54b0\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",
      "[i] Loaded SPY[D]: SPY_D.csv\n",
      "[i] Analysis Time: 34.7742 ms (0.0348 s) for 5 columns (avg 6.9562 ms / col)\n",
      "[i] Loaded QQQ[D]: QQQ_D.csv\n",
      "[i] Analysis Time: 3.1180 ms (0.0031 s) for 5 columns (avg 0.6242 ms / col)\n",
      "[i] Loaded AAPL[D]: AAPL_D.csv\n",
      "[i] Analysis Time: 3.1966 ms (0.0032 s) for 5 columns (avg 0.6401 ms / col)\n",
      "[i] Loaded TSLA[D]: TSLA_D.csv\n",
      "[i] Analysis Time: 2.7987 ms (0.0028 s) for 5 columns (avg 0.5605 ms / col)\n",
      "[i] Loaded BTC-USD[D]: BTC-USD_D.csv\n",
      "[i] Analysis Time: 2.8410 ms (0.0028 s) for 5 columns (avg 0.5692 ms / col)\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.study = ta.CommonStudy # If you have a Custom Study, 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": [
      "QQQ (5801, 12)\n",
      "Columns: Open, High, Low, Close, Volume, Dividends, Stock Splits, SMA_10, SMA_20, SMA_50, SMA_200, VOL_SMA_20\n"
     ]
    }
   ],
   "source": [
    "ticker = tickers[1] # 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": [
    {
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       "  <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>stock splits</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",
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       "      <th>2017-03-27</th>\n",
       "      <td>125.196966</td>\n",
       "      <td>126.519411</td>\n",
       "      <td>124.907379</td>\n",
       "      <td>126.297386</td>\n",
       "      <td>18472400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.491342</td>\n",
       "      <td>126.296040</td>\n",
       "      <td>123.630030</td>\n",
       "      <td>114.376488</td>\n",
       "      <td>19309820.00</td>\n",
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       "    <tr>\n",
       "      <th>2017-03-28</th>\n",
       "      <td>126.297405</td>\n",
       "      <td>127.446093</td>\n",
       "      <td>126.017480</td>\n",
       "      <td>127.069633</td>\n",
       "      <td>23721900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.551437</td>\n",
       "      <td>126.387253</td>\n",
       "      <td>123.798677</td>\n",
       "      <td>114.491380</td>\n",
       "      <td>19665985.00</td>\n",
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       "    <tr>\n",
       "      <th>2017-03-29</th>\n",
       "      <td>127.156459</td>\n",
       "      <td>127.706676</td>\n",
       "      <td>127.021320</td>\n",
       "      <td>127.658409</td>\n",
       "      <td>13710000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.592381</td>\n",
       "      <td>126.439514</td>\n",
       "      <td>123.986228</td>\n",
       "      <td>114.613563</td>\n",
       "      <td>19060795.00</td>\n",
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       "    <tr>\n",
       "      <th>2017-03-30</th>\n",
       "      <td>127.610166</td>\n",
       "      <td>128.005935</td>\n",
       "      <td>127.494337</td>\n",
       "      <td>127.870796</td>\n",
       "      <td>16092400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.663233</td>\n",
       "      <td>126.534182</td>\n",
       "      <td>124.173210</td>\n",
       "      <td>114.736808</td>\n",
       "      <td>18867845.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31</th>\n",
       "      <td>127.687432</td>\n",
       "      <td>128.131468</td>\n",
       "      <td>127.542646</td>\n",
       "      <td>127.783966</td>\n",
       "      <td>19841400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.729840</td>\n",
       "      <td>126.612949</td>\n",
       "      <td>124.359612</td>\n",
       "      <td>114.861100</td>\n",
       "      <td>19173780.00</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>2022-03-21</th>\n",
       "      <td>350.200012</td>\n",
       "      <td>352.480011</td>\n",
       "      <td>345.579987</td>\n",
       "      <td>350.079987</td>\n",
       "      <td>73799100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>334.295990</td>\n",
       "      <td>336.622971</td>\n",
       "      <td>350.758813</td>\n",
       "      <td>367.121709</td>\n",
       "      <td>81985850.00</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-22</th>\n",
       "      <td>350.589996</td>\n",
       "      <td>357.850006</td>\n",
       "      <td>350.200012</td>\n",
       "      <td>356.959991</td>\n",
       "      <td>63345900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>337.696915</td>\n",
       "      <td>337.587843</td>\n",
       "      <td>350.310193</td>\n",
       "      <td>367.231533</td>\n",
       "      <td>80854790.00</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-23</th>\n",
       "      <td>354.010010</td>\n",
       "      <td>357.660004</td>\n",
       "      <td>351.769989</td>\n",
       "      <td>351.829987</td>\n",
       "      <td>70615500</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-24</th>\n",
       "      <td>353.799988</td>\n",
       "      <td>359.700012</td>\n",
       "      <td>351.589996</td>\n",
       "      <td>359.649994</td>\n",
       "      <td>53383700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>342.301181</td>\n",
       "      <td>339.707703</td>\n",
       "      <td>349.240109</td>\n",
       "      <td>367.436991</td>\n",
       "      <td>76213275.00</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>359.589996</td>\n",
       "      <td>360.660004</td>\n",
       "      <td>354.943787</td>\n",
       "      <td>355.645813</td>\n",
       "      <td>24863691</td>\n",
       "      <td>0.0</td>\n",
       "      <td>345.465820</td>\n",
       "      <td>340.222841</td>\n",
       "      <td>348.615591</td>\n",
       "      <td>367.521584</td>\n",
       "      <td>73514354.55</td>\n",
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       "<p>1260 rows × 11 columns</p>\n",
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      "text/plain": [
       "                  open        high         low       close    volume  \\\n",
       "Date                                                                   \n",
       "2017-03-27  125.196966  126.519411  124.907379  126.297386  18472400   \n",
       "2017-03-28  126.297405  127.446093  126.017480  127.069633  23721900   \n",
       "2017-03-29  127.156459  127.706676  127.021320  127.658409  13710000   \n",
       "2017-03-30  127.610166  128.005935  127.494337  127.870796  16092400   \n",
       "2017-03-31  127.687432  128.131468  127.542646  127.783966  19841400   \n",
       "...                ...         ...         ...         ...       ...   \n",
       "2022-03-21  350.200012  352.480011  345.579987  350.079987  73799100   \n",
       "2022-03-22  350.589996  357.850006  350.200012  356.959991  63345900   \n",
       "2022-03-23  354.010010  357.660004  351.769989  351.829987  70615500   \n",
       "2022-03-24  353.799988  359.700012  351.589996  359.649994  53383700   \n",
       "2022-03-25  359.589996  360.660004  354.943787  355.645813  24863691   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2017-03-27           0.0  126.491342  126.296040  123.630030  114.376488   \n",
       "2017-03-28           0.0  126.551437  126.387253  123.798677  114.491380   \n",
       "2017-03-29           0.0  126.592381  126.439514  123.986228  114.613563   \n",
       "2017-03-30           0.0  126.663233  126.534182  124.173210  114.736808   \n",
       "2017-03-31           0.0  126.729840  126.612949  124.359612  114.861100   \n",
       "...                  ...         ...         ...         ...         ...   \n",
       "2022-03-21           0.0  334.295990  336.622971  350.758813  367.121709   \n",
       "2022-03-22           0.0  337.696915  337.587843  350.310193  367.231533   \n",
       "2022-03-23           0.0  339.422278  338.728680  349.753981  367.314911   \n",
       "2022-03-24           0.0  342.301181  339.707703  349.240109  367.436991   \n",
       "2022-03-25           0.0  345.465820  340.222841  348.615591  367.521584   \n",
       "\n",
       "             vol_sma_20  \n",
       "Date                     \n",
       "2017-03-27  19309820.00  \n",
       "2017-03-28  19665985.00  \n",
       "2017-03-29  19060795.00  \n",
       "2017-03-30  18867845.00  \n",
       "2017-03-31  19173780.00  \n",
       "...                 ...  \n",
       "2022-03-21  81985850.00  \n",
       "2022-03-22  80854790.00  \n",
       "2022-03-23  80074795.00  \n",
       "2022-03-24  76213275.00  \n",
       "2022-03-25  73514354.55  \n",
       "\n",
       "[1260 rows x 11 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration = \"5y\"\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"
     ]
    },
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>stock splits</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",
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       "    <tr>\n",
       "      <th>2022-03-21</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>340.087312</td>\n",
       "      <td>350.327677</td>\n",
       "      <td>-0.002780</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-22</th>\n",
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       "    <tr>\n",
       "      <th>2022-03-23</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>338.728680</td>\n",
       "      <td>349.753981</td>\n",
       "      <td>367.314911</td>\n",
       "      <td>80074795.00</td>\n",
       "      <td>345.823813</td>\n",
       "      <td>342.549265</td>\n",
       "      <td>350.636483</td>\n",
       "      <td>-0.014371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-24</th>\n",
       "      <td>0.0</td>\n",
       "      <td>342.301181</td>\n",
       "      <td>339.707703</td>\n",
       "      <td>349.240109</td>\n",
       "      <td>367.436991</td>\n",
       "      <td>76213275.00</td>\n",
       "      <td>348.896298</td>\n",
       "      <td>344.103876</td>\n",
       "      <td>350.989954</td>\n",
       "      <td>0.022227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>0.0</td>\n",
       "      <td>345.465820</td>\n",
       "      <td>340.222841</td>\n",
       "      <td>348.615591</td>\n",
       "      <td>367.521584</td>\n",
       "      <td>73514354.55</td>\n",
       "      <td>350.396190</td>\n",
       "      <td>345.153143</td>\n",
       "      <td>351.172536</td>\n",
       "      <td>-0.011134</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2022-03-21           0.0  334.295990  336.622971  350.758813  367.121709   \n",
       "2022-03-22           0.0  337.696915  337.587843  350.310193  367.231533   \n",
       "2022-03-23           0.0  339.422278  338.728680  349.753981  367.314911   \n",
       "2022-03-24           0.0  342.301181  339.707703  349.240109  367.436991   \n",
       "2022-03-25           0.0  345.465820  340.222841  348.615591  367.521584   \n",
       "\n",
       "             vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "Date                                                                   \n",
       "2022-03-21  81985850.00  340.435699  340.087312  350.327677 -0.002780  \n",
       "2022-03-22  80854790.00  344.107764  341.621192  350.587768  0.019653  \n",
       "2022-03-23  80074795.00  345.823813  342.549265  350.636483 -0.014371  \n",
       "2022-03-24  76213275.00  348.896298  344.103876  350.989954  0.022227  \n",
       "2022-03-25  73514354.55  350.396190  345.153143  351.172536 -0.011134  "
      ]
     },
     "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, 20) > ta.sma(asset.close, 50) # SMA(20) > SMA(50)\n",
    "# long = ta.ema(asset.close, 8) > ta.ema(asset.close, 21) # EMA(8) > EMA(21)\n",
    "# long = ta.increasing(ta.ema(asset.close, 20))\n",
    "# long = ta.macd(asset.close).iloc[:,1] > 0 # MACD Histogram is positive\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, cumulative=False)\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": [
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       "    }\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>2022-03-21</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-22</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-25</th>\n",
       "      <td>0</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",
       "2022-03-21          0          0           0         0\n",
       "2022-03-22          0          0           0         0\n",
       "2022-03-23          0          0           0         0\n",
       "2022-03-24          0          0           0         0\n",
       "2022-03-25          0          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": [
      "\n",
      "Trades Total | Round Trip:\t22 | 11\n",
      "Trade Coverage: 71.67%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\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>2020-04-27</th>\n",
       "      <td>1</td>\n",
       "      <td>213.502670</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-01</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>280.042267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-16</th>\n",
       "      <td>1</td>\n",
       "      <td>286.253387</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-11</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>316.124329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-13</th>\n",
       "      <td>1</td>\n",
       "      <td>338.976044</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>332.536896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-16</th>\n",
       "      <td>1</td>\n",
       "      <td>339.384094</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-05</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>356.483429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-02</th>\n",
       "      <td>1</td>\n",
       "      <td>388.073944</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>379.390961</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "Date                                      \n",
       "2020-04-27       1  213.502670         NaN\n",
       "2020-10-01      -1         NaN  280.042267\n",
       "2020-10-16       1  286.253387         NaN\n",
       "2021-03-11      -1         NaN  316.124329\n",
       "2021-04-13       1  338.976044         NaN\n",
       "2021-05-26      -1         NaN  332.536896\n",
       "2021-06-16       1  339.384094         NaN\n",
       "2021-10-05      -1         NaN  356.483429\n",
       "2021-11-02       1  388.073944         NaN\n",
       "2022-01-07      -1         NaN  379.390961"
      ]
     },
     "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",
    "tradelist = trades\n",
    "if rt_trades > 10:\n",
    "    tradelist = trades.tail(10)\n",
    "tradelist"
   ]
  },
  {
   "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",
    "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",
    "_oc_change = asset.iloc[-1].open - asset.iloc[-1].close\n",
    "_oc_change_pct = _oc_change / asset.iloc[-1].open\n",
    "oc_change = f\"{_oc_change:.4f} ({100 * _oc_change_pct:.4f} %)\"\n",
    "ptitle = f\"\\n{ticker} [{tf} for {duration}({recent} bars)]\\n{last_ohlcv}, Change (%): {oc_change}\\n{extime}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trade Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nQQQ [D for 5y(1260 bars)]\\nLast OHLCV: (359.5900, 360.6600, 354.9438, 355.6458, 24863691), Change (%): 3.9442 (1.0969 %)\\nSunday March 27, 2022, NYSE: 12:50:00, Local: 16:50:00 PDT, Day 86/365 (24.00%)'}, 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=[\"limegreen\"], alpha=0.65) # Green Area\n",
    "short_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=[\"orangered\"], alpha=0.65) # 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 0x13037ff10>"
      ]
     },
     "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.shift(1) * asset.PCTRET_1\n",
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].plot(figsize=(16, 3), color=[\"gray\", \"limegreen\"], alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x130402430>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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J9Z9gUbCITxzzCY7LHMfluy7n6NTR/MPR/8Ca4hpiF9PqJwM52b7DheS4Dm7tvRXnkulR7hu8b8ztYxezeGAxzrnGNC17jnI7GwQWUHVVlueX87oFrxux7paeW7h/8H7OO/68WVn2mXZg4x6LiIiIiMicV3M1Pvj0BynEBTaWNvJHbX/EczPP5byt57GrtottlW18ZN1HeFb6WXTVuqjEFU5qPol1pXV45o06zclofPNxOPpqfaQtTUxMLhq7Set9g/exsbSRwIJZlwUdLuWlIIabum8aEYjGLua7nd+lJ+zhb478G7Jelk9v+DQ/OvlHHJs5dgZLPHsoEBUREREROUQ9WXiSmqtRjstcvutyrt59NSkvRS2uYc5Ie2mqcZUd1R2kSOFwnLf1PMpxmZRNvL/mUDBZdVUCC/DwCF1IPso3sqrDPTz4MFVXxWf2BqHwzNyjj+QfGbH8wcEHqboqALuru3kk9wgD0QCX7riUc47XCLswwVFzRURERERkbitFJR4afIibem4i6VmXBEw1VyMgoOZqFOMig+EgsYtp8pto9Vtp99tJWYqsn8U3n85KJ6ELGaNb6Kh882n1W2n2msl62UaGdFd1V2ObW3tu5aaemwDYUNpA6ELSXnpSX4PJZmakLc1gOMhAbaCx/IbuGyjGxcY1xsSELmRrZesMlnZ2UUZURERERGQe21DaQHetmx/s+AGby5upxlWqcZU3L3ozt/feTuxi2vw2QheSslSStfSCRrNb3/NpphmAjGUouiI4Gn03JyrjZRqPh469qbSJZr+ZRcEiLui8gIFogEXBIjZXNieZ0wk2/Z1JKS9FNapyd//dnHnkmQBsKm/COYdhdIfd9IV9xC5me3X7pJxzRX4Fx2eOZ1Fq0aQcbyYoEBURERERmafu6b+HL2/9MqW4lCxwSfPYH+34EVVXpS9M+mz6nt9oBpslO+bxsl6yzsc/qAF4PDwcjv/Z9j+kLMVfH/HXVF2V0IX89+b/xrBZ3yx3yFB2d01xDWdyJpW4wkA0QMpSVFyF1YXV9IQ9OBwD4cD4BxxHNa7y2Y2fJWUpbnv5bZNwBTNj9v/EICIiIiIi+63manyn8zvkozzluEzoQpr8Jpq8JnrDXi7deSmRiwi8ieemzIwmv2m/s6F7SlmKtKUpRAX6w36u3n01kYvIWIZ8lH8mcJ4DvHpItaWyBYCeWg+xixv9YlcWV9JT68EwQheypbyFFfkV1Fxtv8+1qbyJv3ryr6jGVXbXdlOMipN3IdNMgaiIiIiIyDyzu7qb+wfupy/sI2MZ2v12mqwJz7xGVjMf5UlZakZGpTUz2oI2mr1mHI5aXMPDo8VrIbAkMJ7t/UOHDE1ds7O2E4CuWhcxcWN95CKKcRGfJHN6/rbzOWv9Wfx4+4/3+1x3999NMS42+p/e2nvr5FzEDFDTXBERERGReWRdcR2f3vhpBqNBanGNwIIRWU/PPHzziVw0g6VMNPlNFOMiMXEyv6jv0e61J/0r58jcm2aGYWyvbGd1YTXdtW5iFzcGhHI4UpYiZSmiOOLp4tMU4yJ39N3Bvx7zr/t1rkJUIHQhDoePT9rmRrA+GmVERURERETmkWu7r6W71k0lriRNYEfJLC7wF5D1sgfdxHYyDPUXTfnPTAczV4LQ4WJi/n3Dv9Nd6yZyEb75tHgtpEjRHrQ3+pJWXCXpLxrtX3/RhwYf4paeW4hchMOR8TJz8nUaooyoiIiIiMg88cDgAyzuX4zD0ea3jRmoeObR4rdMc+lG1x60U47Lc2ZwotG0+W0MRAMMRAN017qBZBCjlJdMezP0HCB0IYbtdz/Ym3tupifswcOj1WudkSbVk0kZURERERGReeCR3COcu/lc+sN+0paeM9kyzzya/eY5U97RpLwUGcsQuYhdtWRu1D2nnhnqSzoUiEYuIh/lARgMB9lY2sgN3TeMOYjRzupOPLxkLlY/2zjeXKWMqIiIiIjIHLeptIkvbPoC+SifTMcyx7Nlc5FvPlVXZUNpAxFRYzTdIV79P4cjsIDQheyq7CJMh/zt6r+lHJfBoKPcwSeO/cSIfatxlW2VbWS8DBk/w3ygQFREREREZA5aOriU4zLH8b8d/0tXrYtCXMCwOZ9dnKuGRvvdUtky6jyrZsbCYCEREWEcErqQ5YXlLKwspBSXKMQFPDyWDC7hE4wMRLeUt1BztTndfHlPCkRFRERERCZRNa5iZqQsNf7GB6ir2sUXNn+BSlzBN78xPUiL36IgdIakvTSZOEMpLhGMEWaZGQEBnudRiAv8puc3nNJ6ClVXBZIRdjsqHXuNGrw8v5yaq+G5+dOzcv5ciYiIiIjIDNpV3cUdvXdw5qozOWv9WUAyh+QXt3yRS3dcSj7KE7t4nKOMzznHtd3XUo7LFOJCY0qPjGX26pco02toYKLh84iOxjOPwALWlNawurgawxrZzpqrsa60bsT2j+QewbmRIwvPdcqIioiIiIhMgvetfR/luEzVVdmd2803t32TqquyuH8x+SjPz3b/jNcueC1fOeErB3WepbmlXN99PbGLSZEiImKBt4CUN3+ClLkqsICF/kIcbtxtM16GQlTgqdJTeHi0BW1UXIVCVOB3fb/j5OaTG9tuqWxpzB06X+gnExERERGRg3Rd13VERBTiQmPU0xu6b+DmnpupuiqGMRgN8tu+33LfwH0HdA7nHGuLa/l1z6+pxlV882lPtbMoWETanzuj5M53gRdM6EeBoabb5bhMYAFmRsaSgYgeHHywsV3N1egL+/Bt736nc5kCURERERGZ1+7ovYN/efpfWF1YPSXHfzT3KBfvuJiBcACHI21pUpai6qpUXZXIRSwMFtLut2MYX97yZZwbP2O2p8t2Xsa/rf837h24l8hFZL2kGeh8Ck4OJUOj6oYubCwzMwxjZ3Unf/XkX/HLrl/SH/YTu3ivUXjnOjXNFREREZF56YHBB9hZ3cklOy6hq9bFh9d9mF+86Bcckz1mUs9zTdc1VOIKaUsnmS2MtJemGBcpx2WyXjYZpMYCMi5DT9jDqsIqvrP9O7z/6Pfzp+1/utcx81Gei7ZfxOL+xZzYdCInN53MzT03U4pKeHhkLKMAdI4b/v5FRI3Hnnnk4zxVV+Xr277OK1peMW6f07lIgaiIiIiIzDsr8is4e/PZFKMiDkeT10QpLvHhdR/m+pde38gmHoxCVGBpbikr8itwuL1GrG3xW2j2mkf0FwwsoEyZC7dfyOrCar6w6Qvcc8o9I45bczU+uu6jbClvoRgX6a51szS3tBGAzpd5JOUZxjP1xsOj5mqkLQ3AqsIqnHOTMtDVbDK/8rsiIiIicsjrqnbxjW3foByXcbgkE+llaPFa2FXbxdmbz56U81y560q+uOWLSR8/glEzlGY2YiTbobkmVxdXU3VVKq6y1z5PF5+mo9JB5CJavVaavWYiF1FzNSIX7bW9zF2+JYMPDR+EaKi+RC7C4bir/y4ionmXAVcgKiIiIiJz1q7qLr6x7RvcP3A/ALkox+W7LmdbZRsBAW1+G81+M555ZPwMvvk8MPjApJz7qeJT5KM8kMwhOREeHj4+5biMh4dzbkRwuaa4hk9u+CTVuJpkQP0MWT/LAn8BAUEjkJX5YYG/gKxlRwxu5OFhWKPv6NriWmIXz6sRc0FNc0VERERkjnpo8CHO2XIO+SjPr3t+zX2n3Me3O77N3f13U3VV2vy2vbJIPj6VuNLou3mgYhezvryetKVp9psnvJ+Z0R60U4krhC6k4ipsLW/lzv47OSZ9DN1hN7koR+hC2ry2xn4pL0W7137A5ZXZyTOPlqBlr2WQ9Bs1jEJcSH7A8BSIioiIiIjMqMFwkLM3n00uylFzNQyjElW4b+A+clEu+eJue39x982n5mosGVjCq9teTYvfgs/+T4uxvbqdYlRs9OPbH2ZG1s9SjatUogpnbzmb7lo33bVuXt32ahyOlKU0L+ghKrCg0a/Yx08y5sa8GzV33Ksxs8vMbLeZPTnG+tPMbMDMHqv/TU6jexERERGRMdzVfxfluAzQCAZXFlYSupAWr4WFwcJR9xsKTr+89ct8asOnOGPlGVy0/aJRt3XOMWiDo65bXVxN6MIRo53ur7SXjLK7priGclwmJuaxwmMYNmo2Vw4NgQU0e0mWPWWpRlA6fECj+WAiYfXlwFvG2WaJc+6U+t+XDr5YIiIiIiJj21jeSOQimrymRubwPzb9B6ELcbgxg7ihbFMhKrCysJKaq3HV7qtG3fY7nd/hWy3f4tHco3ute7LwJDEH328vZUnZq65KQEAtrpHxNDXLoa7Jb+Lw1OEEXjIdUMpS865OjBuIOufuBXqnoSwiIiIiIqP6xe5fsKa4pvF8a3krERG++cmgPzhyUY6Kq+wzc+SbT5uf9L10JAMFRS4iH+Yb25TjMg8NPsStvbcSuYjLdl7GxdsvphAVGtusKqwidvFBN5/1zccwqnGVrJelPWgnY5qeRRK++TjcvGuWC5PXR/S1ZvY4sB34jHNu1SQdV0REREQOcbuqu/jxzh9Tjsss/oPF+PhsqmzCw8MzjxQpPDwikqAy8Pf9FTftpcm4TGPAIIfjwcEHeeNhbwTgvWvfS1/YRykq4ePzROEJHis8xpKBJVxw4gWsL61nS2VLEgTbwQUIQ0G0YaS81EEfT+YXH59mr3neNcsFMOfc+BuZHQ/c4px72SjrFgCxcy5vZmcAFzjnThrjOB8GPgxw9NFHv+qaa645mLJPuXw+T2tr60wXQ2aQ6oCoDojqgKgOzLylqaXcmrmV2MUsYAEnhCfwZOpJTs2dygvLLwSg4BW4/rDrAXhf9/vGPebyluWsanomd/Luwrt5Ba+gQoWvtn6VyEW8rPgy1mXXUfWqyQBCLsWRHMlObyfOOd7c/2aOCo86qGsLCXmw7UFeXng5C+OFB3UsmRqLaovoS/XNdDH24nAcnT6adn/2jqZ8+umnL3fOnTrauoMOREfZdjNwqnOue1/bnXrqqW7ZsmXjnnsmLV68mNNOO22miyEzSHVAVAdEdUBUB6bf6sJqHis8xrLcMj5+zMf5+e6f8+ueXyfZTgsIXUjGy+Dj0+Q3AcnAQr1hL4ZxWOqwcc9RjssUoyKu/t+fLPgTLjzxQtYW1/KRdR8hF+VY4C+gpdTCrvSuxoAxzV4zhbiAYbR4LWT9A58CRuaGd3W8i+uOvW6mi7GXMA4569izeNvhb5vpoozJzMYMRA+6aa6ZPQvY5ZxzZvZqkn6nPQd7XBERERE5NNTiGoEFmBkbShs4a8NZFKICVVflocGHkhFkMZq8JpxzhIRU4sqIeTbNjIX+wmSqiwnwSfre+fhERHRWOinFJc5afxaRi2i25mRUW5cMbtTkNVGKSxTjIq1eK775BKaZEEUO1Lj/eszs58BpwBFm1gGcA6QAnHMXA+8CPmpmIVAC3uMmkmYVERERkUNeT62Hj677KAv8BTw3+1y2VrZSikuNPnFVV6U37CXjZWj2kykt/Min6qp7DRTke/6ER7FNeSnaacczj4FwgN6wl8fzj1N2ZUpxiVYvaY79mvxr6Mp2kfbSyVylcaXRn1NEDty4gahz7u/GWf894HuTViIRERERmbdW5FewrrSOdx/xbgAu7LyQHdUdbIw38mTxSRyOgIBmv5kgDijEBWLiEaOGZv0sWQ6+SWzgJV+FffPJRTm+sPkLRC7CxyftJXOTHhEeQWuQBKWBHzSaAovIwVF7AhERERGZFqsLq/nsxs8yEA5wYvZEAO4bvA+Adr+dmqsRu5jAAjzzyPpZfPPJR/kpHTU0ZSlqrsZAOABAi9cy7+ZsFJltFIiKiIiIyJSquRrLcsu4sPNCclGOiIj7Bu4jH+epxlUMI/ACglG+mqa8FAtt4ZSWb8++nvNxzkaR2UaBqIiIiMgcd1ffXeTj/KwdPfMb277B7/p+R+hCsl6WMAr5RfcvaPaaiVxEq7/v6XGmOjsZWIBvPqELMQzfm1g/UxE5cApERUREROawSlzh/G3n0xv28saFb5x1fRgLUYElA0uoxBVSliJtSd/LSlwhdCFN1jTjzWDNjIXBQnpqPTjclDYDFpGE2h2IiIiIzGEPDT5E1VUB6Av7Zrg0I8Uu5itbv0IxKpKyFFk/i5nR6rWStjRpS8+q0WdTlsLq/4nI1FJGVERERGQOe7zwOJW4gsPRE/bwnMxzZrpIDUtzS3lo8CFCQjKWaSzP+BkyZPax58xYECwgdvGMZ2hFDgXKiIqIiIjMYSsLK6m5Goaxs7rzgI8TupAlA0vYUNowoe37an3c3X83uSg36vqaq3HFziuouRoBwazKfO6LZ/p6LDIdlBEVERERmaNWFVaxsbSRwAJCF7K7uvuAj/Vo7lHO2XwOVVflxpfcyJHpI/e5/Xe3f5c7++7kNQtew9ef/3XKcZmf7voppy88ncNSh7Eiv4K1pbUYRsabfdlPEZlZCkRFRERE5qD/3PifLM8vp+ZqpCxF6EJ21XYd8PG2VbZRjstUXIUvbf0S3z3xu/vcfkNpA4W4wP2D9wNwU89N/HT3T7l056U0+80Y1siGqqmriOxJbQ9ERERE5piBcIBH8o/QF/bhmUfKkmav3dXuAz7mjuoOIBmw56HBh3hw4MExt63EFbZXtzcef3z9x7lkxyWU4zI1V2MgHGAwHCRyEWkvfcBlEpH5S4GoiIiIyByzvrQ+mfrEayJlKXxL5r3sDg88EB0KLFu8Fgzj7C1n45wbddvOSiehCxujzD6af5TesJesl6XVbyVrWTJehqxllQ0VkVEpEBURERGZY9YW1xLGIYbhmdeYcmQoq3kgOiudxMT45pPxMvSFfawuriZ0IfkoP2LbjkoHoQvx8HA4qnEVwwgsIONlaAlaaPabSfvKhorI6NRHVERERGQOGQgHuKHnBsysMRKtmZGyFLuquyhEBVr8lv06Zl/YR2e1M8lw1o9VosRH1n2EjJchbWkuf+HlHJU+CoCesIfIRaQsRcUlU8e0eW2NzKyIyHiUERURERGZQy7ZeQk9tR5SliKwZ3IKKS+Fw7G4f/GEjnPlriu5vvt6IBkxtxpX8epfDQMLCCygElfIhTl21Xbx7tXvZungUgB6aj04HIY1+qcGnvIbIjJxumOIiIiIzBGrCqv4Te9vCF1I1suOWDfUTHZrZSsAkYuoxlWa/Ka9jlONq1y16yoGwgG2lbfxeOFxYmKC+ldDM2OBv6CxfW/YSyEucN628/jVS39Fb9iLYfiezwJbQOQizb8pIvtFdwwRERGROeChwYc4d8u5VOIKAcFezWCHAsElA0vIRTmu2X0Nf7/27ynFpRHbVeJKY9qXmJhruq5hXWkdHt6IEW7NrPHX4rXgcFAfu6i31ktM3MigqkmuiOwvZURFREREZrlSXOLszWeTj/I43KhZzqGgcEN5A59Y/wkylqGj0sE1u6/hA8/6QGO787aex5KBJVTipG9n6EJCFyaj5Y4xwm3Wz1KKS2yvbueR3CN017obTXNFRA6EMqIiIiIis8yFnReypH9J4/nd/XdTjstUXIWMlxk1YBwKCiMXsbqwmnWldcTE3NV3V2Mb5xwPDj7IYDTY2MfV/xtvvk/DiIn5xPpP0FXrIiDQ1CwicsAUiIqIiIjMIpvLm/l1z6/5zKbPUI2r/LLrl1zQcQGRi2j320nb6AHj8KAwIqLiKhjG+vJ6BmoD/HjHj9lS2ULoQpq9Zlq8Fjw8spalyZrG7eMZEwNQczVyUW7EQEkiIvtLdxARERGRWSIX5vjB9h9QiSuELuSj6z7KxvJG8lGejJchsPGzkK7ekbMcl8lYhoqrcM6Wc3g0/yiP5R+j5moA+J7PQlsIMKHM5tBULUPHHhotV0TkQCgjKiIiIjJL/Nfm/+Kh3EM45/DxeaLwBOW4TJPXRNbLjhswDvUTTVkKw8h4GQAezT9KxVV4svAkkYvwSQYXGhqMaCJa/VYylsEwaq7WOJeIyIHQHURERERkGuXCHD/Z+RPKcXnE8k3lTTxZeJLYxTT7zTT7zUDSFDbtpSc0Mu3CYCFtXhvtQTuLgkUEFuDhUY7LRC5prutwpLz9z2aaGa1+K1nL0uK1HNAxRESGKBAVERERmWKFqNB4fGvvrVy28zLe9MSb6Kx0NpbfN3Bfo1+nZx6BBY2RaSeafTQzMn6m8djMaPaaG811Qxdi9f8OhJnRErSQ8UcfMElEZKIUiIqIiIhMocfzj/OO1e/g972/B2AgHKAclynGRT6z8TON7R7NPzpi9FoPj4yXIW3pgwr6Mn6GRcEi0pbG4ZLmtQoiRWSGabAiERERkSlSczW+u/279NR6OG/beeTjPE+VnsIzj8hFbCxvpOZqlOMyq4urgWf6eQ41hZ0MZkaL30IQB2pSKyKzwriBqJldBvwVsNs597JR1htwAXAGUATe75x7dLILKiIiIjKXlOISN/fczPrSegByUY5vdnwTHz8ZSKg+ou0ZK88AoBpXSXNw2c998cyjyW+akmOLiOyviTTNvRx4yz7WvxU4qf73YeAHB18sERERkbnt8xs/z8XbL6YW10hbmpiYWlyjGBfJWAbfkoC0EBUYCAeIiAg8NVYTkUPDuHc759y9Znb8PjZ5O3Clc84BD5nZQjN7tnNux2QVUkRERGQuiVzEquIqBqPBZOoVy5J26UazWMOIiSnGRaquiiOZrsUzDd8hIoeGybjbHQNsG/a8o75MRERE5JDUWekkdCEpSxEQ4HkeGT+DZx6eeZgZvvlkvSw+Pgu8BY1BikREDgXT2v7DzD5M0nyXo48+msWLF0/n6fdbPp+f9WWUqaU6IKoDojogB1IHlqWWEWdizuw9k8Oiw6amYDItFtUW8a6Od810MWQGzdY64HC4bsdif/EMl+TATEYg2gkcN+z5sfVle3HO/Qj4EcCpp57qTjvttEk4/dRZvHgxs72MMrVUB0R1QFQHZCJ1oBbXCCzAzMhHeb679rvEtZjbj7qdtK9M51z2ro53cd2x1810MWQGzdY6EMYhZx17FqcdftpMF+WATEbT3JuA91nij4EB9Q8VERGRQ0UhKvB/V/1fvtXxLQDu7LuT7lo3Hp6CUBGRMUxk+pafA6cBR5hZB3AOkAJwzl0M3EYydct6kulbPjBVhRURERGZSU8XnyYi4sXNL24su777egpRgZ93/ZyXtbyMu/vvJiIi42VmsKQiIrPbREbN/btx1jvg3yatRCIiIiKzUOQiPr7+4+SiHPeeci8+PksGlvCzXT+jHJdxOL6w+QssDBYC4OPPbIFFRGYxTVYlIiIiMgFLBpZQdVWqrsru6m6+0/kdluWWUYyLZL0sxbiIw1GMiqS8FGY200UWEZm1NFmViIiIyDj6w34u2n4RhaiAw3HPwD0szS2lGlfJWIasl2WBvwDDqLoquJkusYjI7KaMqIiIiMg4rtx1JburuwkswDnH4v7FhC5M5gL1swCkSOHj43DqHyoiMg5lREVERGTKbS1vpRbXZroYB2Sdv45be26l6qqkLY3Dsba4ltjFpL1nRsU1M9qDdtqDdjXLFREZhwJRERERmVIrCyv54NMf5CPrPjLTRdlvV+++mp81/YyBaICUpfC9ZACiUlwi7aXxbORXKTPba5mIiOxNTXNFRERkSvy6+9dc03UNXbUuClGBxwuPs2xwGacuOHWmizYhV+26iit2XUEmypD38gQEePXf8GPixmMREdl/uoOKiIjIpLtm9zVctP0i1pfWU4pKpCyVLO+6ZoZLNrb7B+7n3v57Aeip9XDVrqsoRkXe3vt2DgsOo9lvxjOPZq+ZZmsm5aVmuMQiInOXMqIiIiIyaXJRjnM3n8sThScYjAZp89tIeSmcc5TjMivyK2a6iKNyzvGlLV9iMBrkZS0vY0t5C/koT8pSpBg5FUuT3zSDJRURmR+UERUREZFJUYkrfLvj2zySe4T+sJ+sZQks+c3bzAgsIBflKMWlGS5pYntlO5AEoT/Z9RNqrkbVVXks/xgD0QAAgaff7EVEpoICUREREZkUv+r+FXf130XkIrJelrSXHpFJ9C2Z2qSj3DGDpUzc2H0j73vqffyu93d0VDq4evfVDEaDZC1Li9dCszXTFrQ1AmkREZlcCkRFRERkwpxzdFY6uWznZfxg+w9wzjXWPVZ4jFpcI+NlGv0ph/MtGXF2TXHNtJZ5T7W4xk92/oT+sJ/vbv8uS3NLqcQVPDya/CYyfoa0nx7/QCIicsD0M5+IiIhMSDWu8t+b/5tHco8QupBSXCKwgJObTubR/KOsyK/A4cbMInp4OBzrSuumueQjLRlcwmA0CMDu2m6u774eh6MtaGsEyyIiMrUUiIqIiMg+5aIc5205j8FokFXFVdRcjRTJiLGX7LyEZq+ZQlQgsIC0jWyOO9xQkLeuPP2BaCWuNMp2S88txC4mbWmqrsrm8mbSlsZHQaiIyHRRICoiIiJjejz/OJ/d+FlKcYlSXCJtabJ+MghR1VWpuiqluEREROzixjQto7H6f1tKWxrL+mp97Kzt5MXNL56ya1gysIQvbvkir2l7DX952F/yROEJHI5mr5lqVCVyESk/NWYALSIik0+BqIiIiIzQH/ZTiAq0+C18ddtX6Y/6wUGz14xvfqPpbcbLUI2qZL0sWZel4ipkvMyYxx0aObcr7GJNYQ0YfHrDpylEBX710l+xKLVoUspfc7VGQJyLctw/cD/5KM8dfXewuriaSlzBx8f3fNppJ3LRXv1ZRURkaikQFRERESAZxCewgP/e/N+sLKwkZSkqcYUmr4nAgr36T6a9NO2045mH53lkGDsIHTKUSf3o+o+StjSluEQ5LnNX/12888h3HvQ1XNR5EfcP3s8lJ1+CZx5/u/pvk4yti3A4dlV3kbY0GT8pa+AFBPo6JCIy7XTnFREREZbnlvNfm/+LlKUoxSXyUR4Pj2a/mZSlxswY7u88m1kv2zh+u9/emFP0sfxjBxWIluMyj+Yf5caeG+kP+/l2x7d5actLKcQFClGhsV1EhO+pL6iIyExTICoiInII21bexoXbL2RFfgX5KE/oQgILaPKa8PH32dT2QHjm0eQ1UY7LhC4EwOEOekqXS3Zcwg3dN1COywDc1HMT9w7cSzku43BkLENMjGGaG1REZBbQnVhEROQQtKm8ifsG7uPG7hvpqfUQEdFkTZhn1FyNrJedsn6TQ8etuRoOh2F0VDsI43C/M6xDNpQ3NKZkCSwgdCE9YQ8pS9Hmt+GcI+tnJ+0aRETk4CgQFREROcQMhAP858b/pKPSAQYpUjR7zY1RY4emZpkqQ/OJhi7EsMY0Knf038EZh51xQMesxlUAspYFg9CFpC1Ni9+igYhERGYh3ZlFRETmocfzj/O/Hf9Lb60XSLKP+ShPV62Lj677KNur2wksIOtlSXtjz/05FYYCw5iYFq+FJr8JgOWDyw/oeM45OiodZCxDS9ACJFPF+OYrCBURmaWUERUREZnjYheztbKVYlTkxc0v5trua7l056UMhAPc238vN770Rr6x7Rss7l/MgmABXdWuJBPppWckUPNJpoCJXUzgBRhJEHx7/+28pOsl+z1oUS7KkYtyjb6fWS9LNa42jisiIrOPAlEREZE5KBfm2FndSWe1k7v67+L+gfupuRovb3k5T5eeJh/lCQjorHbyhifegGEMRAMMRANkvSwZy8xYttDMaA/aG8+dc0Ayfcw3Or6xX4Fo6EIu23kZkYsagadvPguDhZNaZhERmVwKREVEROaIreWtXN99PaW4xAODD5CP8kQuInIRnnlELmJpbikpS5GxDGkvTRiF5KIcGS9Dm9fWyEBOZ1Pc8QyVJSbGOYdzbsLlu67rOn7d82siohEj/M6m6xMRkb0pEBUREZnFSlGJUlzC4fjMxs/QWe2kFtdIW9Kv08MDg4yXwTefKE4C05SXwsxY4C+gEldmrBnu/nI4BqPBERnTsdRcjd/2/Ta5PktrWhYRkTlkQndsM3sLcAHgA5c4587fY/37gW8AnfVF33POXTKJ5RQRETnk1FyNT274JE+VniJlKSpxhYCAjJ/BbPT5MH3Px8dvPDezOTVticOxubyZP2j9g3G3/fq2r7OpvAnPPNJeehpKJyIik2XcQNTMfOAi4I1AB/CImd3knFu9x6a/cM59bArKKCIicsBqrkZHpYMTsicAELmIS3deytPFpwks4IPP+iAnNZ80w6VM+kmW4hIRES1eMuXIz3f//Jn+nvURblOWmhOZzQPhSPqKri2tnVAgurW8lXyUZ4G3QE1xRUTmmIlkRF8NrHfObQQws2uAtwN7BqIiIiKzRi2u8Zu+33BD9w1sKW/hTxf8KX9/9N9zd//dXNt1LYWogMNxz8A9fOsF3+K1C1570OdckV/Br7p/xesXvZ58mKcn7OENC9/AszPPHnff67qv44c7fkjsYjzzODw4nL6wj5qr0ea1JZlO88c9zlyVtjQVV8Ewbui6gde0vYbjs8c31heiApfuvJRiVOR1C17Hny/8c7pr3aQtTcqf2nlPRURk8tnQSHVjbmD2LuAtzrkP1Z//I/Ca4dnPetPcrwJdwNPAp5xz20Y51oeBDwMcffTRr7rmmmsm6TKmRj6fp7W1daaLITNIdUBUBw5MjRqdficOxwnRCWz1ttLu2ml34/f7OxgREbdkbqFmNQxjZbCSVJzi8NrhdKY7G5nEE0onkHIpTiyfyB0L7+Do6Gg+WPngiCatQ8arA8uD5fwu8zvaXBtdXhexi4GkSaxzjmbXzDsq76DVtfLs+NmjTilyd/pu7knfQ+SiEcvb4jbO6DuDjMvstc98ExPTHXRz+8LbMYz2uJ1Plz7dWP9g6kFuz9yOIxnM6NPFT3NBywW8pPASTimeMqVlW1RbRF+qb0rPIbOX3n+ZrXXA4Tg6fTTt/tR+th6M008/fblz7tTR1k1Wr/6bgZ875ypm9v8BVwD/Z8+NnHM/An4EcOqpp7rTTjttkk4/NRYvXsxsL6NMLdUBUR3YPz21Hj62/mN01bqIXEToQv7xqH/k2u5rKcdlrn/J9RyVPmpSzpWP8vTUejgidQQtfgvluMzZm89mRW4F+ShPxjI4HHEQ05vtJXABhaiAYWxp20LaT7OVrdSiGk/HT3PXs+7iKyd8hWpcxeGoxlV881m6ZCkv/ZOX0h/2s9BfyJHpI0eU45qnr2GgMECv68Uwsl6W0IWkLEXoQrpdNz9J/YSMl+HkppN5w6I38K4j3sX13dfTHrRzWHAYD2x6gHJUptlrJrCAUlzCMAoUuOk5Nx0yzU4jF1EKk2u3tHHaa05rrNvdtZtaR42qS96fx573GDZgPLnwSdYftn5Ky/Wujndx3bHXTek5ZPbS+y+ztQ6EcchZx57FaYefNtNFOSATCUQ7geOGPT+WZwYlAsA51zPs6SXA1w++aCIiMlfELmZZfhnXdV3Htso2qnGVJq+JSlzhxzt/jG8+NVfjG9u+wTde8I2DPl8pLvHZjZ9ldXE1gQVcfOLF3N53O0tzSwnjkBavJRk51lJk/CSbmLY0aS+919QgTX4TNVfjjr47+OQxn+Tbnd+ms9LJzupOFgYLeaP/Rr685svELiZ0IT954U84KnUUZ204i1JcYnd1NylL0eq1JgGolyJryeBAGTKk4zS5KEctqvFo/lFWFlby8ODDPF54nFyU4/DgcByOrGVJeUkT02a/+aBfo7loKFvscHtlh3tqPcTEjee/6/td8nrtu2GXiIjMUhMJRB8BTjKzE0gC0PcAfz98AzN7tnNuR/3p24A1k1pKEZFhHhx8kK5aF0emjuSP2/54QtmivlofmyubiVzEkakjeV72edNQ0vmrr9bHrtouNpc3s760npWFlawrrUuyVc7RHrTjmUfGy1CKS4QuxMdnyeAS7u67m1MXnEqb30Y+ytPq71/T55qr8cn1n2RNcQ1VVyV0IR9a9yEMo+ZqZP3sPqfxGK2+NHlNDEaDXLnrSpblltEb9pL1svSUe2hLJ+UMXYjDcf7W83lxy4tZX1pPMS7i4dHsNeN5Hmn2Hrk17aVpo43YxY3y3jtwbzLHpwvpqnXR7DWPmAPzUDW82fLwrkO5KMf9g/cTuQiHwzCqrkolqpD15s6IwCIi8oxxA1HnXGhmHwN+SzJ9y2XOuVVm9iVgmXPuJuATZvY2IAR6gfdPYZlF5BD2wOADnLP5HPJRHsM484gz+exxnwWSLNna4lpe3vJyHI4HBh7g+dnns668jm91fItclCNyEb75fO8F3+PlrS+f4auZezaUNvCrnl/x+77fU4yKjcxVTEzKUvj4pP1n5qs0s0Z2rxpXKUQFPr/585zUdBL/fsy/89lNn+XMI87k357zb/s8b0+th6dLT5P1sqzIr+Dp0tM452j1WylEBQpRgSaviYDggOaSHBoE6IaeGwgIMIxyXMbhWOevw8en2W9mMBrkicITrC2tJXZxo/nvUCZzLENTi2RchkpcoRAXwEGb30Y1rjbm/DzUDX8NhoL0I1NHctWuq+iodADQ4rVQjJO6N9RfVERE5p4JfVo7524Dbttj2dnDHn8e+PzkFk1E5qsHBx/k5KaTOTx1+IjlzjkiojEDicX9i/ny1i9Tjst4eISEXNt1Le8+4t1sq2zj6x1fJx/lOT5zPM/JPIcHBx9sNO+LiDAs6YMWl7h4x8VcdNJFU36tc9XG0ka+svUrfPH4L3Js5lgAbu25le9v/z59YV8jc+Wbj2ceTV4THt4+g6m0lyYgYCAaYHVxNd/s+Ca5KMflOy/Hw+Ovj/hrnpV+1l77FaMiH1v/MTornRjWaJ7pWzKKbJvfRuhCAgsOOJgbCpwrcQUsCRArcYWKqxC7mMCCJNiMkroUupC0pfd7fk4zI+MlwWtAckxlQkcXEfGu1e9i8SsW013rJh/l8fBo8psAKMZFmqxpTs2RKiIiz5iswYpERMYUuhDnkqzRuuI6zt58Nu1BO9e9JOn475zj1z2/5urdV9Nd6+ZP2v+Ew4PDOW3haZzSegoD4QC/6v4VV3ddTSWuYC7JssXEDIQDfODpD5CyFLkoR+hCniw+ybryOmpxjbQl2bmAgIyXwcwYCAdYnl9OISrQ4rfM8Ksz+0Qu4tud32ZNcQ1f2foVLnzBhfRH/Vy0/SIGwgHSlibwggOaSsTzPJppJh/l2VzZTGABoQu5cteV/LLrl9z00ptoC9pG7HNL7y1sr2wndGFjWcYyjSykmZGyg5++w8cnJGwEnSkvRSpO8caeN7L46MUALPAXNOrNgU6lYmaNYEpGN9T8thAV2FbZRiEqEFhAm5/UjSa/iayXVRZZRGQOUyAqIlPmtp7buKPvDtaV1hER8YaFb+DR/KPkozx9YR8rcit4YfMLOXfLuSzLLaPiKjjn+E3vb8h6Wa7puoYTsieQi3IMhAOELiRjGdJ+GjPDx6fFa6EUlahYhbSlafKaKMWlpImolybt791nr9lLmliesfIM3nf0+/jgsz84A6/O7HRH7x38bPfP2FrZStVVWZ5bzl8++Zc0+0nwOHzwnwM1FMBV4gqtXmtjdNlclOPDT3+Y8044jxOaTgCSHynu6LuD0IU0+U0H1Ox2ohYEC6jElREZyoyX4ajwqEbGNOWlWOgtnLIyyN7e99T7eH72+Y3gdIiCUBGRuU2BqIhMiHOOW3tv5ZjMMbR6rTxdepozDjtj1C+DT+Sf4Hf9v+P23tvpD/uTJpsYv+j6BRkvQ9rS1FyNr3d8ndMXns7DuYeJ4qgxMX3FVQjjkNjFbC5vxsNL+h9aElwOP2fGzyQjoeKeCRbsmUzZaFJeiibXRCEu8KMdP+Kfn/XPPJJ7hJt7b+adR7yTU1pPmfwXcJbrqHRw/tbzWVtaSzkuJ30ivWYqcYW+sI/+sJ+slx23L+RE+PiNvpVpL03GMkRxRCEusL68nn9Y+w+c3HQyX3v+17hn4B42ljbimz+lQSgkzXOVqZx5bX4bg9EgkGRG81GeDeUN+PgKPkVE5hEFoiIyqpqrcWP3jbyo6UW0B+38YPsPWJpbSjkuk/aSQPLO/jv5yglfocl75sv7pvImPr/p8/SGvdRcjRavJQkeMUIXNjKZoQtZV1rHzupOQheOGOk0a1nwnhk1c7wvn2a235mSZr8Z5xwVV2FrZStX776ah3IP8fDgw9zxijvG3G9ndScXdl7IPx31T7yw5YXjnmc2iVzEQDiAZx539N3BYDjI6QtPxzefz238HNsq24hcRJPX1Aj4h0YkjYnH7QM6UWZGazBypFzf81ngLSCMQwajQZ4sPslH1n0kmfbE1fA5sGawMvekvTSZOEPN1chYhrIrU4trB9wUWkREZicFoiIzbGVhJX21Pv584Z/PdFEatle281+b/4uN5Y1J80m/lWJcJHZxI6CMXMS9A/dy/tbz+eLxX8Q5R3fYzdW7ryYX5UhZqjEYy56ZSkgCwWpYpRInTWpHy3ZNdfbD93yI4ANPfYCYZI7I3rCXd69+N6e0nMLnn7v3GGz3DtzLPf33cGf/nSz+g8UjgvDRFKPijM4Jubm8mQ2lDfSH/VzXfR27qrsaI91WXZXLd13OH7b+ITuqO5J5Nv2RGeehx9MVCAZewCJbxGA0SEelozHA0cE2B5a5xdUnB/XMw1wyLc9k9AMWEZHZQ4GoyAxaW1zLv2/4dwpRgc8e91n+ZMGfcGT6yBktk3OO87aex4bSBmKXjE5ajsukSJHynwkqIZlL8je9v+H47PFsKW9hycCSJMghosVr2Wcg6ZnHQn8hztyMZTp8fByOclym6qoEFhC5iM3lzWwqbwKDV/EqQhfymQ2f4cSmE+mqdVFzNSIiLttxGf92zNjTjtzWcxvf7vw2PzjxB5zYfOKUXsvO6k6u2HUFpy88nVNbT+XKXVfyWP4xniw+STkuA8kcjYYRuxjf88mSJR/nWZZbBkCr3zormj4OZWLzUZ5qXKU5mLlAXmbG0NQssUsy8THxiFYPIiIy9ykQFdkP+ShP2tJ8acuXWBgs5P979v83oS/vkYu4rus6Xtf+Oo7LHNdYflvvbRSiAhVX4fxt55OxDJ8+9tO87Yi3TUn5+8I+nsg/QSWucNrC0xpzG+6o7mB1YTWFuMB9A/exurgah6PJb9rntWW9LIW4wPe3f5+Ml2kEPK3exAIaz/PG3WYqDWVhq66Kj0+TNZHyU1RdlXyU59aeW9mU2YT1GY8XHuf+wftZGCzENx/nHLf13jZmILq1vJXvbf8efWEf3+r8Ft8/6ftTdh07qjv40uYv8UTxCW7ovoFTW09lTXENpbiEV//P4UhZ8mPCcIZRciWylh3xI8NMG8p+ZSwzq8ol06PJayIX5QgsoMlrouIqSQsGERGZNxSIikxQZ6WTT274JD21HhyOXJTj5t6b+Yv2v+CLz/viPgOvO/vu5Ic7fsgPd/yQ2192O53VTq7cfSVLBpYAsNBfSMVVKMZFvrrtq/xh6x9yXPa4MY93IEIX8qUtX+LR3KOEhHx121c5qekkjk4fzdLBpRTjIpGLMEvm2sxYZtxgsslvwjefUpSMUtvut1N11UaAO9uZGa1eK/k4T2vQ2ghM0yTlr7oqm/3N/L7/9xTjIg7HYDRIs9dMOS7TVevi/oH7uWznZXzgWR/gT9v/FIAV+RX8x8b/oBpXcTi2VrY25rmcbCvyK/jsxs825laNXMTy/HI8PNKWbkxZM5a0n25c72zimccifxER0UwXRWZA2kuzyBYlOXwzmlFWXERkvlEgKjKOyEWsLq7me53fo7PS2WjCmbIUxajIbb238Zq21/CXh//liP1yYY6MlyFlKa7tvpZ8lCcm5l/W/QuD0SA9tR5CFzbmZAwIkuxUXOI9a9/DOc89hzcd9qZxy9dV7eLK3Vfy8uaXj7n9ptImLui8gMcLjxO6kNCFVKjwaP7RpFmsozE4zdCE8RNtLpv20iNGqQ3m2G1laNTd0fpFAlSswvLcclKWSgbTcSEpSxFZRM3V+Pymz1OOy3x242e575T78MxjRX4FhaiQBPYYO6s7+XbHt/nYcz7GI/lHeFHTizgqfdR+l7Wj0sEdfXfw3qPey0ODD5H20tzQfQO5KIdhNHlJRndocJ89r2uu8bwkmyuHJmXCRUTmt7n1jVFkmq0J1vCjtT9iZ3UnNVcjsIAWvwWHazTP7A17uXzX5SMC0Upc4V+e/hd21XbR5DVRjstkvSwREauKq2j2mvHw9mrW2+Q14VzSZ/Fbnd9ia2Ur7zjiHRyWOmzMMl626zJu7rmZX8S/oM1v47Xtrx2xPh/l+dymz9FR6UjOUZ+LMYxDDEsymH76oEZEncvBDoxe/rSlqbgKkLyGzV4znuc1socZL0PkIkpxqfE6PlV8ihc0vYAlA0swjAXBAmpxjXyc59qua+msdLKisIKjU0fzy5f8cr/K+HTxaT6z8TP01HpYW1jLisKKRrkCC2j2mhvXkUKDuoiIiMjspkBUZA+bSpu4s/9OOqud3J29m0q5gpFMOZLxR/ZXMzPSlmZzeTP3DdzXaJp5z8A97KztJB/lKcdlIhfR7DWT8TKEcZj01/NSewVAZkZL0IILHd21bn66+6fcP3A/P3nRT/YqZ2+tl1t7b+Wu/ruIXITDcfaWs7nuJdexobSBjmoHj+YepbPayc7qzqR/oJdqZDoDL/nn34TmTRxNW9BGs2umqdrETn9n4/Ua4plHa9BKFEfUqFGICtzVfxeLBxazqbwJI8kuZ/0sNVej6qosyy+jElfYGG1kbWEtL2p50T7LsKa4hgcHHySwgKt2XUUpLlFxFe4ZvAcjGUm0FtXGHRhKREREZLZRICpS55zjgcEHOG/refRH/YQu5OTyyWxp2ULgJdOQjCawgKqr8p+b/pPPHPMZzjzyTG7puYXIRbR6rWT8DM65RqDQHrTjcPtsdpb20lSiCsWoyIbyBu4duJfXLngtt/feTuxiOqud3Nh9YyPIzXpZIhfRF/bxoac/xGA4mDTXNKMaV0lbmqyf1Tx8+8k3n7/s+0t++Zxfjvna+Z6P5zwKFPjZ7p/R6rdSiSs0+89kKDNehkpUSeqE30ouyvHLrl9ydsvZY557RX4F/2/T/6M/7McwIiLSpGn1W5PmwaSSwaKigpqvioiIyJyjQFQOOSsLK8mFOV674LUjskjXdl/LD3f8kGpcJSAgbWn+LPdn7G7fvc/jDQUo5bjMhdsvpORKrCqsAmgM2rNn/8PxpiEYGtQmJqYYFzln8zmckD2BLeUtDEaDtAft9If9pC2Nj09gAWkvTeQiNpU3kfWyxMT4zifrZfHwpm0eyPnGxx/zR4ghQ9ONlOMyvWEvTV7TiIGJ0l6ahSxs1BXDuLXvVk5tO5UzDj9jr+Ntr2zn3M3nUogKpC1NOS7jm98YxTjDM3NqZjzNrykiIiJzjwJRmTfyUZ7uWjdtfhuHpw4fdZtVhVV8esOnyUd5WvwWDg8O58/a/wyAX/X8inKUfOEfGml0IvPWDQ84clGOy3ZeRjkuk7YDHyjGM4+MZRp9FHNRjtXF1cQuJiYmF+Vo8VpIe+kRmdUmv4laWCOMQ1qClikZpVVG1+w14+MnzbhHmWZieNPerJelGBc5d8u5vPmwNzcCVOccndVOfrjjh/SH/cnIt14y8q3DqfmtiIiIzBv6lipzSl/YxwJ/QeOL+/bKdmJivr/9+zyaf5RKnARuH3n2Rzjj8DNo89voqnXxta1fY0tlC31hX2NKjXJcZktlCxt2bWgcL2tZMv7+ZZg881jgL6AaV6m4CrkoR9aypP2DmxKjNWil2TVTjasU4gKhC2n2mqm6Ks45Aj/Yq3mvbz4Lg4XjNv2VyWdmZP3shLZt8poadfDOvjt546I3sra0lp/u+ikP5R4idjE1VxsxmNVEfhQRERERmSsUiMqsF7mIn+76KXf130VHtYM2v41FwSKen30+9wzc0/jSPjRgT83V+E7nd7hq11W85bC3cHvf7QyEA41Rb9OWJutlG1/wa3Gyb0S014A0EzXUdLMclcFB4E/OPy3PksFuUl4qybJ6abIkwc5Y2bGJZnJl5pglU61U4goX77iYnbWdXLHzCiqu0hiFt9VrVQZURERE5i0FojIr1VyNn+76KXf03cHu2m5iF1OOyxhGMSqyo7qDJwtPApCyFGkvTZOXjP6aj/LJ3I21nVy9+2og6aOX9bKjZglTXmpSprsYmlvUx5/0QYF882nxWyb1mDKzPPPIeBm2VrZyV/9d5KM8KUs1fkSIiGa4hCIiIiJTR4GozCjnHGtLa9ld3c3zs8+nPWhnQbCAu/vu5spdV1KOy435LZv95hF9HqtxlchFNPkjpx9pC9oAyMQZaq5GxstMy2ixZsm8kSITlbY0ZcpsLG1MfmwIWkjHafJRXoNLiYiIyLymQFSm1briOm7pvQUPj03lTXTXutle3U7VVZORXc3nBU0vwLmkiW3GMmP22RwakXYsk5XpFJkqQz+slOMyWS9pcp3yUiy0hTNYKhEREZGpp0BU9ks5LnPJjktIe2neuPCN9IV9PFZ4jJWFlbR4LSxKLSJyEae1n8arF7wagEpc4dc9v2Z9aT1Lc0vpqnYREeHhERGRsQy4pCli6EKeyD+RDLaDR3PQPMNXLDJ1zAwPj5h4r+UiIiIi85kC0VnGOUd/2E9r0EpvrZcjU0ce1OinpbjEdV3XsbG8kTWFNRTiAs9KP4u3HvZWAgsox2U6Kh2sLa7lFS2v4B1HvIMbu2+kq9bFh579IY5OH00hKiQjsTrH9zq/x829N1OMivx010+TKSUwKnElGezHAhyOG7pv4LmZ53JK6ync3X831bhK6EJCQlq8lsY1eST/H/7Feygb6pymq5D5r8lvIh/lqcbVvZqZi4iIiMxXCkRnkUpc4dwt5/Lw4MMAOBzvPeq9fPDZH9xr23yUJ+tlx5wnsuZq/HL3L/ld3+/YWN6YBHb1oHFndSdPFJ4gZSlCF+KbTxiHPJp/lOu7rydyEeW4zKriKk5tO5U7eu/gJS0vIbCAx/OPE7mIrJdNRqiNa5gZbUEbzjkwwCUB8KbyJrZVtmFYMheiZWixlnGDSzMjbQc39YnIXJH1so1m6SIiIiKHCgWi08y5ZO7AocxHMSrync7v8EjuEQbDQUIXNvpLVlyFn+z6CUekjuAPW/+Q7dXtXLrzUnJRju5aN0ekjuBvjvgbTl94OotSixrnWFdcx9lbzmZHdQfVuErKUjT7zXh4eObhnKMSV4hdTMYyxMS0+q0MRoPkohzNXjIo0KbyJnZXd1NxFR4efBjfktFgA4Jn+m36PJO5HIovDdq8NsI4uZaAYNz+nCKHMv37EBERkUONAtEpVnM1VuRXsL60noFwgOW55XRWO7ngxAu4rec27hm4h95ab2OOS8+8RiDoRz7FuMg3O75JTEyT10QuyiWjyGKsD9fzzY5v8uOdP+aqF11F6ELu7LuTq7uuJhfmMIwmvwkff0QW0szI+tm9yrqABVTiSmOuylJcwuFotmYCPyAmboxgO9xYGc7ACwhUxUREREREZA+KEiZZOS5zU89NXLP7GrJelnJcpi/soxJXkvkBLdnmg099EA+PqquS9bI0e817Nc3LelliF2MYzjkGw0EyXgaPZP7BQlSg7Mp01bp4x6p34JvfaC6b9tLJnIT70ccy8AIC75kq0eyPHChI00mIiIiIiMhkmFAgamZvAS4AfOAS59z5e6zPAFcCrwJ6gL91zm2e3KLObh2VDn6444esLKykP+ynGldxOAAylkkynObjmUfoQkpxiRa/hRavZcy+YWZGS9DSeO6caywHaA1aycZZqq5KOS4TExNYQJM1qamfiIiIiIjMWuMGombmAxcBbwQ6gEfM7Cbn3Ophm30Q6HPOnWhm7wG+BvztVBR4OvVZH7f13oaPT83VOCF7AhkvwwJ/AUeljwIgdjG/7fstl+y4hN213VTjJMOZtvSY818u8BZQczXSlt6vjOVo2w41f23ymhqB78GMsisiIiIiIjLVbCjLNuYGZq8FznXOvbn+/PMAzrmvDtvmt/VtHjSzANgJHOn2cfC2tjb3qle9ahIuYfLFxOyq7mJ3ZTex7TG/X31Enha/JWkG62rU4mdGpFUQOL8cWTmSrkzXTBdDZpDqgKgOiOrAoU3vv8zWOuCc49jMsRyeOnymizKme+65Z7lz7tTR1k2kae4xwLZhzzuA14y1jXMuNLMB4HCge/hGZvZh4MMAqVSK/v7+iZR/2jkcvX4vTVETTa4JHGAQEgIQWtK0NraYTJyhzbXRFDc1glSZPwIXcGTlyJkuhswg1QFRHRDVgUOb3n+ZrXXA4aAG/dY/00U5INM6WJFz7kfAjwBOPfVUt2zZsuk8/X4pxSXuu+c+XvjaF465fkV+Ba9qfRUZb/QmuDL3rX1wLS967Ytmuhgyg1QHRHVAVAcObXr/ZTbXgWdnnk3KUjNdjDHtqxviRALRTuC4Yc+PrS8bbZuOetPcdpJBi+asJq+JlKV4bva5Y27zwubRg1SZPzbaxn3WAZn/VAdEdUBUBw5tev9FdWBqTKRD4yPASWZ2gpmlgfcAN+2xzU3AP9Ufvwu4a1/9Q0VEREREROTQNW5GtN7n82PAb0mmb7nMObfKzL4ELHPO3QRcClxlZuuBXpJgVURERERERGQvE+oj6py7Dbhtj2VnD3tcBt49uUUTERERERGR+UhzjYiIiIiIiMi0UiAqIiIiIiIi08pmakwhM+sCtszIySfuCPaYC1UOOaoDojogqgOiOnBo0/svqgMH7nnOuVEnYZ2xQHQuMLNlzrlTZ7ocMnNUB0R1QFQHRHXg0Kb3X1QHpoaa5oqIiIiIiMi0UiAqIiIiIiIi00qB6L79aKYLIDNOdUBUB0R1QFQHDm16/0V1YAqoj6iIiIiIiIhMK2VERUREREREZFrNqUDUzI4zs7vNbLWZrTKzs+rLDzOz35nZuvr/F9WXv8jMHjSzipl9ZthxXmhmjw37GzSzT45xzreY2VNmtt7M/nPY8kvN7HEze8LMrjOz1lH2bTazW81sbb285w9b9+1h53/azPon75WavyarDtTXfap+jCfN7Odmlh3jnP9UP+46M/unYcu/YmbbzCw/TplH3c7MMmb2i3rdetjMjj/Al+WQMUPv/+1m1m9mt+yx/IT6+7a+/j6mR9l3X/eA95tZ17D7wIcm4zWa7ya5DpxVf/9XjfUZUN9urM+B15vZo/X37z4zO3GM/fd5rzCzd5qZMzONyDgBB1AH/sGSz+qVZvaAmf3BsGON+t6Ocs6xPgfSZvYjSz7H15rZO8fY/1X18683swvNzOrL312/hljv/8RNch24zMx2m9mT45zzgL8P1rcb67uAvg8egBmqA6NuZ2bfqP/7f8LMbjSzhWPs/z/1bR4zszvM7Dn15Va/L6yvr3/lQb48c4dzbs78Ac8GXll/3AY8DbwE+Drwn/Xl/wl8rf74KOCPgK8AnxnjmD6wk2SOm9HWbQCeD6SBx4GX1NctGLbdt4bOv8f+zcDp9cdpYAnw1lG2+zhw2Uy/vnPhb7LqAHAMsAloqj//JfD+Uc53GLCx/v9F9ceL6uv+uF6e/DhlHnU74F+Bi+uP3wP8YqZf39n+N93vf33d64H/C9yyx/JfAu+pP74Y+Ogo+455DwDeD3xvpl/TufY3iXXgZcCT9fcoAH4PnDjK+fb1OfA08OL6438FLh+jzGPeK+rXcC/wEHDqTL++c+HvAOrA64bdt98KPDzee7vH+fb1OfBF4Mv1xx5wxBhlXlqvBwb8Zth94MXAC4HFev+nvw7Un/858ErgyX2c76C+D9bXjfudAX0fnLV1YF/bAW8Cgvrjrw2dc5T9h9eVT/DMd8Az6vcFq9eTh/dVjvn0N6cyos65Hc65R+uPc8Aaki+UbweuqG92BXBmfZvdzrlHgNo+Dvt6YINzbsso614NrHfObXTOVYFr6ufCOTcIya8YQBOwV2db51zROXd3/XEVeBQ4dpTz/B3w832UUeomuQ4EQJOZBSRfRrePss2bgd8553qdc33A74C31I/9kHNuxwTKPNZ2w8t8HfD6oV/JZXQz8P7jnLsTyA1fVn+f/g/J+zbinHvsO9F7gEzQJNaBF5N82BedcyFwD/COUU455ucAyX1/Qf1xO2PXoX3dK/6H5ItLecyLlhEOoA48UL9/QxLwD/0b3Nd7O9yYnwPAPwNfrZ8nds7tNeG9mT2b5AvoQy751nnlsLKtcc49dUAvxCFsEusAzrl7gd5xTnlQ3wfr203kO4O+D07QDNSBMbdzzt1R/xzZ69h7bDc47GkLz9SVtwNXusRDwML6fWPem1OB6HCWNGP8Q+Bh4Ohh/7h3Akfvx6Hew9j/6I8Btg173lFfNlSGn9TP9yLgu+OUdyFJVuXOPZY/DzgBuGs/yiwcXB1wznUC3wS2AjuAAefcHaNsus86cJAax67fwAaAwyfp2PPeNL3/Yzkc6B/2wTNuvRjjHvDOYc25jtuP8wsH/TnwJPBnZna4mTWT/CI92nuwr3vAh4DbzKwD+EfgfPZDvfnVcc65W/dnP3nGAdSBD5JkHmDi9/dRtxvW/O5/LGmifa2ZjXbOY+r7jHceOQAHWQcmatK+D45F3wcP3DTVgYn6530de6iJNvAPwNn1xVP5XXNWm5OBaL39/fXAJ/f4dYH6r40TGgrYkj5dbwOuPZByOOc+ADyH5FeYv93HeQKSYPdC59zGPVa/B7jOORcdSBkOVQdbB+p9Bt5OctN/DtBiZu+douLKJJtr7/8Y94CbgeOdc68gybBcMdb+sreDrQPOuTUkmcg7gNuBx4D9vQ9/CjjDOXcs8BOSZnkTYmZefftP7+c5pW5/64CZnU7yBfRzk1SEgCTz8YBz7pXAgyQ/cMk0mQV1YOhcE/o+OA59HzwAs6UO1I/9BSAEfjbWNs65Lzjnjqtv87HJLsNcM+cCUTNLkVS4nznnbqgv3jWUwq7/f/cED/dW4FHn3K76vscN6zD+EaCTkb+QH1tf1lC/YVxDktnwh+3/pWGb/QhY55z7zihl2FdGVkYxSXXgDcAm51yXc64G3AC8zsxeM+w9fBsTqAN7lG2sOjCaxrHrgUo70DPOPoe8aX7/x9JD0nQmqD8/Fujcn3uAc67HOVepP70EeNW4Fy/A5H0OOOcudc69yjn350Af8PREPwfM7EjgD5xzD9eX/4KkDk30HtBG0k91sZltJukXdJNpwJoJ2d86YGavIPl39nbn3NB9dqz3dqKfAz1AkeT+AcmP2q8cpQ50MrKp3j4/R2RiJqkOjHXsqfo+uC/6PrifprkOjFeW9wN/BfxDPQDGzH5S3/+2UXb5GTA0uNl+fdecT4LxN5k9zMyAS4E1zrnhvzzfBPwTSbOofwJ+PcFDjmiL75zbBpwy7HwBcJKZnUBSId4D/H29HC9wzq2vP34bsLZ+EzqFYczsyyQBxl4jYprZi0gGPnhwguU95E1iHdgK/LElTfJKJH2Fl9W/VJ4y7HyHAefVM2iQdEj//FgHHa0O7MNQmR8E3gXcNXTzktFN9/s/FuecM7O7Sd63a4bOuT/3ADN79rDmQ28j+SVdxjGZnwNmdpRzbreZPZekf+gfO+f6mcDnAEng2m5mJzvnngbeWC/ThO4BzrkB4Ihh51lMMpjSsvH2PdTtbx2ov783AP9Yf6+GPMIo761zbhUT+Byo3wduBk4jaU75emD1GPeBQTP7Y5Kmg+/jAJtvSmIS68CopuL74DjXo++D+2m668A4ZXkL8FngL5xzxWHH+MAe253knFtXf/p2YO2wMn/MzK4BXkPSXWjcMUjmBTcLRkya6B/wpyQp9idImlE9RtKv53CSflfrSEY+PKy+/bNI2lkPAv31xwvq61pIfs1sH+ecZ5CMxLUB+EJ9mQfcD6wk6Wf0M4aNhDVs32Pr5V0zrLwfGrb+XOD8mX5d59LfJNeBL5LcBJ4ErgIyY5zzn4H19b8PDFv+9frx4vr/zx1j/1G3A7Ikv6CvJxlR8fkz/frO9r8Zev+XAF0kAWsH8Ob68ufX37f19fdxr/33dQ8gGeBkFcnoi3cDL5rp13cu/E1yHVgCrK6/B6/fxzn3+hyoL/9rks+Bx0lGPR313/BE7hVo1NSprAOXkPxwMLTtsvHe21HOOdbnwPNIRj1+on7u546x/6n1e80G4HuADatDHUAF2AX8dqZf37nwN8l14OckYwXU6u/FB8c45wF/H6xvO+Z9AH0fnCt1YNTt6veFbcOOffEY+19frydPkHTPOaa+3ICL6nVrJYfQZ8HQjVBERERERERkWsy5PqIiIiIiIiIytykQFRERERERkWmlQFRERERERESmlQJRERERERERmVYKREVERERERGRaKRAVERE5CGYW1SctX2Vmj5vZp81sn5+vZna8mf39dJVRRERktlEgKiIicnBKzrlTnHMvBd4IvBU4Z5x9jgcUiIqIyCFL84iKiIgcBDPLO+dahz1/PvAIcATwPOAqoKW++mPOuQfM7CHgxcAm4ArgQuB84DQgA1zknPvhtF2EiIjINFMgKiIichD2DETry/qBFwI5IHbOlc3sJODnzrlTzew04DPOub+qb/9h4Cjn3JfNLAPcD7zbObdpGi9FRERk2gQzXQAREZF5LAV8z8xOASLg5DG2exPwCjN7V/15O3ASScZURERk3lEgKiIiMonqTXMjYDdJX9FdwB+QjMtQHms34OPOud9OSyFFRERmmAYrEhERmSRmdiRwMfA9l/R9aQd2OOdi4B8Bv75pDmgbtutvgY+aWap+nJPNrAUREZF5ShlRERGRg9NkZo+RNMMNSQYn+lZ93feB683sfcDtQKG+/AkgMrPHgcuBC0hG0n3UzAzoAs6cnuKLiIhMPw1WJCIiIiIiItNKTXNFRERERERkWikQFRERERERkWmlQFRERERERESmlQJRERERERERmVYKREVERERERGRaKRAVERERERGRaaVAVERERERERKaVAlERERERERGZVv8/S2ukS4ZS3QcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "((asset.PCTRET_1 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=[\"limegreen\"], title=\"B&H Percent Returns\", alpha=0.9, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x130470400>"
      ]
     },
     "execution_count": 16,
     "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 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\")[-1], title=\"B&H Cum. Active Returns\", alpha=0.4, grid=True).axhline(0, color=\"black\")\n",
    "((asset.ACTRET_1 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=[\"limegreen\"], title=\"B&H Cum. Active Returns\", alpha=0.65, 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 (ipykernel)",
   "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
}