01_intpy_day_2_overview.md

Intermediate Python for Finance Training

This is the Gist for Day 2 of the Intermediate Python for Finance Training in London, 29. November 2017

Agenda

Module 3 — pandas

This module is about data analysis and visualization with pandas for finance.

pandas has become the central data analysis tool in the Python ecosystem. It is powerful, among others, in handling financial time series data, in visualizing such data and implementing algorithms on such data sets.

The goal of this module is to be aware of the capabilities of pandas and to be able to apply pandas to typical financial analytics tasks.

Module 4 — OOP

The final module addresses object-oriented programming (OOP) in Python based on finance examples.

OOP is a powerful programming paradigm with many benefits over simple procedural implementations. Among others, it allows a simplified modeling of real-world and financial object, to avoid redundancies, to simplify code maintenance and re-usability.

The goal of this module is to be aware of basic OOP features in Python and to implement financial algorithms in a re-usable fashion.

Notebooks & Code Files

Below you find the all the notebooks and code files as worked on during this day.

The Python Quants

http://twitter.com/dyjh

[email protected] | http://tpq.io

http://pyalgo.tpq.io | http://certificate.tpq.io

02_numpy_finance.ipynb

03_pandas_basics.ipynb

04_pandas_finance.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='http://hilpisch.com/tpq_logo.png' width=\"300px\" align=\"right\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Intermediate Python &mdash; Day 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**pandas for Finance**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pylab import plt\n",
    "plt.style.use('seaborn')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Financial Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = pd.read_csv('http://hilpisch.com/tr_eikon_eod_data.csv',\n",
    "                 index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>INTC.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "      <th>GS.N</th>\n",
       "      <th>SPY</th>\n",
       "      <th>.SPX</th>\n",
       "      <th>.VIX</th>\n",
       "      <th>EUR=</th>\n",
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       "      <th>GLD</th>\n",
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       "    <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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>30.572827</td>\n",
       "      <td>30.950</td>\n",
       "      <td>20.88</td>\n",
       "      <td>133.90</td>\n",
       "      <td>173.08</td>\n",
       "      <td>113.33</td>\n",
       "      <td>1132.99</td>\n",
       "      <td>20.04</td>\n",
       "      <td>1.4411</td>\n",
       "      <td>1120.00</td>\n",
       "      <td>47.71</td>\n",
       "      <td>109.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>30.625684</td>\n",
       "      <td>30.960</td>\n",
       "      <td>20.87</td>\n",
       "      <td>134.69</td>\n",
       "      <td>176.14</td>\n",
       "      <td>113.63</td>\n",
       "      <td>1136.52</td>\n",
       "      <td>19.35</td>\n",
       "      <td>1.4368</td>\n",
       "      <td>1118.65</td>\n",
       "      <td>48.17</td>\n",
       "      <td>109.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>30.138541</td>\n",
       "      <td>30.770</td>\n",
       "      <td>20.80</td>\n",
       "      <td>132.25</td>\n",
       "      <td>174.26</td>\n",
       "      <td>113.71</td>\n",
       "      <td>1137.14</td>\n",
       "      <td>19.16</td>\n",
       "      <td>1.4412</td>\n",
       "      <td>1138.50</td>\n",
       "      <td>49.34</td>\n",
       "      <td>111.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>30.082827</td>\n",
       "      <td>30.452</td>\n",
       "      <td>20.60</td>\n",
       "      <td>130.00</td>\n",
       "      <td>177.67</td>\n",
       "      <td>114.19</td>\n",
       "      <td>1141.69</td>\n",
       "      <td>19.06</td>\n",
       "      <td>1.4318</td>\n",
       "      <td>1131.90</td>\n",
       "      <td>49.10</td>\n",
       "      <td>110.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>30.282827</td>\n",
       "      <td>30.660</td>\n",
       "      <td>20.83</td>\n",
       "      <td>133.52</td>\n",
       "      <td>174.31</td>\n",
       "      <td>114.57</td>\n",
       "      <td>1144.98</td>\n",
       "      <td>18.13</td>\n",
       "      <td>1.4412</td>\n",
       "      <td>1136.10</td>\n",
       "      <td>49.84</td>\n",
       "      <td>111.37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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       "               AAPL.O  MSFT.O  INTC.O  AMZN.O    GS.N     SPY     .SPX   .VIX  \\\n",
       "Date                                                                            \n",
       "2010-01-04  30.572827  30.950   20.88  133.90  173.08  113.33  1132.99  20.04   \n",
       "2010-01-05  30.625684  30.960   20.87  134.69  176.14  113.63  1136.52  19.35   \n",
       "2010-01-06  30.138541  30.770   20.80  132.25  174.26  113.71  1137.14  19.16   \n",
       "2010-01-07  30.082827  30.452   20.60  130.00  177.67  114.19  1141.69  19.06   \n",
       "2010-01-08  30.282827  30.660   20.83  133.52  174.31  114.57  1144.98  18.13   \n",
       "\n",
       "              EUR=     XAU=    GDX     GLD  \n",
       "Date                                        \n",
       "2010-01-04  1.4411  1120.00  47.71  109.80  \n",
       "2010-01-05  1.4368  1118.65  48.17  109.70  \n",
       "2010-01-06  1.4412  1138.50  49.34  111.51  \n",
       "2010-01-07  1.4318  1131.90  49.10  110.82  \n",
       "2010-01-08  1.4412  1136.10  49.84  111.37  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 1972 entries, 2010-01-04 to 2017-10-31\n",
      "Data columns (total 12 columns):\n",
      "AAPL.O    1972 non-null float64\n",
      "MSFT.O    1972 non-null float64\n",
      "INTC.O    1972 non-null float64\n",
      "AMZN.O    1972 non-null float64\n",
      "GS.N      1972 non-null float64\n",
      "SPY       1972 non-null float64\n",
      ".SPX      1972 non-null float64\n",
      ".VIX      1972 non-null float64\n",
      "EUR=      1972 non-null float64\n",
      "XAU=      1972 non-null float64\n",
      "GDX       1972 non-null float64\n",
      "GLD       1972 non-null float64\n",
      "dtypes: float64(12)\n",
      "memory usage: 200.3 KB\n"
     ]
    }
   ],
   "source": [
    "raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>INTC.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "      <th>GS.N</th>\n",
       "      <th>SPY</th>\n",
       "      <th>.SPX</th>\n",
       "      <th>.VIX</th>\n",
       "      <th>EUR=</th>\n",
       "      <th>XAU=</th>\n",
       "      <th>GDX</th>\n",
       "      <th>GLD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "      <td>1972.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>86.53</td>\n",
       "      <td>40.59</td>\n",
       "      <td>27.70</td>\n",
       "      <td>401.15</td>\n",
       "      <td>163.61</td>\n",
       "      <td>172.84</td>\n",
       "      <td>1727.54</td>\n",
       "      <td>17.21</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1352.47</td>\n",
       "      <td>34.50</td>\n",
       "      <td>130.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>34.04</td>\n",
       "      <td>14.39</td>\n",
       "      <td>5.95</td>\n",
       "      <td>257.12</td>\n",
       "      <td>37.17</td>\n",
       "      <td>42.33</td>\n",
       "      <td>424.35</td>\n",
       "      <td>5.92</td>\n",
       "      <td>0.12</td>\n",
       "      <td>195.38</td>\n",
       "      <td>15.44</td>\n",
       "      <td>19.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>27.44</td>\n",
       "      <td>23.01</td>\n",
       "      <td>17.66</td>\n",
       "      <td>108.61</td>\n",
       "      <td>87.70</td>\n",
       "      <td>102.20</td>\n",
       "      <td>1022.58</td>\n",
       "      <td>9.19</td>\n",
       "      <td>1.04</td>\n",
       "      <td>1051.36</td>\n",
       "      <td>12.47</td>\n",
       "      <td>100.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>57.57</td>\n",
       "      <td>28.12</td>\n",
       "      <td>22.23</td>\n",
       "      <td>202.66</td>\n",
       "      <td>144.23</td>\n",
       "      <td>132.64</td>\n",
       "      <td>1325.53</td>\n",
       "      <td>13.25</td>\n",
       "      <td>1.13</td>\n",
       "      <td>1214.56</td>\n",
       "      <td>22.22</td>\n",
       "      <td>116.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84.63</td>\n",
       "      <td>36.54</td>\n",
       "      <td>26.41</td>\n",
       "      <td>306.42</td>\n",
       "      <td>162.09</td>\n",
       "      <td>178.80</td>\n",
       "      <td>1783.81</td>\n",
       "      <td>15.65</td>\n",
       "      <td>1.29</td>\n",
       "      <td>1288.82</td>\n",
       "      <td>26.59</td>\n",
       "      <td>123.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>111.87</td>\n",
       "      <td>50.08</td>\n",
       "      <td>33.74</td>\n",
       "      <td>559.45</td>\n",
       "      <td>184.11</td>\n",
       "      <td>208.01</td>\n",
       "      <td>2080.15</td>\n",
       "      <td>19.20</td>\n",
       "      <td>1.35</td>\n",
       "      <td>1491.98</td>\n",
       "      <td>49.77</td>\n",
       "      <td>145.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>169.04</td>\n",
       "      <td>83.89</td>\n",
       "      <td>45.49</td>\n",
       "      <td>1110.85</td>\n",
       "      <td>252.89</td>\n",
       "      <td>257.71</td>\n",
       "      <td>2581.07</td>\n",
       "      <td>48.00</td>\n",
       "      <td>1.48</td>\n",
       "      <td>1897.10</td>\n",
       "      <td>66.63</td>\n",
       "      <td>184.59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        AAPL.O   MSFT.O   INTC.O   AMZN.O     GS.N      SPY     .SPX     .VIX  \\\n",
       "count  1972.00  1972.00  1972.00  1972.00  1972.00  1972.00  1972.00  1972.00   \n",
       "mean     86.53    40.59    27.70   401.15   163.61   172.84  1727.54    17.21   \n",
       "std      34.04    14.39     5.95   257.12    37.17    42.33   424.35     5.92   \n",
       "min      27.44    23.01    17.66   108.61    87.70   102.20  1022.58     9.19   \n",
       "25%      57.57    28.12    22.23   202.66   144.23   132.64  1325.53    13.25   \n",
       "50%      84.63    36.54    26.41   306.42   162.09   178.80  1783.81    15.65   \n",
       "75%     111.87    50.08    33.74   559.45   184.11   208.01  2080.15    19.20   \n",
       "max     169.04    83.89    45.49  1110.85   252.89   257.71  2581.07    48.00   \n",
       "\n",
       "          EUR=     XAU=      GDX      GLD  \n",
       "count  1972.00  1972.00  1972.00  1972.00  \n",
       "mean      1.25  1352.47    34.50   130.60  \n",
       "std       0.12   195.38    15.44    19.46  \n",
       "min       1.04  1051.36    12.47   100.50  \n",
       "25%       1.13  1214.56    22.22   116.77  \n",
       "50%       1.29  1288.82    26.59   123.90  \n",
       "75%       1.35  1491.98    49.77   145.43  \n",
       "max       1.48  1897.10    66.63   184.59  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw.describe().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets = np.log(raw / raw.shift(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>INTC.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "      <th>GS.N</th>\n",
       "      <th>SPY</th>\n",
       "      <th>.SPX</th>\n",
       "      <th>.VIX</th>\n",
       "      <th>EUR=</th>\n",
       "      <th>XAU=</th>\n",
       "      <th>GDX</th>\n",
       "      <th>GLD</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",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.000</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.003</td>\n",
       "      <td>-0.035</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.010</td>\n",
       "      <td>-0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>-0.016</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>-0.018</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>-0.002</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>-0.017</td>\n",
       "      <td>0.019</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>-0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>0.007</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.027</td>\n",
       "      <td>-0.019</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.003</td>\n",
       "      <td>-0.050</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            AAPL.O  MSFT.O  INTC.O  AMZN.O   GS.N    SPY   .SPX   .VIX   EUR=  \\\n",
       "Date                                                                            \n",
       "2010-01-04     NaN     NaN     NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "2010-01-05   0.002   0.000  -0.000   0.006  0.018  0.003  0.003 -0.035 -0.003   \n",
       "2010-01-06  -0.016  -0.006  -0.003  -0.018 -0.011  0.001  0.001 -0.010  0.003   \n",
       "2010-01-07  -0.002  -0.010  -0.010  -0.017  0.019  0.004  0.004 -0.005 -0.007   \n",
       "2010-01-08   0.007   0.007   0.011   0.027 -0.019  0.003  0.003 -0.050  0.007   \n",
       "\n",
       "             XAU=    GDX    GLD  \n",
       "Date                             \n",
       "2010-01-04    NaN    NaN    NaN  \n",
       "2010-01-05 -0.001  0.010 -0.001  \n",
       "2010-01-06  0.018  0.024  0.016  \n",
       "2010-01-07 -0.006 -0.005 -0.006  \n",
       "2010-01-08  0.004  0.015  0.005  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets.head().round(3)"
   ]
  },
  {
   "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>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>INTC.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "      <th>GS.N</th>\n",
       "      <th>SPY</th>\n",
       "      <th>.SPX</th>\n",
       "      <th>.VIX</th>\n",
       "      <th>EUR=</th>\n",
       "      <th>XAU=</th>\n",
       "      <th>GDX</th>\n",
       "      <th>GLD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "      <td>1971.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.000</td>\n",
       "      <td>-0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.016</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.132</td>\n",
       "      <td>-0.121</td>\n",
       "      <td>-0.095</td>\n",
       "      <td>-0.135</td>\n",
       "      <td>-0.137</td>\n",
       "      <td>-0.067</td>\n",
       "      <td>-0.069</td>\n",
       "      <td>-0.351</td>\n",
       "      <td>-0.027</td>\n",
       "      <td>-0.089</td>\n",
       "      <td>-0.114</td>\n",
       "      <td>-0.092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.007</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>-0.008</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>-0.008</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>-0.041</td>\n",
       "      <td>-0.004</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>-0.014</td>\n",
       "      <td>-0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.010</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.085</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.146</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.405</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.047</td>\n",
       "      <td>0.107</td>\n",
       "      <td>0.048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         AAPL.O    MSFT.O    INTC.O    AMZN.O      GS.N       SPY      .SPX  \\\n",
       "count  1971.000  1971.000  1971.000  1971.000  1971.000  1971.000  1971.000   \n",
       "mean      0.001     0.001     0.000     0.001     0.000     0.000     0.000   \n",
       "std       0.016     0.014     0.014     0.020     0.017     0.009     0.009   \n",
       "min      -0.132    -0.121    -0.095    -0.135    -0.137    -0.067    -0.069   \n",
       "25%      -0.007    -0.007    -0.008    -0.009    -0.008    -0.003    -0.003   \n",
       "50%       0.001     0.000     0.001     0.001     0.001     0.001     0.001   \n",
       "75%       0.010     0.008     0.008     0.012     0.009     0.005     0.005   \n",
       "max       0.085     0.099     0.089     0.146     0.090     0.045     0.046   \n",
       "\n",
       "           .VIX      EUR=      XAU=       GDX       GLD  \n",
       "count  1971.000  1971.000  1971.000  1971.000  1971.000  \n",
       "mean     -0.000    -0.000     0.000    -0.000     0.000  \n",
       "std       0.075     0.006     0.010     0.024     0.010  \n",
       "min      -0.351    -0.027    -0.089    -0.114    -0.092  \n",
       "25%      -0.041    -0.004    -0.005    -0.014    -0.005  \n",
       "50%      -0.006     0.000     0.000    -0.000     0.000  \n",
       "75%       0.035     0.003     0.006     0.014     0.006  \n",
       "max       0.405     0.030     0.047     0.107     0.048  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets.describe().round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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hNgmShBBCCNEls9mCWq0iXt/56hGJSbGewGbaccO5+Oo5nmMrXtlKU0MrT97zNS88vNqz\nv7ZamTjlcDrJykviuMWjwvQEvSNBkhBCCCG61NpiJV6v67J3R58Y47Ot0fiGGMVFde2L17rUVrZg\ntzlw2J3ExGhJTG7vqXJ2PHkASJAkhBBCiE45nU6aG9uI18f4HSsYm9Hp+zRadZfbANs2HMPcouQl\nxcRqSUppL5fT3DjwidwSJAkhhBCiU0X7q7HbnaRmxPsdmzAt1/Pae8Yb+PcklR71Pe5WX6vUU4qJ\n1aBPaA/Exk/N6fU9h0rUlABwe+ml51m+/BVee20FsbGx/P3vf+Hbb79ixYpPiIlRfjgm0x5++tMf\n8dBDT6BSqXjmmSc976+srCA5OYU77riLiy8+nyeffJ7x4ycA8Pbbr1NdXe1XQqC2tpZHH32QsrJS\nHA4HWVnZXHfd9WRkZPbfgwshhBA9VHq0jg/f2AHAsAKlYGScXudZniRQ75KbRuM7NLdjk++KFJlZ\niVRVNNFQpyRv62I0PsN5hpykvj9AH0VdT9Knn37E0qWn8Pnnn3j2ZWRksnZteyLZJ5986FmrbcaM\nWTzyyFM88shT3HHHXahUKq677npAKTJ51123Y7F03iXodDq55Zbfc8IJJ/LII0/x2GP/5swzz+HG\nG6/Hbrd3+j4hhBBioL393y2e15nZSq2jcy+dDiiVtb1noy1aNsbnvWpN5yHGCaePo2Cc0lHw1Ycm\nAOLilaTw7185mwsvn9npe/tTVAVJmzZtIC9vGOeddyFvvrncs3/ZslP57LOPAXA4HOzdu4cJEyb6\nvNdms/GnP93EJZf8mKlTlV+QYcOGM3fufJ56qvPikSbTbhITEzn++CWefXPmzCU/fxhbt24O4dMJ\nIYQQodMxcTotUykYmZ6ZwDU3ncAFl830BDaAz9IkAGp14CTv8388g4nT8oiL9x3MajMrVbwzshLJ\nyk3u8/2HQr8Pt63+4gAH91T06RpqjRqHvb3OwujxWT41GTrz3nvvcPbZ5zFiRAE6nY6dO5UuxAkT\nJvH1119iNpvZsWMbM2fO5vDhgz7vffDBfzJq1GjOPfcCn/1XXfVzrr768k4DnuLiYvLyhvntz8vL\np6ystNt7FkIIIQZCVXmTz7ZWq/G8DjTLzTtgcp8zsjCd5kYLVRXt14qJ0QY8f/KsvD7fc6hFTU9S\nQ0MDa9asYvnyV/jtb6+jubmJN9/8n+f4okWL+fbbr/n004845ZTTfd77/vsrOHBgH9dff6PfdWNi\nYvjjH2/jH//4G2Zzq99xg8FAWVmJ3/5jx46QnT3wSWlCCCFER8cO1/L68xuDOnfZOROYOmeYp5Ck\ntzMumsqFV/hW6Xb3IHnPZFtyupGUNH0f7jg8uu1JMhqNVwBXuDbjgOlAjslkCpym3o0FJxUG1evT\nFYMhicrKxu5P9PLJJx9w1lnncu21vwagtbWViy46x5N0fcopp/Hgg/ehUqnIz2/v+dm9eycvvvgc\njz32b7TawM1lNI7n5JNP47//fcGz6K3blCnTqK6uZuXKb1i0aDEAa9eu5tixY0yfHhljrkIIIYS3\nd1/1XyakM2MnZjN2Ynanx9VqFSeeYeTLD5Tco1hXD1Jyans+U1wXRSoHUrdBkslkeh54HsBoND4K\nPNvbAGkgvfvuO9x66x2e7bi4OE444STee+9tLrzwB4wYUUBdXS1nnXWuz/uefPJRnE4nf/7zzZ59\ner3er1fpxz/+CatWfevZfuyxf7FkyVImTpzMPfc8wL/+dR8vvvgcAFlZ2dx774NoNBqEEEKISGL3\nSmdxG1aQ1qdr5gxLIV6vY0Rhhqc0gHf17o5Db5FCFWxFS6PROBv4p8lkWtLVeZWVjWEvkdmbnqSh\nJNqfH6QNQNoApA1A2gCkDSC0bdDc1MZ/Hlnj2b7qt4vQ6jRhWUvt8bu/AuDiq+eQlpHQ6+v05fkN\nhqROH6wnidt/BG7v7qS0NL1Pcle4GAwDXz9hIEX784O0AUgbgLQBSBuAtAGErg3sVt+epLz8vvUi\ndeXinx7Hnm2ljBmX3elsuGCF43cgqCDJaDSmAuNNJtOX3Z1bW9vS55vqTrT/1RDtzw/SBiBtANIG\nIG0A0gYQ2jYoOdaeUXPq+ZPC2rZpBj3zlxZSXd3U/cld6GNPUqfHgp3dthj4rFefLoQQQohBw+yq\npn3CaeMYbTQM8N0MrGCDJCNwsNuzhBBCCDGomZuVVSQiNZm6PwU13GYyme4N940IIYQQYuC5e5K8\nF5uNVlFTTFIIIYQQ3TO3KD1J8QnSkyRBkhBCCBHFHA4njfXtK0aYm5WepHi99CT1+9ptQgghhIgc\nX39kYs+2MoyTsznhNCOlx+rRaNXoYqTgsQRJQgghRBTbs60MANOOckw7ygEYMTo9LMUjBxsZbhNC\nCCGEj4nTcwf6FiKCBElCCCGE8JGdlzzQtxARJEgSQgghhMcp501Cnxg70LcRESRIEkIIIaJUW6sV\njdY3FBhtzBygu4k8EiQJIYQQUerQvmrsNgfjJmV79knCdjuZ3SaEEEJEqZamNkDpPaosa2SsV7Ak\nJEgSQggholZbqw2A+IQYLr76uAG+m8gjw21CCCFElKqvNQOQIInaAUmQJIQQQkSppoY2NFo1SSlx\nA30rEUmCJCGEECJK2Wx2tFoJBTojLSOEEEJEKZvVgVYna7R1RoIkIYQQYoirqWzGZrN7th0OB4f2\nVmJps0lPUhdkdpsQQggxhNXXtvC/Z9aTmh7PsnMmsm39MfbuLPccT0ySpO3OSJAkhBBCDGHFRXUA\n1NWYef35jX7HY+MkFOiM9LEJIYQQA8zpdIbt2qVH67s8HhuvC9tnD3YSJAkhhBAD6IPl23niH19T\nX9sS8mtbLXaOHKzx2afVqllyutGznT8iNeSfO1RIH5sQQggxQKxWO0UHqgF45+WtXHL1cRw7XEPB\n2Mxer6G2f3cF2zYcw2qxM3vhSFrNVgrHG0jPTGD46HQSk2LRxWjYuLqI0UYDk2flh/KRhhQJkoQQ\nQogB8s1Hez2vmxvbWP3FfnZtKWXRsjFMmT2sV9f89J1dntefvK28HlaQxsTpeT7n/ejn83p1/Wgi\nw21CCCHEACkvbfDZ3rWlFICy4q7ziDrTWW5T/kgZUusNCZKEEEKIAWC3O6ivMQc8povp3UCP3e7w\n25duSCAlTd+r60U7CZKEEEKIAWButgCQnZ/MaRdM8jmmVvcuH8lqsfvtM+Qk9epaQoIkIYQQYkBY\nrUpAk2FIICMr0edYW6u1V9dsa7X57UtJi+/VtYQkbgshhBADwmZVhsZ0Og2JyXE+x+prW3t0LbvN\nwXv/24o7JUmfGENLk9JTJUFS7wUVJBmNxpuBc4AY4DGTyfRMWO9KCCGEGOLcQ2PaGI3f8Jr3OmvB\nKC9t4OihWs923vBU9u+uACA5Na6zt4ludDvcZjQalwALgIXACcDwMN+TEEIIMeS5gySdTgNA3vAU\nzzGHo2cVuJub2ny2s/OSPa+TU6UnqbeCyUk6FdgOvAW8C7wX1jsSQgghosAn7+wEQBejBEnnXDqd\n4xaPAsDZwyDJ0ubb81Q4wQBATKyWOFl2pNeCGW7LBEYCZwGjgBVGo3G8yWQK30IzQgghxBBmtzs8\nOUnuoTaVSsWsBSPZvbW0xz1JljYlYXvUuEyOP3ksCYmx/PCaudht/iUBRPCCCZKqgT0mk8kCmIxG\nYytgACoCnZyWpker1YTwFgMzGKJ7SmO0Pz9IG4C0AUgbgLQBDL42aGpoT8xOSIj1uX+dToPVYg/6\nmZwOJ2+9uAmA2fNHUjA6Exh8bdJX4XjeYIKklcCvjUbj/UAukIASOAVUG4YF+joyGJKorGwM++dE\nqmh/fpA2AGkDkDYAaQMYnG1QXdnkeZ0/KtXn/h1OJzabPehnKjpQTVmxUrlbrVMPurYIhb78DnQV\nXHWbk2Qymd4DNgPrUHKSrjWZTD1LuxdCCCEEZcX11Ne20Nqi1EGatXCk3+iL0+nE3GKluqIpYAXt\njlrNyrVyhiWTnpkQ+puOYkGVADCZTDeG+0aEEEKIocxuc/DWi5sBOOW8iQDEB0iqdi9V8tqzG4iL\n13H5dQswbS9jzARDwOVK3HlHkzosYCv6TipuCyGEEP2grqY9HaWhTslJitN3PfOs1Wxl6/qjfPWh\niY/f3hXwHJsrSNL0Qz5wtJEgSQghhOgHtdXtQdLarw4CBDU9v6aiGYCjB2twOv1nvbl7krQ6+UoP\nNWlRIYQQIkyslva11Gqrmv2Od1yOJBDvatwtzRbqalrYtuEYTqcTp9OJzbUGnFYrX+mhJmu3CSGE\nEGGwf3cFn63YxRkXTSU2TsuGVUV+5wRaMuTcS6fzzstbPNt1XrPGD+2t4ttP9gGw6rP9qFR41mvT\nSJAUchIkCSGEECFUV9PC+69t8+Qdff2RiaaGNr/zlp41Ho3GP7DJG5Hqs+2+DuAJkNy8R9+kJyn0\npEWFEEKIEPr0nV0+gU2gAAm6T9p2a2myBHWeJG6HngRJQgghRAjVeOUejRqX6XPMkJPoed2TNdUC\nDct1JD1JoSctKoQQQvRRW6sNh0OZZeawt4+BzZg3wvM6ISmGxaeOA2DMBAOZ2YkEK93QfZFImd0W\nepKTJIQQQvRBc1Mb/3lkDROn53qCIABdjAZDThJTZudTWdbIsrMnkpQSx8//sKTba06Zlc/2jcWe\n7YSkWM/rcZOyGTUuk7QMPeu+PcxBUyXQs54pERwJkoQQQog+OHqoFoBdW0pZcFIhAEkpcVxw2UzU\nahWLlo3t8TUXLC3EarWzZ1sZAAkJMZ5jCcmxjDYafM6fPCMflUqFCC0JkoQQQog+qCht8Lz+9/0r\nAcjOT0bvFdj0lFqtJjk13rOtT2zvSUr06lU6bnEBmdmJLDtzQr8sMB9tZABTCCGE6INAs9diYvve\nB+FdHiAtQ+957Z2gnZaRwKwF/ovkDnb1zRbe+PoALa3WAb0PCZKEEEKIPijaX+23r7UluGn7XUlJ\na5/RFhOnZc7xBYB/HaWhaP3uct5fU4TpaN2A3ocMtwkhhBC95F4SpCNDTlKfr52U0j7cptGombVg\nJDPmjQhYgHKoaTIrPUhxuoHtIZMgSQghhAhC6bF6dDo1cfE6z5prra3K2mwFYzIYOykbQ04SDXVm\nhhWk9fnzEpLac5o0GhUqlQqNJjqSs1tc7aqPG9gZexIkCSGEEN2wWe28/dJmz7Z7Gv/2DccASM3Q\nM2ZCFgApafF+7+8N7yn90bYuW22TkueVktj75PdQkCBJCCGE6EbRAd+8o8b6Vr79ZC9FB2qI1+uY\nPnd4yD/Te0p/NAyxeauqb0WnVZPShxmCoRBdrS6EEEIE6dC+KrauOwrAF+/v8Tn20uNrKTpQA0By\najzx+vB+mQ+FIMlmd/DoW9v5ZmtJt+dW17eSkRw34LWfpCdJCCGECOCjN3YAMNpowGZVlhwpHG/g\nwJ5Kn/NiYsOXXHzaBZOoqWweEsNtm/dVsdFUyUZTJYum5qLuJAAyt9loMlspCEHye18N/lYXQggh\nwuitFzd5Xp901ni/47qY8PU3jBpnYNbCgrBdvz9t9xqyPFTS0Ol5ja7yCQOdjwQSJAkhhBB+nM72\nRWqbm5Qv7bknjEKr1TB+So7PuflRULeot3YfruG3j6zk7W8PUt3Q6tn/9xc3sr+4PuB7rK4FgnUR\nUCBTgiQhhBCiA4fD6bdv+Kh0ACZMz/XZrwvjcNtgdrCkgXtf3UJdk4UVqw6z50gtqV69Qw++ttXv\nPV9uLubrzcrCvtoIKHcgQZIQQgjRQaAikQmuNdNy8lO4+Oo5nv2hWIJkKNrboVq20wnjR7TXj2pp\ns1Hj1bvkcDh58WMTn21UyiroIiBZfeDvQAghhOiF5sY2qiuawnJtqytR21u8Xuf1ur1HJCZGepIC\nqagz++2b5OqNc3tgeXtvUmWH87USJAkhhBC98/JT3/HasxuwWmwhv3bHnqSTzhrvMx3du9CjOgK+\nzCNReU2L374Fk3PI9Vqs1zswOlbZ7HOuNgJm9EkfoRBCiEHJPS2/rsYMIe7McV97yqx8Fp08NuA5\ncxYVsG3DMdIz9QGPR7OK2hZ2F9X67Ms3JKBSqbj9yuM4UFzPP17ejM3mxOl0olKpOFDim8itHviU\nJAmShBBCDG7mFgvxSaGbLl5T1czXH5sA0HaxwOrsRQXMXlQQss+NRJ9vPIY+Vsv8yTndn+zluQ98\ni2/ONhqYPDoDUIbRjCPSmDzBf8ITAAAgAElEQVQqnR2HarDYHOg0aj767ojPe5z+ufP9ToIkIYQQ\nEa24qBatToPd7iBvuP90+7Y2W0iDpNef24DdNQ1dqxv4IZ+B4nQ6+e+newGIj9UydngKf35mHXWN\nbdzx0+PINyR2+l6LzTen6xfnT/E7Rx+nhCAtrTaefnen3/Fls4f15fZDIqggyWg0bgbc/WCHTCbT\nT8J3S0IIIYSiuqKJFa/4ThWfe8Ioz3R8AEtraHOS3AESgH6A1w4bSOa29rysTfsqsdjs1DYqC88+\nsWInf/3p3E7fO3NcJodKlYKRC6cE7oVKiFPyuv78zHc0u36Gf7tqLnExGtKT40LyDH3VbZBkNBrj\nAEwm05Kw340QQggBtJqtfPD6dtIy/PN9vvv6EN99fciz3dYW+sRtt4KxmWG7dqT73xf7PK9Xbitl\n5bZSz3Z8F1XGj1U08blrGv/135/GFNcwW0cJ8co1mr2C3LzMhD7dc6gF05M0DdAbjcZPXOf/0WQy\nrQ3vbQkhhIhmOzeXUF7cQHlx58tXuJlbrGG7j2juSVq9o6zTY5mpnff0/PnZdZ7X2i6yr/WxOp/t\n848f1YO76x/BBEktwD+BfwNjgQ+NRqPRZDIFDN3T0vRo+6GUuMEw8AvfDaRof36QNgBpA5A2gKHZ\nBsnJ8UGfa26xhq0NBlPbhvpep47JZPPe9sV8f3LWRFZ8e5Dq+lY0Wk3Az7PbfXORMjISO72vHK+c\npkd/fyLDs5N8yiz0VDh+VsEESXuB/SaTyQnsNRqN1UAucDTQybW1/nURQs1gSKKysjHsnxOpov35\nQdoApA1A2gCGbhuUl/pOB09MjqWpoS3gua1mS8jawNlhStVgadtw/B6UVvnWLTp+cg6zxmTyywe/\nobk5cJs/8c4On+3GRnOn96X3SopX2x1UVfW+MGhfnr+r4CqYtP0rgfsAjEZjHpAMlHb5DiGEEKKX\nmhrb2L6x2Gffj34+j8uvW+Czb5QrXyiUw22WNv/lSKKR0+mkpqGVJL3vkJh7PTWbw78iucPpZN3u\nCt/z1Z2HGWPyUzyvYyO0ankwPUnPAM8bjcaVgBO4srOhNiGEEKKvqsp8ewRGGzNRqVRovCpbLz17\nAoXjDTx17zchDZIcXl/+5/1wesiuO9g0tlix2BxMGpWOSqVi+hglIHUvFWKz+QdJm/dW+e3rKvhR\nq1XcevlszGFMvO+rboMkk8lkAS7th3sRQgghsHT40tS4lqfwXqYiLUOPRqNGF6Oh1WwJ2Wc7Hcpw\n25gJBnID1GSKFu6p/hkpcVy6bJxnv1qtQqtR0xZgAeCP1yvFIH/7/Wnc/5pStiHNtShwZ0blJofq\nlsNCikkKIYSIKNYOX8DFh5XV5NWa9qTexGTlyzc2ThvaniRXSlJfEoiHAvd0/8Q4nd+x9ORYqutb\n/fbXNrSRnhzL5NEZ3PCD6VQ3tBLbRcXywUCCJCGEEBHFavEdymlpVnqKAi0wGxunpbE+cEJ3b7h7\nkqI9SPp8k1LnqLbJv21TE2PZW2vmy83F5KbrMY5Qetzqmy0Mz1LqHE3yKvY5mEmQJIQQIqLYXD1J\nMbFaLG02Lrx8pt857iAmNk5HdUUzdrvDJ2ept9yz26I5RnJ4zfCbbczyO773qNKz96JrfTuAh359\nPDa7g5SErofXBhsJkoQQQkQU93DbWT+YSnaeb87K6d+bjM5rCCfeNfvK3GwhMTmOyrJGvvrAxLJz\nJwas1t0Zp9PJ+8u3o3EN6akiYQn6fnKkvJGS6mbmTVSWDzlYohTwnDw6PWCP0JhhKew/5lui4ZXP\nlDXecnrQ5oNB9K7cJ4QQIiJZLUqQFGhx2YIxmeSPTPNsZ2QpBQmPHa4F4KsPTFRVNLH2ywM9+sy6\n6haOHqzh8L5qIHqG2z7dcJS/PLeep1bsory2BYfDyZ0vbgRgdCdJ1b+6cKrfvjU7ywFYNmvgF6UN\nJQmShBBCRIyaqmZ2bi4B8Okx6kyGKwemY/K2M9DJXSgv9S07EC09Sa981r4+238+MlHsVUBymFdF\nbG+J8f7J3G6RsjBtqEiQJIQQImJsXde+mENMbPcZIe6yAPYAdXt6orrCt9pzNHQkOTpUF99dVMtt\nrnXXMlPimB7E4r6/u7i9llRG8tDKRwLJSRJCCBFB3D1Ci08d65nB1hW1K1m7rKTBb92wnmhp8q21\n5B7yG6rqmtr47SOrAJhWmEF2up5P1rcHqLdfeZyncGQgx03IYtuBasaPTOOZm07km60lTBmdEfb7\n7m8SJAkhhIgYllalkOSEaXlBne+e0Xb0YA07NhZDL3uA3GUG3NrMoau9FGksVrsnQAKIi9UyukOC\nfHw3vXjXnDvZZ/uE6fmhu8EIIkGSEEKIiGFusRCn16EOMifIe9p/yZG6Pn1ubJyWzOxEiovqaG2N\n3KUyemvFqkO8/e0h8jMTfPYvmprLpIJ07HYnK1Yd4qQhlnzdFxIkCSGEiAgOh4OmxjZSUuODfo9G\n2x5MJafG09TYu8KS5mYL+oQYzxDfUOxJevvbQwA+ydm/uWgqkwqUaf7zJ+cwf3LOgNxbpJIgSQgh\nRESoqWzGZnVgyE0K+j36zooX9mB6m6XNRqvZRrohkVhXkDQUe5I6uufn88lMCT4gjUYSJAkhhIgI\nZcVKEcOc/JSg3xMbp+Wiy2ez/IUNOBwOqsqbun+Ti9PppORIHSteURZj1SfoSE5VprDHB5E0Plg4\nnU5WrDoMKOuu/f6SGWSlxkdNLai+kCBJCCFERHAHOFl5wfckARiylXo+DXXti652nN4eyM7NJXz7\nSXudoHh9DFNm5dPSZGHSjOASxweD7QdreGelMtSWmRJPdtrQqoodThIkCSGEiAju5UhiA6w83xV3\nGYAjB2s8++zW7qfwr/3qoM92WqYerVbDwqVjevT5kazJbOXB5UpP2dTCDK46a+IA39HgIsUkhRBC\nRASHXen9CXZmm1ug821BFJccWei7Ltn4qbk9+tzBYMu+KgDyMxP4zUXTuqyWLfxJkCSEECIiOBxK\nYONeZDZYmgBFD4MpBuk9Ihcbpw14ncGuplEZgvzBSUOnd6w/Db3fCCGEEB5rd5Xx9/9swNzW/Wyt\nNoudzzYcxerVC1NU1khFnTmct+jhcPSuJ8kdXHkzt/gWh3Qnabs/49C+Kg7sqQSUHKgLLpvZm1uO\neJv2Ks+Ymjj0lgzpD5KTJIQQQ9hTK3YBsHV/FfMmdV0D5+n3drFpbyVtVjtnzi/A4XBy+/PrAbjy\njAks6mI4av+xet785gC/OH9Kr4d02ofbevb3e2KARVXjE2J8tjeuLmL9t4c54bRx6BNj2LO11HPs\n/B/N7HFgNhhs2V/FEVcyfJ4hoZuzRSASJAkhRBQIZrbXZlevQ7NZ6XWqa2ovzPjsB7tZOCWn02nj\nd720ESewclspp80d0eP7s1rtHDtcC4C6F8Nt2XnJlJcoJQT0iTHU15ix2x2eITT3sVWf7ffJV5q1\nYOSQDJBACYwBls0ahlqm+/eKDLcJIcQQ5fQKjD5Ye6T7813/1ccpfz9/s7XE5/idL23s9r29jTfe\nddUqAnpVv8cdBAFkZificDh98pLcvU0dE7rHTsrq8WcNFuU1LQCcv3j0AN/J4CVBkhBCDFGNLe1L\na5RUNbPvWOdrmzV5LcNRVNaIw6sAoduB4gYaOuT6QHsuEYDd0YNS1168g5zemDFvOAALTiokxrU4\nq90rIHLYA892i+lmIdfBqrHFwr5j9QwzJHa7WK3onARJQggxRH228ajP9quf76e0upmXP92L1eY7\n+6vSKzl7495K7v7vJs/2iTPzPXlGv3loJUfKGymvbaHV4j8sZ+0kGAm3eUsKueamE5h23HC0riE2\nu9e92Du5r7ghOiX+vle3YHc4mT85e6BvZVCT8FIIIYao7V7FFUHpXXhw+VYq61pxAj88eRymI7Vk\npelZu7Pc59z9x+oBOGtBARcsHs3kgnQefnM7AH95Tknmzjck8NefzqWmoT1IsvUiSHIGkS8VDPcw\nnUarBEnuobVvP9nLvp0VAd8zFKf9A1TVK1P/ZxmH7nBif5AgSQghhqDtB6spKmtkmCGB234yh6vv\n+crzxQnw+cZjxMdqeW/14S6vM35EKgDTxmb6HSuubGbz3kqf3iObrecBTzA1jXrCHSTZbQ4cDgc7\nNrXnVukTY2hpUoYMh2rCNsCI7ET2HKkjM8V/5p8I3tAMoYUQIsrtds0Uu2TpWDRqNUl6/2Gl7gIk\nwJPPolapePg3xzNznMHn+MNvbueJd3Z6tnsz3NboFbwtWtb3ooeeIMnuoNXsWx/q0v+by4RpSikD\nfWKM33uHCpvDiUqFzGrrIwmShBBiCGo0K70lGa6ehN9fPKPH11ABuRnti6EmxOn45QVTeOjXx7Nk\neuAFYI+WN3Z73YY6M689s96TrP35u7uV6yfGMGX2sB7fZ0eenCSbg1avhPSZC0ag02kYOzGLYQVp\nnPX9qX3+rEhltzs87SB6L6gWNBqNWUaj8ajRaBwf7hsSQgjRd+5aRwmuxORhWYmdnnu1a9HTiQVp\nLHMFKSOyEnnqxiXExfhnZSTG6yjITfbbr9OqOVrZ7DPbLZAvPzBRXdnM2i8PsG9XOdWVzYDvMiF9\n4Z2T1Oqa4TdrwUjmuqbC549M4+yLp5GWOXQLLNrtTjRDeDixv3Sbk2Q0GnXAk0D/1KUXQgjRZy2t\nVlTQ7fTv7y0pZP7kHHIy9ORm6ImL0XLpsnE4nc4u6xUtmpJLk9nK298exGZ3MmNsJvo4Lau2l/Ha\nl/u5eOnYTt9b5aoCnZgSx2crdnv2nxminh2NV0+SuwxAbHx0peDaHRIkhUIwPUn/BJ4ASro7UQgh\nRGRobrOhj9MGzEn5449mAaBRqzhj3kgARuUm+/QadVfQUe16b6xOA0BKYiwjspIwALXri3npsTU0\nN7axZ1upbx0luwOLax05dwK1W2a20tu1anspD7+xrVcz5dz3BlB6tJ5mV3mC+CE61T8Qq81BQ4tF\nhttCoMvQ2mg0XgFUmkymj41G483BXDAtTY9WqwnFvXXJYEgK+2dEsmh/fpA2AGkDkDaAwG1gbrOT\nlBDjcywjJY7q+lbmTsvn3Rl9z/2B9l6b+DgdFywdy/7PDwDQ2NDGWy9uprGhFa1Gw/wlhQCeoAXw\nLEMCkJQS57nXZ97/AoCqJitTxvjPqgvE+zlLjipFM7dtOObZl52bMuR/V9zPd90/v/QUEh3qz+wt\nHM/aXf/jlYDTaDQuA6YD/zEajeeYTKayzt5QW9sSyvsLyGBIorKy++TAoSranx+kDUDaAKQNoPM2\naGqxkJeZ4HPsjiuPw2pzUF3dFLobcCUSmc0W3viP77IljQ3KrLVjR2qprGzEbnfwylPrAl7m9Asn\nU1nZSG1jexD19+e+46FfH99tr1bHNgi04G2bxTqkf1fcbWCzOzhcqiTE56Trh/Qze+vLvwVdBVdd\nBkkmk2mx+7XRaPwKuKarAEkIIcTAe3/NYSw2Bwlxvv/Ex8dqiY8N7Wcl6mNoaLESo9NwbE9VwHPc\neUENtWaf6f5up54/iQxXYvlNT6zx7G9utVFRZ8aQEt+jmkZTZuWzdd1RxkzMYv8upYikThf+EY6B\nVF1v5p6XN7HniNKLVpCTxG8umjbAdzX4yYClEEJEsMNlDfzl2XVsOxA4AOnoy03HeOPrgwAk6cNf\nB+gX501mzvgszpw/ksRkJQKrwHeamrvydXOT/7pv0L5+2pZ9VX55SC99sper7vmStTvLeOKdHew4\nWN3tPak1SkDl9MqFSk6LD/KJBqcHX93sCZDUKhWnHDec5IShWweqvwQdJJlMpiUmk2lPOG9GCCGE\nrzue38CRiiYefWtHt+e2Wey8+Mlez/a5x48K560BkJeZwM/Pm0ySPganUwl4juKkFCe7UQKeg6ZK\n/vvEWjavPeJ53/ipOZ7XMbFKL89Db2zz7Dt97ggAdh5SllZ56t1drNtdwf2vbaWmwb83ypu716mh\nTjmvcLxhUCw/0tBioarOzF0vbeRgDxb8bTJb2bK3EoAz54/k6RuXMG9iTjfvEsGIrjmRQggxiHj3\nqlht3c/08q52/fuLp5Odpu/i7NBzOJyoNSocwLEOvUkNda2eoOWcS6ZRX2tmzzYleyMmQJmCuC5K\nFxwqbSA9QN6Rm1qtBESVZUqOSkYXNaIixQdri3j9qwOe7Zc/28ufLpvd6fkOp5OvNhezZX8Veldb\nXbB4NGctKAj3rUYVCZKEECJCHS71TUS1dVNF2TuQGj8yLWz31Rmnw+mXO+TAiRrffe9uKWZadnsx\nypgY/3yh2C5yiI5WNHW5cKt7uM3NXVogknkHSACG1K6HB1esPMSKVYd99g0zRP5zDjaR3/8ohBBR\n6r+f7vXZvu/VLV2eb7UpC8XOn5TT7YywcHA4/AtQ+hXRVsG63RW8vuqgZ5fO1RMSH9seGBXktM84\nmliQ5hMAdAwOOuoYqBkiLEiqaWjl0be2e4YN7Q4HMa4q4cdNUIK/rmpEHS5rCNgGwwdBj9lgIz1J\nQggRgRxOJ0Ud1kEzHa3rshK2uyfJO9joT05noJ4k8L4bh0oFTmiyOnD/na51BQj6WB3mNiXQ8/7C\nj4/VYhyeyrHKJtd5XX91ed+DVqtGnxjiKX199PbKQ2w0VbLRVMmfr5iNChUWm4PF0/L48anjWLe7\nwlPnKJCvNiu1nS88YTSTR2Xw2YajnDhnhGedPhE60pMkhBAR6KvNxZ7Xv7t4uuf1v15XKlH/7T8b\nuP259TS1tM8Yc+ck6bQD80+707Xy/LTCDM++jv0hrQ5lj81rn0qlwuFwUu3qWcnLTPAZbtt5qIYz\nFxRw/feVKe1drUPnvp7ONYQXp4+8StupXkHbHc9v4NG3tgMwdlgKGrWaZL2OfUfraGjxnw1YXd/K\nN1uVIGnB5FxG5iTx07MmMndybv/cfJSRIEkIISKQOx/prAUFTCxIZ6or8Nh2oJo7nl/PwZIGisob\nOVBcDyjDM/f/byugLG46EByunKRfXzSNMfkpyr4O5xxwDcB1vEN3L1FKQgy3XznHpzdoyugM1CoV\nU0ZnEBejoa6pDUc3q+Emu3pV4iJwORJth5ypKlftKPfPeOzwVJzAZxuO+r3XdLS9SnlyQuQ921Aj\nQZIQQkSgOtfyHWe61lYrzGtPdD5W2ex5vXpbCa9+vo+DJQ00mZUhmupupsiHi93uQOUKbn5z0VRu\nuWyWT5C0BwetKDlGi6bksg8H5Cfx6Jvb+ctz6wE4cUY+GrXvV9PPzpnoeT1ldAYVtWa2Hei6XpI+\nsWc1gj78rojlX+3v0Xt6q81q99s3IivRU9fqvONHA1BRq6wrb7U5eG/1YbYdqKbZrPTBzRib6ddO\nIvQkJ0kIISJQXVMb8bFaYl3DRqfPG8lb3x7yO++D1YcBfBay7aaTJSxMO8qwtNmxtClLU+njdBTm\npeBwzWwz48SdYaWP1fKjU8ZxzfZS1rt6wtySvYKbK04fj0at8gkGZo4zsH5PBW98fYDpXazr5i4r\nYLX4ByTeKmpbeOztHRwpV3qyzl5Q4LPQbzhYLEro+JuLpvHtthIOFNfzq+9N9RxPdbXBut0VTCss\no6i8kU/W+/Yqne4KnkV4SZAkhBARqLaxzfNlCaDVqJllNLDRpBQN/PEp43wKR360rr1QY3dDUeHw\n3df+ARyAQwU48SkCEKPTdJo3ddz4bM/rxdPy/I5bXDP4ir160wJx5yRZ2mxdnveHJ9f6bLe02sIe\nJLValXvKSY/n2vOn+B1PiGsfRnv6vV0Br5GT3r81sKKV9NUJIUQEqaoz8/yHu2lutfkk+ILvMiOj\nvIbfOurvGMlqsdHsWphW0yH4cbg2vWe4zTZmBZyhd/Ls4ejjug5Q5ozvvD6St5Gu/J4xEzo//0i5\n/4KogZKl++Kj745wzX1feXKuQKmMDnQZjOVm+AZB+ZkJPtuJEZhrNRRJkCSEEBHkrv9u4putpQBk\nd1hvbIRXvZ/sNL3fF6fb6C4CqHBoa1V6RnKHp3DZtfN9D7qCIfeXzYkz85k+1neYLEar5lcXTuUH\nS8d0+1lxMVpSXD1sNz6+mqff3YkzQFQ42mjgwstnMv+kwk6vtfxL/xyko+VNAc7sOYfDyW3PruO1\nL/djsTr48zPrKK9poaSqmd1FSvJ1bIAimm6aDqUUFk/PY7YrQMzootq4CC0ZbhNCiAjhcDipdfXI\nAJwwPd/n+LTCTMAEKF+weZkJFFf5Djv9/LzJzBjbea5OOLS5hrTSDQn+s8nUynibO0j60cnjPIdu\n+fEsVCpVj4M6fayW+iYLVfWtVNW30mwOXFMoK7fr647KS2bn4VqffYfKGjl+Wo9uJ6DN+yo5WuEb\ncD2xYidFrqVSVCo8BSQDufrsSdz27DrPdl5mAifPHo7pSC2pSZFV92kok54kIYSIEJ+6pnwnxGl5\n9g8nMdKr6jRAmteXo1qlIqtDT5NGrWLO+Kwuly4JB4urAGRsoCKPrh4RFSpyM/Q+w2yF+Sm96vWq\na/IdEvMOLIO192gda3eWA3Dr5bN58ndLAKU+lbtyeV98t0u5dm6Gnr/+9DgAT4AEEKPVdFkVfXhW\nok++Upyr18k4Iq3f1+SLZtKTJIQQEeKw60v0xJnDOj0nIU5Lm1WZHZXWoUehYw5Tf9m4uggIPJPM\nu97R366aG5LPM3dIxq5vaiMuOfhn/3T9UV75fJ9nOyUhxieRvKzG3KclPmoaWtngSrD/61VzUatU\nZKfrKa9p8Zzj9F+wxc8so8HzOlnfs5IGIjSkJ0kIISJAQ7PF0/uwdGZ+p+fd/8uFPHr98QAcNyGb\nhVPzuOjEQuJjNVx55oR+udeOjh6sAaC8pMHvmFWnfM1YkmJCtp7cRUsKGWZI5PzFSj2hmx9b1eVa\nZx15B0gACa4hwstPMwLwsddMwd54cPlWz2t3aYbfXzzdJ6gNNrne/f6OAbHoH9KTJIQQEWD9ngrP\n66Queg102vZk38R4HX+4fA6VlY2cPnfg6uZkZiVSVdHE4lPH+R1Lykxge30rGbGh+5v89HkjOX3e\nSIqrmnnrG2Wh3PomS1Brl9kd7cHU9DGZtLTZPLlBC6fk8tmGY6zeUcaly8Z1O9MuEIfD6VPs0y09\nOY77rl3I42/vYP2eCpKCXC7ln9cuoMls7fchVKGQVhdCiDCrrDOzYtWhLns73BW2b7p0ht8isZFO\nG6NGpYKMLP/ZdoaUeFqBirrQVwHPz0xgyQyl163V0nU9JFByl6pc9zHbaOBX35vKH34409PDpdWo\nGTtMWU6ltqnneU6g/Kzd/vjjWX7HK1zHs1Lj/Y4FkpoYyzBD74f+RN9IT5IQQoRRq8XGTU+sAWBM\nfgoTC9L5aksxxZXN/NBrpldNg/KlnJwwuHJPnE4ntVUtJKfFow6wTMb4kal8vukY8yZmB3h338W7\nEprN3VTWttkd3PDoKs92Z+3s7qmz2YIfvvPmTiI/Y95Iz/p13iYWpFFU1si8STm9ur7oXxIkCSFE\nmDgcTm79d/s07jU7y/jnq1s822cvLPAk5BZXNhGjU5M9gJWU92wrJTZOy6hxhi7Pa2m28NGbO1i0\nbAyJSbG0tdrIG54a8NyZ4wzceMkMxgzzDxhCwT3rq9Vio81ix3S0limjM/zynxqafWfEjevkfmNc\nOVTWXgZJ7orgnQ3VnX/8aGaMMYStPURoyXCbEP3I3GYbkCUjxMB49fN9PovNrtpe5nP8by9s4J+v\nbuaZ93ZhtthIiNP5rMHW3778wMRHb+7E4eg6QNi0uojy4gbeeXkLtdXKjK20zMDBnUqlYvzItLDl\n1LirVre22Xn9qwM8uHwbn2045neee7FYt+MmBO7Z0mncQZJvz1R5TUtQgZPNrvz/re1kyFSrUUuA\nNIhIT5IQ/eRwWQN3PL8BgGduOjFkM31EZHI4nXy5ubjLc9zFEN3yOqmg3d/Kihv8eoZqq1twOBzE\nxmrZvlF5LpvVwYpXlJlcCQNUfsDdk/TY2zs80/hf+XwfJ88Z7nPezsM1nte/uWgqnXFfw+qVP3ao\ntIG/vrCBzJQ4fnnBFDRqFfkB8oQ27Kngmfd3A6DtolCkGDwkSBKin3j/dXuwtIHCPPlrcqhZu7MM\nVDBvYg71TRbsDicjshI5bd4InlqhLFS6eFoeRysaOVTqv25YYi9mU4VD6ZE6Du+twpCb5Fn77NWn\nlWHDsRMDr4UWGz8w9x7vVcDSu6fH6XT6/CHS7Fo65a9Xze10ORdoD268r+WunF1V38pfnlsPwNM3\nLkHjlYNVXtvCY2/vaL+OzEYbEiLj/0ghhjin08kGU/sU7y37qiRIGmJaWm089a4SCE0rzGTnIaXn\nYqbRQIzXtP2ahlY6G80q6GYZjf6y7tvDntefrdjtc2zfrgoC0XWxDlk4xXXyuXaHE61GxfaD1djt\nTixWV1Xwbnp43D1JFq8gqabBf2be0YomCnLaf15fbvLtNdRqpKd4KJBQV4gwczidvLvqMBarw7NA\n6ftrigIuyikGr7e/Peh5fbSiiZXbSgCYPymHQq+lN8YOS2F0vrJ97qJRPkM//b0wbV9Mme1b8DKr\nwxIq/cWdk9TRYVdP3QOvbeWhN7ZxrFLpDYrpJpiLCdCT5J556O2O5zfQ3Nq+Ztwn64/6HB/I3DIR\nOtKTJESYWG12nvtwDzsO1tDkWoBzRFYSR1yrjJfVtJCbERk5KKJ3HE4n9U0WPlxbxGcb24dTi6ua\n2XusnrHDUjC46uE8fsMJVNSayUnX43A6MQ5PZcZYg89yGDkDOLOtp0H7xOl5zD+xEJVKhd3mGLCe\nJF0nPUN3vrSRX32vPQB1/3/X1aKyyvWU5/AJkhqVnqQfnDSG7DQ9D72xDYA1O8o4aeYwPt/knyhe\n32E2nRicJEgSIkweeXMH2w9W++zLTm8vIHfL09/xwHWLSBlkdXFEu3e+PcS7qw/77X/xYxMAI7Pb\ne1didRqf9cC8Z1flG34rlxAAACAASURBVBIormwmPbn7itHh4nD4B0mTZuSxc3MJ808sZMrsfNZ8\ncYCqiiay85JJ81qsVj1AARJAVlo8CXFapozOYK1rWRe3h17f5rM9eVQ6sbqu79U9u63alVDfZrVz\nqLSBjOQ4Tj1uBABnLyjg3dWHefmzfbz8WfsSJ+csLGC2MYvlXx1gwWSpgzQUSJAkRBis31PhFyAB\nJMT5LkWwdX8Vi6fl9ddtiT5qs9iJdQUETqczYIDkzXuB0q7c/MNZNJktJMYHt1RFODhdQZIhJ4nU\njHicDicLl41h6pxhpLp6uBadPHbA7q8z8bFaXvnbGVRWNnLF6eO55r6vOz336rMndjur1N0z9dG6\nI+Rm6GkyWzG32TnJa9Hh3ADlDrLT9Zx3vLKW3PXfn9abRxERqNucJKPRqDEajc8ajcZVRqPxG6PR\nWNgfNybEYPa41yyX/MwEMl1rSiUnxHDGvPY1tgL99S4i0+Z9lfziga89Cdl7j9b5nZOeHMsdVx4H\nQG6GHuOItKCurY/TkpU2cENt0D7cFp+gY9nZEzn53EloNGpPgBTJVCoVKpWKmE56iVITY9Bq1EEF\nod7nLP/qAMu/OgD49grONmYxb5JvnaXLTjX25tZFhAumJ+lsAJPJtNBoNC4B7gfODedNCTHYxWjV\nWGwOjp+ay0/OmEBzq5Vt+6uZMTaTmeMMFJU1sPNwLY0tFlZtL2WW0dBpAqrons1mZ/OaI0yYlkti\nmIasXvpkL06n0sMwaVQ676w8BMA1507iiXd2AnDqnBEMy0rklstmkT3AQU9PuWfcDfb6XTnpespq\nWjzbsTEa/nntQnAG92zeQ+LuXEKAaWMyPa+1GjXnLhrF2p3K8N5lpxmZMDK4gFgMLt3+q2wymd42\nGo3vuTZHAuVdnS+EwPMX7WWnKX9dJsTpmO+Vo3DZaeO56Yk1vPWt8kX73a5yfvuD6f1/o4NQVXkT\ny5/bwOSZeZzzg+nU15rZt6ucDauK2Lm5hLknjGbCtNyQfuaB4nrPmlw7D9Xw3urD7C9uAJRehWWz\n6mlutXoKGA7G8g7unqTBPivr1xdNZeehGk6ckU9DixWNWqU8U5CPFRej5Z5r5nOja709UJYw6Zgg\nbkhpD6YyBjCXTIRXUH+6mkwmm9FofAE4H/heeG9JiP5R39RGXIzWk2MSKlabnSazlQkj03yKzXkz\ndFgBfMehmoDnCX/Ln1Oqlu/YVIKlzc7ene1/t5lbrHz1oYlhBWkkpYTui2v9Ht/aQG9+o0z3v3TZ\nWNRqFZd6LVQ7WLmDJNUgLwyTnab39OL1dlJEZmo8d/5sHn98ai1AwCRstVrFoim5rNxeyogs/+rb\nYmgIun/fZDJdbjQabwK+MxqNE00mU3Og89LS9Gi14Z/pYDAMTE2OSBHtzw99a4MPVx/isTe2sWTW\nMG64dFYI7woOFtcDYEjX9+geyxramFKY2f2JXqLt96CxQ1E/7wDJW0pKPBkBlo3ojY/XFnlq4IzK\nS+ZQSYPn2KxJuRHxMwjFPTS52jYuLiYinqmnQn3P3tcbW5Ae8Pq/u2wO17ZaSdRHxgzVwfhzC6Vw\nPH+3QZLRaPwxMMxkMt0FtAAOwN7Z+bW1LZ0dChmDIYnKSv+S/tEi2p8f+tYGbRY7j7nqnGzaXR7y\ntnzhPSU/JT0xpstre+eyAPzlqTU88bslQX9OtPwerF95mJ2bijnlvEl+QVJn6upacBCapPhHlm/x\nvL7lR7OorDNz81NrSUuKJSlGPeA/g1D9HtS58ngsFtuAP1NPhev/hbkTs9mwp4KUWE2X1zc3+xeb\n7G/R8u9BZ/ry/F0FV8H0JL0JPGc0Gr8BdMBvTCZTcP9SCRGBisrb/0dqaLFSXNXc5VpOwXI6nfzz\n1S3sLqoF4OTZw7s8f9qYTCaNSvfMluqsKF6027W5BHOLlXdebg9W5p04mvoaMzhh97ZSAGJiNVja\nOv37rVfaLO3XO33uCNRqFdnpeh7+zfGoUA2q9bnKiuuxWuwMH5Ue8Pjar5QhxBYpguhx9VkTueK0\n8SEfkheDRzCJ283A9/vhXoQIu8o6M3f/d5Pfvt4ESe7gpqymhTH5KTS1Wj0B0k/PnOCz8GYgsToN\nN/xgOlfe/QXQvgCnaOd0Omn1mmHklj8ilRlzR2AwJFF0uJqmhlbWfHGAkqPKUGeoSiu419vLzdBz\n0YljPPs71ruKZKYdZXzx3h7P9s//sMTneEuzhZef/A6rKyCcvXAkQqFWqyRAinIy51hEDZvdwddb\nSjzbkwrS2Hm4lode30ZOup4LFo9m9vjAK5x3tGp7Kc+8vzvgsZ+cPp6FU3o3u8pmdwyq3olwa25s\n8wt40jL1ZHktBKtPiEGfEMPJ503ihYdXA10HSVarHa1WHdR0cHdB0F9eMKU3tz+gqsobeeOFTX5t\nYWmzodVpUKuV51/12X5PgASQL1PZhfCQf41F1PjfF/v5YG2RZ3vMsFTP67KaFh7zKgDZnc4CJICp\nhRk9uq8fes2Mci/CKRS11UqezKwFIznnkmmkpMVz0pnjA56rT4jxTP13dhIkHTtcy7/v+7bTlewB\nymtaKCpr5FBpA+t2V6CP1ZI9CAoqdrRpzZGAweKaLw/w5D1fs/brg9jtDvbv7rwthIh20pMkosbn\nG30XoTQOT/U7J9ienIQ4bcDhscyUOFISY3t0X0tnDSM1MZZH39rOHc9v4NHrF3c7VBctivYrPTmZ\n2Ynkj0zj0v+b2+X57kVWOwYHTQ2tHDtcy5cfKGuqbV57hHEdKiYDVNS2cLNr2nduhhIY/WDpmEFX\nO2jz2iMc2FPps+/cS6fzzstb2LVFyeHavOYIm9cc8TknNWPwBYNChJP8SyyiQrFXD012up7vn1gY\nsHegvLbz/CSn00ljixWVSskfKsxLpiA3mZljM7n3VSWpePLonvUiuc0c1z71f9fhGmYZlWG/VdtL\nKSpv5OKlYwfdF3VfOBxONq89wvaNxSQkxjByTHDt6h5C6rii/fqVh9mzrcyznW7w/xm3We384cm1\nnu1SVy/Wol4OnQ4kdxI2QFy8lgsvn9Vl3agFSwtJSY0nOz+503OEiEYSJImocOsz6wAYk5/CTT+c\ngUat/n/2zju8jfr+4y9tWbJsyXtvx3bi7E12AmRACaPs0Zb+oFBaSgeUQlkFWkZpoVA2tKyyVwiQ\nkE32dAaO4xXvvS1Z1rz7/XGybFl27IRs9HoeP4/u7nun78nS3fs+E0H0d0U8/cFenvzljAGPsS2/\ngVeWH/RaGCZkRbJ4ajLN7d3eMaMHyRwaCplMxvULs3hrZSHvrCpiwohIuu1ur1tv9a5qXr97/jEd\n+0xBFEXsNheiKNLcYGHHt1I1cmO4DsUw47R64oz6W5K6LL4ZW1aLfwZXY1u33zqdRnnGtenoKxAX\nXjKKtAGa7I4cF+u1KM06L5PcifEnbX4BApxJBERSgB8EapUch1Pgohkp3irYA1lmWjrtiKLovTH+\nb1URnVYHe0uacTil5lY9FobJniBvdZ/sl5yUYw961aikebVbHNQ0d9Ft93Xn2Ryus7q/22fv5FFf\nLRVqnLu4t1lot9U/u20weixJe7ZUEGIKYvq8dJobLFQdljIRr71lKp+8tYcus39dmwZPnaCLZqRw\nuK6TaJOOH52TMuz3bqzrRKVWYjrFLquyomZAKonQXyCdMz+dlqYuZi8cgSlCT0x8iE8QfIAApwMu\nwcUzeS9jdVr5/cTb0KmCht7pBHH2XnEDBOhDUpSBw7WdjOpn6blkVqq3f1oPOwoamZITRV5xM6v7\nxTH1xeiJPdL06Tz+fURMRJ9eUFaby8dFCNBhcaANO3t/sj0CCWD914Xe13MW+rb8EASR8nozqbH+\nBeBkHpFUUSqJohBjEHnbeuNuQoxBGEK0NDdacLsFHwtVg6cQbkpMCBfPSjuquRflN7DmC8nqd/Mf\nZqM4hTWvaivbAZg62/8cxk7prd01ZlLCSZtTgABHQ6utjcMd5QBUmqvJDss8ZXMJZLcF+EHQbXcR\npFH4uU4WT/OvCfPSsny+2lbBc58c8NuW2KdHU0+At0al4Ip5Gfz8gpzvNccRiUbGZ0qxSVabi7e+\nKfKuBylm5ofGRVePJSYhlPte286Nj63ly63lbNxfyyNv7mL51gq/8dogXxG5eXWJ17V24ZVjACkI\nXHCL7NpU7jO2skESpXERR2cJaqzr9AokgI4B3HYnk5ZG6TxG5PoHpgcIcCbgEnqvdckhp1bMn72P\npQEC9MFqdw2YMaZUyEmOMVBR71vO/uMNh/3GPvizySREBfPZxjIS+gX+LpqadFzmOTIljLziZr7d\n11vPKSXGQFFVOy738SmQeLqiUisINQbhcLjobJeK+uv0akRRpKZJahX58YbDhHialn767WGiwvVM\nzYqkzWzHZNBgCh846H70xHhvpWm9QbIA7tlaydQ5vdaWNosdGf7Nh4eifwq9IAhHtf/xxmK2ow9W\now5kSAY4Q3EKkot9QeJsgpSnztUGAUtSgB8I3YOIJIArPZWUf3/lOJ64dTphIf4p/NeeN4KkaANy\nmYxLZ6cxJefEPKX3uO4snirTBp0KtWed03V2W5IEt4BcIfMKJJAEzUcbSn3GdfZpm/HSpwcoqGjj\n9//ezI2PreWrPQO7R2MTQ72vx06WXE5Kle/lz+UShl1ksi/NHgtUj/garJBlwb46qjxV2k8kgiAi\nDxQkDXAG4xSkeEyl/NQL/cAvKcBZjd3ppqbJgs3hRq8d+AeXnWzi9bvnMyo1jIjQIDLie2+oz9w+\nk9fvns+CiSfH5Kv1BIGX1EjtNX66KBuVQrppt3b2BhvXNFl44JWtdJxFfbbcbt+b+4TpSag1Sr72\nxBQNVpph9a4q7+ttRb21gWb1iWVKyewtsaBSK9AbNLicAvt29O7rcovHVO28rdlKiFHrrbsk9LP4\n1VV38L+XtrP+60KWv78fu234gejHgiiI3gD2AAHOROq7GgBQBURSgAAnDrcg8PAbu7zp/1NHDs/6\nE9fnZmzQqU/I3IaLQadmh8ed88ryg3R5brAvLctnz6FGPt/o7xY8E+mxvsjlMhZflkt8spEJ05N9\nrGe3XTqae66f6F0+1xN4nFfc7HMsR0ool/7fJP6x8hA7Ecg8N90nQLvb7qLRLFmrtqwtxeJ57Xa7\nUR3FFVEURdpbrTidbtRqpVeY9LckffZ2nk+cUnV5+/DfxENJQaPXYjUUgiB6A9gDBDjTyG8p5N3C\nT4DTw5J06mcQIMAJoqapi9rmLu/ytJExw9qvJ+blVOB0+8azGPQqVH0ype59eRt/vXkaZo87zuk6\ntfEvxwvBc94KhYyUzAiv5afJU4Nq+qhoYsJ0CKLI0pmp5KaFeeOU+mMyBnGgvM273BOQXV7fyReb\ny8lNDcMO9Ejhkop2xuXGENXuQC2IPiUgfOYoCOzeUokpXEdUrAFzh41l7+4DJNedXCHzjgOw21zs\n3lLudxyH/egaGe/YWMbuzVKQev/mtAMhBCxJAc5Qqsy1PL/vNQDUCjUTo8ee4hkFRFKAs5imPrEt\nwLC7eatOYTzHpKwoNh+o46DnJh+iU3Prxbn88cWtAHRanTzy5m6snpYoKtXZ0aG8zuNeLCxrZXKb\nlUhjEPllrd4YrZ5WL3KZjKUzUwFIjQmhs9vFJ+tLALj72gk89s4enG6Bmj7ieNOBOupbrV4XZl5x\nMwogDElIrFtegC5YjdpjARpMJO3ZUumTETe6TwFGh8PtFSZuj7tt1ef5VJVJ/0eVWsG8JVl889lB\n1n9dSJfZzripiSiH+P+1tXR5BdJwEUXxB1WdPcDZgSiKfFL8BQCJwXH8fuJtqBSqUzyrgEgKcBZz\nqKLXmjBtgD5dg5GZEEqQRsGSAcoDnGhUSjl3XD6Wm59cD0gxSkEaJfPGx7MurwaQmvH2sD6vhvgI\n/UmLmToROJ1ulr+3HwAdMv7UpzVID8YBrHtyuYwbluQgEwXGZkSg8wTmu90iFfWdPmN7BFIPbmDM\n9CT2b61Ei4w1nvcHKaZI3k8n221OdvYrGXBgd433dWtTF3LPTj3utoZaaQ4yGcy/INtHEO3cVM7O\nTeXcfOfsQauJtzZ18f5rO33W2bqdaIOOfOMIuNsCnAkIokCtpR69SkeoJoSn97xIaUc5ySGJ3DXp\n16d6el4CIinAWYnV5mTNnmoMOhWP3jSN4CFuLH2JMul47o7Zp6wdhVIh54LpyRiDNd45XL8wyyuS\n+vPOqqIzWiRZOnstfhYGzgxL6FOfqi8KhZwLpqcAvVlv1U0Wqpu6GJcRQVJ0MMs2lwPwl59P4eP1\npXTbXdx6cS51ZW0DHnOg7LT21qFrH/W421oaLSSkmHDY3SSmmlhy+RjkctmAx13+/n6yx8SQkhGO\nRuv7Hd20utj7OjYxlLqqDorzGxg9RBHIgLstwOmKIApsqtnGqPAc7t/6NwBUchW/HHsjpR3lyGVy\nfj7qulM8S18CIinAWYfZ6uDfnkKQ4zIijkog9XCq+3VdNid9yDFGg4Z2T3uN5z/7juKqdp66bcYZ\ncYN02F188tYeYuJDGTU+zrv+0CAiaWTK0D3xejLTqj2xSiNTTJw7KZEN+2rRqBQkRAbzm8t7Yxw6\n9AN/L9xu/zivbo8A0+pU2Pq0SdEGqbB1O1l6zThvrNHOjeXe1iQ6vdr7/5DLZVx36zTefqHXUlZb\n2e6tkN0/3qivKzVnbCx1VR3DimcSA5akAKeQNZXf8knJckaGZ3HrmJ8hl8mpMtdi0oRyoPkg7xd9\nBnzmHe8UnDyT9xIA02ImEh507K2dTgQBkRTgrOOOf23y3mrnTzhzLSz9UchluAWREL2azi4HM8fE\n0dLezdb8enYdkjLgHC73adHfTRRFXll+kKKqdu6+ZgJhoVo+WFtCVqIRV4OFXZ44m7ZmKzqj1J3e\nbdTy+FVjKapuZ/Wuan5/1Ti25TcwJSdqWO+pVPgKg4wEqZTDE7ecw0CaN85Tybw/A1l8nJ5q55Nn\nppA7Id4nbkkQBORyuU9j2bXLDwEQavIthGcI1fKLu+Zgtdh563lft2JnezdOh5twj9WsxzJ1xY2T\nvMLtwO4aJs5IGXDeIH3uosgZIZQDnH3UWur5pGQ5AAdbCjnYUkiDtcm7rj9LUs7lq/LV3uWFKQtO\nyjyPhlN/NQ0Q4DjicgtegTQ+M4LkGP/+Xmcqj9w0FadTIC5Sz57CJs6dnsKy9SVsza/3jhmskOHJ\noKyoidAwHWERejYfqGdbvlTr5K4XtzIuI4K9Jc1s2VlFTr/KI9/tkdyIkaYgIozS3zm5sQBH5UZU\nKeXIZCCKYDJoSIkJ8a4fCKVKwfjpSeRtrfQsy3E5BZ86R63NXaxZVkCzp9VHT1xRX0tjTyySTCZj\n3pIs1n1ViMuTdTiQa0wulxEcouX6X05jxSf5NHmqvb/78g4EQeSG26ajN2g4XCiVNjCG63B5RFq3\n1UljXSdRsSGYO2wcLmpi/iKpHY4oiuzZUuF9jwABTgTfVm9ldeUGbhp9PYmGeJ9tHxUv81l+Yf9/\nBjxGemgKi1PPJSdsBF0uK/nNh7h7yh0EKbUnbN7HSqBOUoCzio3767yvh1sX6Uwh2qQjISoYuUzG\npOwoVEoFBp2vy8h1kkWS0+lm384qtq0/zIpP8nn/VSnQeHtBg8+4vSXSDX8gyWo3S66s5Ljv141e\nJpMxZ1w8Oo2SxcNsEzNhmjROpVaQkS1ZrJa9u5cv3pNS+/dur/IKJADVEIWUdMG9AeZKlfyIrUGC\nQ7T8+KcTiUuSLFo9Are+pgNbd69LT6GQo9Gq0HuO/fEbexBFkQ//s4sta0pZ/oE016Z6Mzs2lgO9\nlq8AAY4nzd0tvF/0KS22VrbW7cTssLC9bjduwY0oilSaa4gKiuDf85/gupwrBjzG7yfexu8m/pKc\nMKnY6xUjLuahc+4+LQUSBCxJAc4yDpS2AHD1gswT1jrkdKJ/qvfJtiQd2FXN9g1lPuu+/aYImyd2\n5op5GXywrsS7Ta9SgFOkCoEGYFKf57TEpIHdX0fDDQuzuO68EcO2pKg1Sq66aQo6vYpt66XCnJ3t\nNjrbbeRtq6TwQL3PeHn/tLd+9M08u+7WacOaQ3J6uDcuCWDdV4Xe13F9PpO07EgO7JKsbi8+vsG7\nfv+eaibMSMLSpyJ7S+PwCk8GCHA0rK3a6H29oXoLG6q3AFDeWcnClPl0u7oZYZLiKafHTmJk2Aie\n2/sqSSEJXJy+BK1Cc1qk9R8NAZEU4KzC4qlIvWCIDKCzhegw3471giDicgscKG1hVGqYt+/biaK9\nxeq3Ln9PLWKoGp1GydiMcK9ICgJ0LknEtYJPiHZcitFHEHwfjtbV1BNk3b9mUY9oAknwFOyrIynt\nyAHkkTEG5iwaQWJqGEHDrNY+akIcW9f19qdzOnqtQKkjetupTJ2T5hVJfRHcItvWHyamTzudvm1Y\nAgQ4FmosdchlcpxuJx2OTsyOLq8o6s+3NVuxuyWLcKy+9+E0VBPCvVN/d1Lme6IIuNsCnFVYbS70\nWuUPppheTJiOh26cwoQRkYDkbnt5WT7PfnKAzQfqhtj7+9PdPXAfsvAOB6EqObHhel65ay5P3TyN\nUTI5Go8y6r/X+ReNPOUZhdGDuPuyx8RgCNUyZXYqikHim3qQyWSMHBeHIXT4rgOVSsHSa8ZhDPPv\ndp7RJ2hdpVL4ZcAtuXw0AAf31tFtlW5SoyfGM6dP37oAAY4Wi6OLx3Y+wyPbn+LxXf/ixf3/5Z1D\nHwKgVWi5NvvHfvtsr98NSBaks4mAJSnAWYMgirR02Ig0+t9szmYSo4IJDpJ+yoIgsqtQavJaNUjb\njuNJd5cDhVLOtbdMZfeWCnInJfL+y9sBiLZ7Wo3I5ezZUoHMI5BEREQgO8lITlwozk77kAUSTwYJ\nKQOnHscmhA64/ngSl2Rk6pw0Vn6a710XagpCd4QWOVfdNEWKUvewdZ1k+UpKDz9iLFSAAEPxdN6L\nCKJ/KYxEQzx/nHQ7MpmMc+KmAPDc3lcpaC0CIC00hYig8OM2D7e1C4Vu4MbWJ4uAJSnAWUNDqxW7\n00185Kn9UZ0KFJ5Yme4+dXQ27qvF1a/mj8st8OG6EtbuqR7wOIIg8syH+9jbr2nsQNi6nbQ0dhFs\n0KAP1jD7/BEs217BQaT3VDkF1n55iLLiZkoONuJEJB/BWwvprmsmMHduOuedBlYkkOKJrr55ik/d\npnPmp5M1eng9/74v8j4lDCbPTGHpNeMGHLfgwmzmLBqBKVyHMVzHiH4JCkG6Uy84A5y5VJlrqeuS\nEi/+OedRrsm6zLvthpwr/X6rvxjzU6bGTGRkeBa/HnfTcZuHJW8PpbffRndpydCDTyCBx40AZwUu\nt8C9r0gWjJHJp1cxspNBTxzOw2/s8q5zCyL/eH8vd10zwbvuxc/z2VMkWZpm5Mb69bP7fFMZ+0pb\n2Ffawst3zvUWaByI/TurEQTRR1QcLG+lC2hEJAoZhQfqvcHPMYlG9lZJVa5vWTrq+53wCcIYpiMq\nLoT8vFoSU02MnZJ40t67b1D4hHOSB42tGpHbK9pkMhlX3jiZh//QW4cmxHh6ZgkFOHk43E7a7R1E\n6YaOTXMJLgpai9Ao1KSHprKldgcAP8+9DrVCxYz4qagUKnTKIOKC/R8YVHIlN4y88rifQ+fWzQAI\ndvsQI08sAZEU4KygJ/5GIZcxc0zsKZ7NyUfscjAZOSUItAEZ8aGU1HRwqLKdsrpOUmNDqG3u8gok\ngJZOG3ERvla3vOLe7Su2V7JoahKvf1mA3enmogmJKOVSbzRjWBB52ysJ0qkYOU4SSYdrO2nukFqM\ndCECvjf5MWNjWeERSWmx3y/d/0SSlStZZlIzj5/bYDhExxlITAtj3JTEowo+l8lkLL12HDs3ljNv\nSZZfe5MAPzy+KlvFqsr13JR7PeOiRiOIAnKZHIuziw57J4WtxeSEZ7Gldgf7mw/S3N3id4yxEb0P\nMlNiJvhtP5G4zJ1Y9kgxTirTqX3oDYikAGc8dS1dvLFCSpv+1aWjTwvXzcnG6ektloqMNkQumZ3G\nk+/mAZJ16anbZvBdWavPPq39RJLd4fa29ADYUdDAxv21NLXbCAO+Ku7dPzImGMEtMuPcDFQea1RP\nLaSJIyIZmWoiTqlkz9YKb9+z9KxIDGtVmK1Owo8isPlkI5PJyD5JLra+aLQqLrxizDHtG5doHNQ9\nF+CHx76m7wBYdngluxr2srfpO08kYB8GqYINkGRIQCE/sZmxR8JtlkpYyDRa1LFxQ4w+sRxRJGVl\nZamA14EUQAM8UlhYuOxI+wQIcLLpufmH6tWMzfjhpT7bbU4ETzyLAhkgotMouXFJDq9/VYAe+ODF\nbbjcAmHA7FmpfLaxjPpWK5nxoVKLDeDV/+5GAQTr1XR0OXwEU3Q/q1BTvQVDiMabfVVe38nyLeUA\n3HhBDkGewOH0nEj2bKkkIcWESqXgrzdPw+UWf5BCNkCA40lRWwlfl63BqA3l4vQLCBf0lHdWkhgc\nj0OQ8kcbrI00WBuPeBy5TM5Tsx9GrVBxqLUYQRRIMpzaEiqiU8rUDJ01+5TOA4a2JF0HtBQWFl6f\nlZUVDuQBAZEU4LRC4XFNXDE/4xTP5ORTXd7mrQ7dw+VTkwgLUqEM1XLx1CQKt1chuEXkyEhHxrRR\nMXy2sYz/rS5m25pSwj0PmHIgARlTJify8fpSQoAOYO7oWJr7FVUEmHFuJjKZjDaz3dtQOCk62CuQ\nAJRKBVNmp3qX9QFXUIAA35vVlRv4tORL7/KO+j1HHH911qVMjZ3EppptlLQf5uqsywhW62m0NmPS\nGlHJpd9sdljmCZ33cBGdksiTqU799WIokfQh8FGf5aFbUAcIcJIQRJF1e2p4Z5WUfqpVnzrz8Klg\n384qP4EEUL69mvLtUvaaWqOkfxJ5eLCGaLmcJkHwCqQeFMC0UdGUr++tom050IDWY0kyIyIHwoNU\nxCWFsqeoiec8e9smugAAIABJREFUAgngsjnpx+PUAgQIMAiN1mYfgRQRFO4XUySXyblz4q9o6m4h\nVh/tDbielziTeYkzveOGE9h9KugRSXL18AqynkiOKJIKCwstAFlZWQYksfTnoQ5oMulQKk/8zSoy\n8uxpXHosnA3nvzGvhife3sXlCzK5YcnIo9r30/UlvP5Fvs86uVJxWn8ubpdAl8WOLlh9zL8Rl8uN\n4BZRa5S88Nh67/qcMbEU7PcvHumwu1AjowURDWCQyagoaSFJgKQBKoCIagXW5u4B3zslK5IPCxuQ\nAf+6ZTpr99fy4ZpinzFhJt1J/x+czv/zk0XgMzh7PoOSlnLe2vcJ1429hDhDNIIosLxwDZ8WrPAZ\np1GoeXLRnxFEgQ+/W06yMYElmfPYW3+Q+JAY4kNOflzd8aJ2uyT6go3BR/V/PRHfgSEDt7OyshKB\nT4HnCwsL/zfU+LY2/zYFx5vISANNTeYT/j6nK2fq+Vc2mJHLZCREBQOwYqtkrfhwTTGLJx9dqvXy\nTYf91kWFaE7Lz0UQRPK2Vnibj8YlhnLOggyWvbuX8dOSmDA9eVjHcbsFXn7yWwCuvnkKao0Ch93N\npTdMIDouZECR1EMzIgvSI6gubWXr+tJBx0Xo1Kz7+pDf+rmLs0jPjsQeEcSyzeUs33yYlTuq/Ofo\ncJ3U/8GZ+ls4ngQ+g7PrM3h732cUtBRz7+onjjju3im/Q9GtRQFck3GF9zNI1aSDnTP283A01FP+\nymvSa+3w/6/f5ztwJHE1VOB2NPAN8KvCwsI1x/TuAQIgFTl86L87EUV46Q9zUSnl2Dw9qpQKOXan\nG7VSTpvZTohePWh9HqfLzbo9NTS2dTNhRCSXz01Hq1GiVsp9YmFOJxpqO70CCaC2qoOP/iult27f\nUEbuhPghKyRbLXa6rb3NPN59Waplkj06xttOY8GF2axZ3itw0rIicDrcNNSaufcnE+hs7KK6tJXO\ndpvPsW2AN9es3YYZiE82sviyXAr21ZOWHUmwQQNAqid1f31erXf/n1+Qw/jMCKoaLSRFnx1P8wEC\nnAoEUaC4bfCHmL6EBx25j+CZhrO5ibZvVtK+djUAMrWa4PEnt/TAQAx1V7kHMAH3ZWVl3edZt7iw\nsHBge3yAHyRrdlfjcLpZPG1wi0hpTYe3g8K7a4q5YWEWrZ3SzdrlFrj1qd6u5nPHx3PDwiy/Y9gd\nbu58YQsWT7+wi2ak+DV4PR2xdNqOuL3L4hhUJFktdt59ZScO+8DhgCNyo/u8jmFEbgxWi53t35Yx\n8ZxkDKFanA43ao2SCFNvuxaFUo5KJUcbpKJUI+dwnZmRfdxvk2akoFIrGTPZN8slJ9mEWimJWoD7\nfjLJK5yykn54RTwDBBgMs8PCGwffo6C1iNvG/pzarnocbgfzE2ejVWq8YyrN1cQHx1Lf1YhWqcEp\nuMg0plFhrsbhaRoLcPfkO9jf9B3b63dz+/hfnKrTOiE46usp//PdPuvS//ksMuWpf/AdKibpN8Bv\nTtJcApyB2B1ub+C0UinnvEkDu82Kqtu9r9fn1TBvfDytHTbUgKPf2PV5NT4iyeUWcLkFth9s8Aqk\npbPTzwirRUVpC6uXFQAwb0kWI3KjeemJb33GFOytZfSkhAGboubn1foJJLlchiBIirNv5/cedMEa\n5i3J9i73CDCZTMalN0ygtKCRafPScbsFZMAznxygf5e3uCTjgOejVimIi9BTXi+ZtZPPgP9BgACn\ngncOfejtafbvfa95139ZtgqDKpgYfRTF7f5hAwBdTisPTLuTb6u3srJiLXKZnBh9FImG87kg7fyT\nMv+TSduqlT7LaX//J3KN5hTNxpdTL9MCnNGs6dMD7N3VxWQlGr3iJb+8ldqmLs6dlEBRVQcA4zMj\nyCtuZvOBOhKREYWMCgT6VvJQKmS0dNgID9WyZne1V4T18MBPJzNpdNxp73Nf8cl3lBX19kAzhuuQ\ny+UsuDCb5gYLXV0OSg42sm9nNYcO1HPjHTP9jnFgdw0AwSEaLJ12YhND0QapKCtqRm/QDNmVvj/R\ncSFe95zcUyyuzSyV/bcZNWjb7Sy85MgtQ5bOTOWZj/YTGqw+qsrQAQIcL9rtHWgVWg62FlLRWcX/\nRVzxvY8piiLrqjcRGRTO6IijSyTpwSm4eP27d9jf7JtUEqzSE6Y10dLdSpfLitlpwdxu8W6PaXaS\nVW6jOElDbZSa3IgcjJpQLkpfxMKU+djddm+a/rDm0dSEraqS4PETTvuaZKLbjWXPLhSGEFL+8iii\n24XSePpYpQMiKcD3Yt2eGp/lDftqSYsNITvJxFPv7QWgsKqdsqp2xiqVZOo15CFVZ072pJUnI+dP\nv5qOVqPkjy9sodPq5M4XtvDM7TP9BFKQRklyzOltvXC53Hz+v7001vaKuCmzU73iRHKLQVO9mZKD\nkjy021xSUcc+F7TmBgt2mwutTsV1t07D2uVAH6yhs72bLoudi644PhWWz5+cyJsrCrnwwhwyEwa2\nIPVldHo4Vy3IZHzm6Zk+fDZiqyin8uEH0aSkknT3vThbWmhd8SX63NFELpp/qqd3Uuh0mLln0yP+\nlaOBuZlTMBHpXe5pwzEUoiiyvlrqEaaWq/i4+AsAHpt5PwZ18FHPcVXFOh+BdF3OFUyPneQz5uuy\nNawq/JorvmlDbxPROHqbUI8rkiJZkv8+1btOo1CjUQycCu/u7kYRFOSzTnA6KPvTnQDE3HQLIVOn\nHfV5OFuasR0+jGHylKPe92gQ7HY6Nm/EbTYTOm8+CsPpd21XPPjgg8f1gFar4/gecAD0eg1Wa38n\nzQ+H0+X8BVHko/Wl6LUqrj43k30lLTS0drOjoJFVu3ozn+parCQiI0QAa5uNKrebLpuL+D5VnOVA\nakYEhyrbaWiTLhR6rZKCijZy08Jo9KyLMgUxf0LCafMZ9FB6qJGdG8uwdTs5tL+eipLeuiW3/HEO\ncUlGvyc6fbAGvUHtHbtrcwUyGeRtryQ1M4K1ywswd9o5Z346UbEhqNXSM41Gq2Lk2DhiYkOPy2eQ\nHGNg8bQkIo3Di++SyWSkx4eeFoUhT7fvwYnA2dJMxX33AOBub8dWdpim9/6HvbICy66dmCaMp6O0\nDGWokZbln6OKivG7cZ5JuAU3Npedv+18Bq1CQ4Ihjm5XN3/b8TQ298DxfWvLtjA1ZiI6VRBttnbu\n2/JXWmytg1qEKs3VFLaV0G7v4M2C9znYWsiBlgLv9kxjGlG6yAH3PRL7mvIp76wkJ2wEd4z/BZmm\nNL8xicFxxDc6CdlxEKXbX/AB6FLS0MQPXvXa1dFB+f330vLJh7R9swJkMnThRoruu5/mjz+kJwDU\nUVuDcf65R30epbf/EsvunVj25qEflYtCpx96p4Hmae5EplQik/sL1q6D+VTc9yesB/YDEH3dDd/L\ngvR9rgV6veahwbYFLEkBjpmGVituQSQ72URilPQE0D1IgHFPVSCFp31Gf2/zvh3VnDM/g58tyeG3\nz24C4OMNkr8+O8lERlwom7+r4+pzT0xFWFEUqaloJzYxFMUgmXVHIj+vlpqKdg4X9rrX0rIimH9h\nzhHN3SPHxuG0u9myVspo2enJgisrbqauuoPIGAOjxscf9XyOFtVJqG0W4Ngw79zhs2zN/85nef9d\nf/LdfugQSXffe8LndSLoclq5a+OD3uU3C97nzYL3Bx2/JOVcVlSsRRAFitpKiAiaQoO1CZvbzuba\nHVyYtpAQtb914vGd/zriPFyi+6jn3mRtYV21dO26PPMiTFp/q6yzrY26J/6Grsm3VUjIjFnoc0dT\n99LzAMiGiMep/OtfcLVKD1eCzUbzxx9K4qgfjvo6qp74G3KNhi6PGIm4/ErCFi72GWfZvw9HTQ2m\nhYvo2pfnXW+vrKDq74+T/OcHcXW007ltK9aD+dgryom95ZcYJg1uaTLv2kHdi897l1MefQx1dG/t\npvbV33hfR1x2OdqUVE5HAiLpLMTpElAqZCfcF739YAMA4zLCSYoe2DSdk2wiJ9mEq7ydusp2uq1O\nJiOnHMFvrCiKhOrVPHrTVO59Zbt3/ZTsKCKMQfxoRsoJO6eC/XVs+LqI4BANF145BmOYbtD3MnfY\n2LOtksjoYEaOi6Op3kxrs2/os0wGU2alolINLT4yR0Z5RVIPjXWdiCJEDPK5Bvhh0HVgP80ffQBA\n6hNPUXbX773bwpdeQsvnn/rtYyspRrDZkGtP3ybCg5HXuP+I27UKDaPCs6mx1JESksR5iXNI0yXw\n3MH/8s6hj2i3dxAXHOsd39LdRojaQLu9A6fbxda6nRxs8a8DtjR9Md0uG3KZnBXla3yyynroEUHz\nE2cRMUD6/duHPkDXLZBZaUM93d/KKths1PzzSZx9BFLMjTfham/DeN75yFVq3BYLje+8iWDzt5g5\nm5pwd3WhCAnB1SIJJE1iEvKgILqLpAbfMqUS/ZixKMPCUYaE0PzJR95tPTR/+D7NH75P1LXXEzJz\nNq3Ll9H6peRm7Ny2BUddrc94V3MzpXf8ym8+dS8+j/v6LkJnzBowC828fbvPctP77xJ/+28RBYHa\n55+la/8+NImJJD/wsN++pxMBkXQW4RYE1uyu4b01xdy4JIfMhFA2Hajj/MmJGHTHt7z71vx6lm0u\nR6mQMT4zAnO7/486JkzHnVePB+DTUt/eQimedPMFF2az7utCBLfoTVWPDdeTEBlMdZOF7CQjEUbJ\ndXAiRd+hfVJvMkunnfde2UlGThTnLfU11YuiSGOdmU/e7D0XhULOtyuLcLkk0Td+WiK5E+KRyWTo\nDcPLztAF947LHhPDof31HNglxXrFxId8r/MKcGqxlZdh2beXkKnT6C4uouGN/xByzgyURhNhF/wI\nwW5HGTL4/7hludQqU2EwoAoLJ/3ZFyj99a0AhP9oKaqoKOpfeQmAqGuvp+mjDxHtNuy1tQSl+bt6\nTnfKWssItrqx6BRE66K8zVnnJ85itiwVcfcB9OG5tG2uQRVto/yZX6KQyZBfZkJQyPiybJXP8Rqs\njSw/vJJDbcV+7zU+cjTnJc/F6uwmJ3wE0NsDbUP1FqbESDV6ai31dDmtPJ33omfbZn4z/hdkGtM4\n0HyQ7LAR5DXux1pUyE2rpSzejsZ/or32euxVVbja27wipD/a9HQf64rCID0U1b/yIqqICLSpaSAI\n1L36EpZdO332DZk5m+jrfwIyGe4uCzHJMTS3+hZzVhpN1L/+CgBhF/wIZ1MT5h3bAGh85y0a33nL\nZ7yjRkrEMZ2/iKARWaiioqi4v9cqGTQiC13OSK84b3zrDVzt7UQsvcTnOM7mJix5Ui240HkL6Fi3\nhq79+3CZO2l44z907ZWsVWEXXjTg53I6ERBJZxFvfF3IpgNS1eWP1pfQ7XDjdAl8ubWCG5fkMHVk\nNJ1dDowGNQqPj9jhdLO3pJnsZBMhwxRSrZ02XvniIACRxiAO7qphx8ZyooGGPuN6Mp+6rQ5am/0r\nsesNajJHRVNe0kLpoSZcLgG1Ry888LNJrNtTw+j08GP7MI4Sm83ps1xS0MjoifHEJPSm2O/dUcW2\ndb4pu2u/9H0qnTb3+/UumzwrlbqqDjo8MVgZOVHf63gBTg5NH75P28qv0eWOIeKSS9EmpyCKIpWP\nSKEOrV987h3buUUKFG79ajkAyQ89ijomBplCsjoKNhutK7/GOHcettISAOJv/y0AiqAgUh7+K6Jb\ncgcFT5iEafIuNOMnEzJlGu6uLlo++wTB2oXodtP0/ru0r11N1PU/JXT2nGN+0LDX1uJsbiJ4zNhj\n2n+4xH9bwNS8FtwaFYkP/g4hVE/3nr3Y3ltDW8XHALT3pIsXHPTuF97hoinM33pT1lExoEAC+L/R\n1/utC1JK1rfyzkq6Xd38Y/cL1Hb5N3d+7bu3yTJlsLvR0ztRFLltbW+ZE0dVJVWPPeq3n370GKKu\n+wmtX3+JYeIkH4EkbR+LXKdHsHZR9bdHBpw3AHI50df/xPudURpCvK/7EjxxEoaCfILHjccwcTIA\n4Rctpfbfz/pYjCIuuwLj/AXUPPMPlEYT4RctRa6VHk7jbvs1tf9+FkWwgYTf3YlMqcR03kJq/vVP\nuosKseTtIfyii3HU1tK1L4/WFV8jWCXLetiSC4m49MfIFHLaV6/i8G9v953f+ImDn+NpgkwUBw4c\nO1aamszH94ADcDaVoD8WIiMN1Dd08NH6UnJTwxmVGoal28ntz2w84n6jUkzkl7cRG67joRunoFTI\nefLdPAoq2rxjEiKD+c2PxxAequW7shb2l7Zw9YJMn4vrF5vL2LWxnC5EcmND6K7rTWXdicAV8zLY\nW9LMeZMSSIsI5r1XpJiK8Eg9NpuLLk/KeVZuNPMvzGHNFwUU5TcQagryioNZ52WSO3HwWJzj/R14\n+4VtdJntJKWHUV7cG3R9/S+nUV/Tya5N5bS1+Aq9IJ3Kpwo2wK13zz2m9y8vbqa+poOpc9IQBNHb\nfuRIx/uh/w7g9PgMBKeDkltv9lmnjonFUT94m5j+BGVlk3jn3bitXZTefhsAitBQ3B1S6YzUJ/+J\nyjRwUGvfz6Dtm5U0ffAuANqMTGwlvgIh4tIfE7bkwmHPq4fDd/4WV1sbiX/6M0HpGUe9/3DZ+4db\n0bX31ipOfuBh6l56fsjP0jhxAn/JrEIcZkmKW8b8dMCgbqfg4r7Nf8XstAywF/x63E18VvoVVWbf\nrN6MShsXbOoc9P3048YTdfV1KENDhyyQKLrdNH/yEW0rv/ZZH3H5lTR/KMVnadPSSLrnfp/tR/Nb\nEEURZ1MTosOOKiLCK4gGw1Ffj9IY6jeu8rFH/b5jPfRkYsqUSgSnk9pnn8ZeU40mMQnjnHnox4wd\nUNgdK9+zLcmgX5yAJekM5bUvC9iW38DKHVWMTDFxsFwSOkumJVPdZGF/aYvfPvmeMXUtVjbtr2PG\n6BgKK9t9xlQ3WXjpi3xuWJjFP96XnpKSow3MGC35+Vs7bazdUsEIZIDMRyABPPTTSSTGhLBoahJ1\nVe1egQSQOSqa9OxI3nlR8lWbIqWMCXOH5KrrEUgAe7ZVHFEkHW8EQSA4RMPiy0ZTX9PBp29J5uC3\nnt/mM84QoiE9J4qxkxPYsq6U4vze+IIg3bFne6VkRpDiSalXKGRc+fPJqNSBYOozAdHh9FvX96ae\neM/9BKWlIdjtyDUa3NYu7BUVVD/V25uru/AQoihy+He9tXt7BJJ7bM6gAqk/qpjeCuwD3byaP/8U\n0+ILjmhRqtm+AWHrLsKXXIizoZ6GN/7j3dax6dsTJpK6i4t8BBJA/X9exdUpfQ6RV15N2+pvCJk6\nndaVX4PbTfwdv5NaWezew73Tb+WRVsna9NTsh7lz4wMIouQG/8v0u2m1tdHpsGDSGkkLHbg7gEqu\n5KqsS3jlu7cG3J5lyuDGUdfw0LYnfdZPr5VM4Il/+jPWgoMY5y3AvH0rqugYtKmpR5UdJlMoiLz8\nSsw7tuFqayNkxiwiLr1Myl78/FNEh4Ooa24Y9vEGfA+ZDHXU8K3U6piBm+VGXX0tlQ8/6LNOlzOS\n6BtvQqHXewWhXKUi4Xd3HvN8TyUBkXQGUlbbwbb8XsdWj0ACWDQ1iT1FTV6R9Nof5/HK8oM+44M0\nCt5cWcj/VhcjiCJTcqLITjbR1e3k4w2HKanu4P7XesXNJ98eZtqoaBRyOSu3VxLnFoGBL7LBfQKV\nN37je5FOHRGBIVSLTq/21vwBsA+QEed0+Ad2n0jcbhGVWnJBmsIHvqDp9GrmLM4iMVUK2jxnfgZN\ndWYSUsLInRhH0HGM+wqLPLaU2wAnH9HZG+Sb+dJrlN97N87mJgBC5833xgb1VBBW6PTockaS8e+X\nqHrsEexVUrkM887tiC7f30JthIoPRzbz+45yntr9PLPjz+HKrItps7VT1lnJ+MjRPuODx/jXzkr7\n+9Mc/sMd0oLbTfehAnQ5vlaU7sOHqf3XP3Fbep/Eq7874Hcse0XFsD6To8XZ2krV438FoCJGzayb\n76Vt1UrMW7cAUiyM6byFmM5bCIBp8QW4OztRR0fjtliwHszH/NwLPH7br70unB+lLeTz0q/JNmUS\nHhTm0+vM1dmJNf8A+rHj6dy2hdBZc5CrpIeckeHZTIoex/6mfGbET2Vp2mLKOiulx0KZjChdJEvT\nFrNh7xdcuqadJpOSsFoH8qAgtGnpXhF5LKn3fYm/4w+0r1tD5OVXer87yQ88jKutFW1Kyvc69vFC\nm5xCxGVX0PyxlFygyx1D3K23nTbVso8HAZF0BvKvD6QijedPTuSbnb31iP54zXiCg1RMHxVDfYuV\nqSOjkclkJEYGs80TLXTjkhxUSjkvLcvH5ZaESGaCkbnj4hFFkdL8RgqaLdg9x8xMCKW4uoObnljP\nmPRwyktbyEJOaISODk+c0fR56bhdbnZsLKc4v5HJs6QsNGUfS8iEc5IwevqsXXDFGEoKGknLkiwn\nzj4iKTEtjKrDrTjsLlwuN8rjnJouiiIVpS3EJ5t8Ms8Et4jCY6rXaJX8/LczMXfY+OD1XcDA7j+d\nXs3VN08lwA8bwWNJCpkxS7ICXH0ttc8+jUyjwbTAv4WEzWXjUFsJo8NzSH7gYcof+DOOmmrqX37R\nO6bRpGTtFAOtIQqQyXhqt5RK/W3NFkaFZ/FWwQdYnF0sSlnAuerplLfWkxMmBR/H3PQLXC0tWIuK\nMEyejNJoJPXxv2MrO0zdi89T/dQTjHj1vzhbmpEpFChCjTS9+7aPQOpLk1GJatxojHtKsNdU42pv\np+zuPyC6XCTd/xDapF6rjMPtQK1QU9FZRZO1mezwEYiieMTCjNbCQqqf/BsAdpWMz+aFcl5SMqbz\nFnpFkrpfzSBFUJC3FlTf2jq1/36WEa/+F4DzkuaSYUwl0eBfb6jtmxW0rfiq9xz/9zbRP70RRbAB\nVXg4Pxt1jc/4EabeWENnSwsT9rWTsrwVAEO3JJINk6ce1+QSTXw80df5WozU0dGoo6MH2ePUELZ4\nCWGLl5zqaZwwAiLpNMflFqhvsVLVaOHbfbUUVknuMb1WyRXzMrwi6V+/mUVwkPQkpFLKuWJ+r0l8\nXGYEH66XUsxnjpHcZhX1ZlbsqARgdFoY1i4HhQfqUTVbmaDTYIs3kBobQkqswet221/aQorHgjT5\nnGQyR/b+WEsPSW6n3Vsq2L2lgqtvnkJnWzdKlZwb75jpU3soIjrYJ7Xd6WmWOmp8HLMXjmD1Fwcp\nzm/EanEQYjy+RfH6Bl/3jfcRBAG5ovcCp9YoCY8KZsGF2dTVdDJyfNxxnUeAs4cecSFTS5bE4LHj\nSLznfuRarY+bQhAFPiv5ijVVvb37Hp1xL1ZXt8+FeOU5oZTHqFic+yOSDYnerKoeXtjf6/5aUb6G\nFeVrALgp93reOPgesfoYbj//Zp/YI1V4BEpTryXFbbFQ8eB9CN3dRN/wM2xlvgkJDqUMtUukJUTB\nu4tMiPIa5tW4GFPs7rVKAXUv/JvUv0luwy9KV7CiYi0z46ayqdY3/fvm0TcwNjJ3wM+vZO3n9BQr\nWDfJINXPQEpvVxiNuNvb0WWOGHBfAMUg2YEymYy00BS/9c2ff+ojkHpo+O/rfXcm9bEnUYVLD3Ki\ny0Xriq8w79qJo7rKb19tegaRV1496BwDnLkERNIpZNehRhrbu1kyLZm84iae/fgA4SFa/vaLabRb\n7Lzx9SFvHFF/bv/xGORyGbdenIvLLXgF0kDEhut59a55Pn22rpifwYgkI0FqBeEhWm+gMIDL6mRu\nShi5E+IRBJFzJyawereUGhoKKFUKUkf4tqTom8YOsHlNCd1WJ1m50UMWZ3Q6JJHUE4Oj00vHsnY5\nUGuUqDXK49YjrGBfb6zIrs3lTJqRAkiWJPkA85RaiAzsjw/ww8VeU0PTe+/gMpu9N01NXK+QHij9\nflnpCh+BBHDv5kcZm2BnrscbXpyo4VCK9P2fnzgLuUzOYzPvp9ZST1ZYBr/fcB82t2TnvTh9CZ+V\n9t7se+JoKsxVNFqbSArxtaD0rXrct+5Nw5u9ouvNC8KIDU/moKsGmSCyNPMCgirWYXV1czBVy5hi\n35ihnpo/pe3lrKhYC+AnkACK2koHFEmCKNBZVYYWWDXVQFGyhv/LlbLOZDIZyX9+EGdLs5QKPwjq\nqGiUBgMusyRWBaeTlk8+Qj9mrJ9b0dna6s00VEVHE5SZhSosjJZln/keVBRpXyu5ugA6Nm6g5bNP\nBp1D6KzZZ5WLKUAvAZF0iqhp7uL5z6TKuWMzInj9S6kkfkunjRc++4684maf8amxBiZlRTFtVAyC\nQk64J0h4cvbwgu8GEhnjMiSh8+F/dvlt27SqhE2rSpDLZdx852xcboGivbWokZGSGe7nButfz6ey\nVDJF902hH4ycsXF8t6fGG+ujD5aeyGsq2r0B1NPmpjF+WpLfvi6Xm8OHmuhot9FUb2bBhTlotAN/\nrUVRxO3qjXXauVESSaIoIghioFlrgGEhOJ1U/vUviHa7d50qNpb60Ql0mqtJ8rh3Ouyd3LPZN41b\nhgyVQoVGocbskJIe9mXpmLtber1lrBSLdlXWpd7eYwZ1MFlhkmX4qTkPc9vauwCYFjuJ8s4q9jb5\nxw45BP9gcoDQ2XPo+HaD33pNYhKRN99MW8G/iDbouDb6cjrsHZyXPJc5CedQ2FaCw+1gVcdrzN1l\n5quZoYw6bCOjyk7R//2UFT/3T+W+OH0JLbY2NtZspdbin0YP8N3+9UQ1dtORGM5FV/2Om3VRqBS9\nD3xKoxGl8cj9BGVKJeOeeYp9f7oPV0sLtpJi2latpG3VSjKee8GbkWWvqqLiofu8+yU/8DByj/XP\nOG8BoijiqK3BXllB0wfv0bbya0JnzsJacJDmT6WA8MQ//RltcgrI5SCTUXzTzwBQxwYszWc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3mgRUJSv6Ag+v7+WZzVVU2rfJLuvJu67CyiL5qDX9DpG4HorIdiXU42ub95nICkXtRnm302/YVX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\nXhAjSRAEQRAEwQtiJAmCIAiCIHjh/wHXEhrcRruPagAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109c31588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# to_plot = raw[['AAPL.O', 'MSFT.O']]\n",
    "to_plot = raw.iloc[:, :4]\n",
    "(to_plot / to_plot.iloc[0]).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding Rolling Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sym = 'AAPL.O'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.DataFrame(raw['AAPL.O'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Hd3ZeFwi82jrcvLGrHICTVc2D1cyEzps/lvtuX8vogs7yB4+t8+9stmR2KT8J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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109cdaac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['SMA1'] = data[sym].rolling(42).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['SMA2'] = data[sym].rolling(252).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ICdIDEBzY/JJAua2SfeUHSAiKI9wQNiD3tWdnUf7F56j0euJu+hWqDnKaHU+O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\nEKmgEhEREQmRCioRERGREP1/XyLl2BFH+jAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112ff6be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mf3M+NezfR8Oe7wkaNZq462/o12f3NgmohBBikGvbQwXw9heWLu+prGsNhipr\nbbg9HooqGlCpwKDXEBzkXZPkcLj9hhTbqqlvXVHo6mQelhganC43R4vqSI4NIcTo30OV3zzcNzEm\ns1/TJThKiil6/t9DKhv6icgqPyGEGOS+2p7vd/zt7iJuOH8spdWNBOm1hAe3/yFquxrwmaV7WHh6\nOgBBeg0v3HMmdqeb259bxeaS7exe/h1p6W5MWiOXjbqQ5JBEwH++ltstPVRD2YqNuThdHpJiTO2+\nawmoUkOT+60+ittN+ftLUJxO4m64CePIUf327L4iAZUQQgxyB3Kq/Y41ahWKovB/L20GYNGD7bNJ\n1zf5p03YbikDYM74RBRFYUf5DoImrQOVggfIrVOhoHBw6yFGR44k1hhFXWMC4A2kZMhvaNuw1zt/\nLjq8fZqM/Hrv4oTU0KR+q0/5+0to2PM9hvThQzJFQkckoBJCiEHMoygEB2lpaHLx8M0z+evibahU\nKuydDNOBN01CaVWj37ni5jlVE0ZG83X+OpYdWYkaLU25o/DUR6A0hqIOr0CXfJRDHOFQNaCFoOkq\n8Ggob0plLO2TQYqhYdLIaL7dXcTp4xP9zjvcDo5UHyNEF0ykoX9W1zlKSqj59mu00dEk33XPkEyR\n0BEJqIQQYhDbcqCUhiYXc8YnkBoXwpjUCA7mVrN6W+sw4Nrvi5gyOoa7nl2P0aDhtAnxHRemcfJV\n+XKONGRh1BpZGHcdb2xrTZ3gqYnHXhPP8/edxo6y7/lkz1YaVOWo9HZWlrxPRtrtxBij+vqVRR9o\nWcigVfsHL5uLt2N11nPusLP6JbBx22zk/+uf4HYTc+kVaEPD+vyZ/UUCKiGEGMRahmounTscaJ0b\n9XHzFiIAi1dlodVkgK4J9/Dv2aiqxjDRhKc+HNw6FLsRlb4JTVw+Rxo8pIYkcbX5coaHpbFjRBP7\njlX5PXPTnkoWTJ3F16s1VJZa0SYfoj75GB8f+ZRfTPhZP7256E0tawpUxwVUx2rzAJidOL1f6lH9\nxSrcNTVEnHMuoaed3i/P7C8SUAkhxCBWWtVIZKiBmAgjABpNx6uwXv10P/rR+9CEVeNpCENlaEQb\n4593SnEYmJsym8vHnk2Q1juX5t6rJ7P2+yIWr8ryXffOl4eoqbf7JqW7CkeTmN7IrvK9bC/ZxfSE\nKX3xqqIPuZvnwGmO64UqqC/EoNETa4zu8zrUbdlM1cpPUAcHE33p5T+Yob4WkjZBCCEGsUa7m+Cg\n1mXuP79wbPuLVB4M4zahiajAXRuNff9pNO06i1G287FbpmE/PBm7ZRpN35/JuamtwVSLeZOSePau\nM7hkTrrv3KebctukXlAxO/yfeSV0AAAgAElEQVQc9GodHxxZgUeRFApDTcs2Quo2PVQOt5PSxnKS\nQ5L6PF2Cp8nm3VpGqyXlnvvRGI19+ryBIAGVEEIMUoqiYHe4CdJrfOdSYkOYMjqm7VXoR36POtiK\nuyoOx5HJgAoUDSmmNDy1sXiqE/DUxnLV/NEdrvICCDHqSIoJ7vA7AJUtghkJU7A66jlWm9tLbyj6\nS0sPVduAqqC+EI/iISWkb1f3KR4PBU89gauqkvD5CwhKH96nzxsoElAJIcQg5XIreBQFg87/n2qD\nrjXAUodVookqxV0XiePYJJ654yzfdzMy4vzuu2DWsBM+Lzaifa/B5FHe4C2/rJ5JsRMAWH50FU6P\nq921YvBqmZTedgrVZ9lfAZAZbe675zodlLz2Mk3HjhE8YSIxV/64z5410GQOlRBCDFItqREMev9/\nqttmQQ+KK0PBO89Jr9YRZtIzf0oyGrWK9IQwXrx3Hvll9USGtt8Q93gdBVQLpiWzL7uKosoGxkZO\nZVTEcI7UZLO7bC8zZC7VkNGSR0zTHFHZ3Q4s1UcYFppKZnQHw8i9pObL1Vi3bMaQNoz4m3+BWje0\ns6GfiPRQCSHEIGVv3oPv+B6qoormDY11TXjCilAcBjzWSK4/19vTcMN5Zn76ozEABOm1jE6JICa8\n6zkrIUYdf7ppOj87r7XHIi7SRGK0ieLKBlQqNdeMuRyA3eV7e/x+ov+0BFQtE8Hzrd7hvpER6X02\nObwpN4eqVZ+iNplIuf+3P6gUCR2RgEoIIQappk56qMJDvL1NusRjqLQunEUjABVzJyYeX0S3pSeE\nEdtmnlVUqIGIEAMOp4el3xwhMTieBFMc35fvZ39l1glKEoOJW/HvoWr5bzcsLLVPnqe43RS/9B88\nNhsxV16NxtT5/LwfCgmohBBikGrZtPj4HqqWeTDGaCsalRZ3eSo3XdB7wzY6bevztBo1Nrt3vtQX\nW/NRqVRcNeZSFBRWHP38pJ9xIKfqhNneRe/ytJmUnldXwJe53xKuDyMjakyvP0tRFCqWfYCzrJTw\nM88i4sz5vf6MwUgCKiGEGKSafEN+Gr/zCoDahVNbw7CwZBb97hzmTeq9lVr645534/mtQ4CKojA2\najTjos3k1xdR3ljZ7fL3HavkX0t285+P9/W4rqJrHo/iyymmVqs4UHUIBYUrRy8kWNd+s+Seavh+\nN9VfrEITEUH0wkt6vfzBSgIqIYQYpFonpfsHOD8+cyTq4DpQKaSHpfX6c/Va/5+G5NgQJo30Jn5s\n6a2aEJ0BwOGaY90uv7zWO6l+z9HuB2Oi+/72xnbySusBUKtU5NZ5ty0aGZHe689yFBdR9s5boFKR\ncs/9aCNOnf0fA1rlZzabZwGPWSyW+WazeTLwHOAG7MANFoul1Gw2/xL4FeAC/m6xWFb2VaWFEOJU\n0DIpPei4HqOJI6Mxzyohpw7GRI7s9efqjnseQETzKsHqegemIB3myFGoULG2cCOnJU7v1sTmH1iC\n7EHN6fKQW2r1HSuKQk5dHhGGcCIM4b3+vNJ33sJVXUXUwksxJKf0evmDWZc9VGaz+bfAq0DLLMV/\nA3daLJb5wDLgd2azOQH4DTAHOA941Gw2d71GVwghRKdaeqiOH4LLtxaSU5fH+OgMxjf3FPWm43uo\nACKbJ8LX1NsBiA+OY0LMOPKthZTbKrpV/uH8Gt/nrNzqHtRUdKXJ0Zov7NwZqeRZC6hzWEnvg8no\n1u3bsGUdxDQuk5hLL+/18ge7QHqojgJXAG81H19rsVhaNojSAk3ATGCDxWKxA3az2XwEmAhs6+X6\nCiHEKcPXQ3XckN/3FfsBmJU4rU+WvHcUULX0UNVY7b5zoyNHsKdiP7l1BcSZYgMq+2BuNZv2l4Ki\nEOpqZOvqLSRPi0Wx2/E4HChOB56mJtx1dQCodDp0cXFoIyIxjUxFMUWiUstslUC43B4O5HgD1tMy\n47n27NG8+P0iAM5IPq13n1VTQ8mrL6HSaok+BYMpCCCgslgsH5rN5vQ2x8UAZrP5dODXwDy8vVK1\nbW6zAr3flyiEEKeII4W1/G/NYcB/UrrD7WRbyU60ai3jovomw7VO28GQX4g3IeOh/BpKq21cMied\nkeHpgHcJfiBJPhVF4ei+I5xWtYeM+hziHDWQC8VbAqtXEaCLiSV40mSMo0YTPHESaoMMhnRk68FS\n/rt8v+9YrVbhUTwcq80hzhjD2KjRvfYsV20Nhc8+jeJyEffTGzCOHNVrZQ8lJ5Up3Ww2XwP8AbjI\nYrGUm83mOiC0zSWhQE2HN7cRGWlC28H/cftCbGxo1xcJaacASTsFRtoJ3G4PTQ43wUZdp9d01E5P\nLNnt+5yeGum75ssj66hsqubiMWeTmhjT7r7e8o/b5xAbYSQ22ps/aLjDuyHyuj3eAYrRwyI5a1oG\niVlxbC/dzblj5zIpYVyHZTnrrFRt3UbRp58x5lg2YwAPKo4Gp+COjid9TApWl4rZU9JwqrRoggyE\nxEajUqtw25poKi3DUVlJQ3Y21Tt2UbPmS2rWfIlKqyX+3HMY9rPr0Zp+eJvt9kTbYGp4Uhg/vWAc\nbmMjNlcT05Im9Or/N4+8/zb2vFwip01h5GUXoNYPnWzovdkO3Q6ozGbz9Xgnn8+3WCxVzae3Ao+Y\nzeYgwABkAF2uh62ubuzu409KbGwo5eXWri88xUk7BUbaKTDSTl4PvLiRyromHrh2MhnpUe2+76id\nln57hIM5Vb7jYK3Kd83OfO8P5bSoqX3avglhBvB4fM9QnP5791VVN1JRUc9PzD/myR0v8vnBtSRp\nWufl2AsLadi3h4a9e7BZskBRUFQqjphSOBaczOgLFvDJ9hLiI40sy/GuQCtIDuO73UXYnW5efmCM\ndzgzGFQxyRiAlCtDKSuuxnbkMI1ZB7Fu2UzJZ59TsXkbsVdfS8i07k2O/6GyNge/AJfOHc6lc72b\nEW/N8SbzTDAk9trfju3YMUrXfIMuLp6YX91JZa0d73q1we9k/o06UQDWrYDKbDZrgGeBPGCZ2WwG\n+M5isfzZbDY/C6zDO9H9DxaLpanzkoQQ4ocvu7jOt+9eTom1w4CqI6s25/k+33P1JF+QoCgKR2tz\nCNWFEGvsu96pjoSYdGjUKtzNCSKNBu/Px/CwYYTrw7BUH8HZUE/jrl3UbViH7fAh371Bw0cQPGky\nT1v0FDm9vRfnpMWi21XmmycGsGpL63vvOVrJpFHt31Gl1WIam4FpbAZRFy2k6tNPqPp0JcX/fYHI\n8y8k+uJLUAcFtbtvqDlSUEtOSR3nTO/+5PEt+0sAMKdGcOHs1g2xd5d7+zl6Kzu64nJR/N/nwe0m\n5vIrT/m5bQEFVBaLJQeY3XzY4b8IFovlFeCV3qmWEEIMfYXlDb7P1ubEit2RFh/ChBHRvuNyWwU1\n9lomxY7v954YtUpFkF5DQ5O3p8qg0+BxOnGWFDM/W4smK5ej79yF2uUGlQrjGDNhc+YSPH4i2nDv\nlFp30Wao8o5MaDRqtBoVdY2ODp+3Pausw4DKr046HTGXXUnIlGkUvfAs1Z9/Rv2unaTc+wC66OgT\n3jtYFZbXY3O4+cfbOwCYnZlAyAmGizuyy1KGWqXizisn+LLelzSU8X35PoaHDeu1FX7WHdtwVVUR\nftYCQmfM7JUyh7KTmkMlhBCia/Vtgqj6xu4HVKOS/df2vH9oOQCTYjJ7VrGTpNV4f5wTmiqwvbuI\nI4WHwO0iHW/29spwDXGzz2LYgovQRbcPhkyG1p8cjUaFVqOmpr7jgKo729IEDUsn9cGHqPjwfaxb\nNpP7l4dI+8Of0SckdOf1BlxtvZ0/vrbV75zD6YYAAqpqq53vj1ZgMmgpqWwgJiIIU1DrfUdrsgGY\nnTgNtarnPUmOsjJK33wD1Goizz63x+X9EEhAJYQQfaSsxub7XH8SPVTTzHG+zzZXE1lVhxkWmsrM\nhKm9Ur/uClYcnFGyjnH1OahRqAkKJ23meEwZ48iN1/JO7ofMTjQyqoNgCsBkaF2EpFWrfQEawDnT\nU1A8sGZnAZq4PA6FbODhzau4znwFYyK7XjWmi4oi4ZZbMSSnULHsA/KfeJTEX/4/TGN7P09XX1m5\nKbfdOYfL08GV/ooqGnjoVf+lkiOTwvyOj9V6yx4ePozeUPP1Vyj2JuJ+cv2QC1z7yqk94CmEEH0o\nv02G6u4EVDHh3jlAGcNat+04VpuDgncfvYGYeF3z3bdct+9dxtdnU6EP573Es/lv8iUk3PJLwk6f\nQ8bwaUQZItlcvJ3F69d2WIbxuB6q4KDWY4NOQ7BRizYhG336ARzqesoaK3hu96vk1OV1VFw7KrWa\nqAsvJmrhpbjr6yl85kkqln+E4uk6KBkMQk3te6IcAfTUfbG1ffu0XVWaW5fPrvI9BGtNJAbH96yS\ngD0/j9p136EJCyN83vwel/dDIQGVEEL0AY+icKy4jpTYEMCbV+pYUV1A96pVKl/epxaHqo8CMDpi\nRO9WtAseu53Cfz9F2VuLcas0rImZzqLUhWQHJ/vtIaNVazkr5kIANhXs7rAsTZseKa1GTWpciO9Y\np1FTqTmKLs2C4tRj338aPzVfhUfx8OaB9yhtLA+4zjGXXk7Sbb9GFRRE1Yrl5D/2D5qyu7/nYF9q\ncrhobPIPsnOKvQH4X34+g/hIbxqIrnqoquqavIlSjxMR0pqf64PDK7C7HVw5emGPh/sURaFk0Sso\ndrt3IrpWBrpaSEAlhBB9ICu3GkVp3aoF4F9LdgV0r8vj8RsOq3c0sKFoC0ZtECP6YEPbTutRW0Ph\nv5+iYe8egkaM4M3k89kWMc4XSGnUKhRF8V1vdMWhOHVoIsrJL2u/HN3VJjjQqFUkxQT7jss5xq6m\nr1BcOuxZM1Aaw5gcPZkZ8VMpbSzn7YPvd6vuIZOnMPyRxwieNJmmo0fIe/TvFL/2MrZjx/zqPFD+\n7+XN/PqZdX7n8svqCQ/RkxYfymmZ3mG0tqsgO/L1zkJcbg/Xnj2af9w6G61GjSlIy8WneYf29lda\nOFabw7hoM7MSp/W43rVrv8Wen0/ozFmEn3Fmj8v7IZGASggh+sDbq71pA9oO9TV18ePYwu1W0Khb\ne3/2V2ZhczVxTtp8DJr+SZrorKqi8Ll/YztkwZQ5npQH/o8qvf8kebdHweFsDZIKyxtx10Wj0tv5\n22fvsy+70u/6tvvKqVVQpeSjTbGgH7uVnY4v0Kl12C3TUGzeXD9Ol4ebMq9lZPhwjtXmUlhX0q13\n0AQHk3zn3STfdS/6hESsmzaS/4+/UvD4o1i3bx3QwKq2eTL+wZwqFEXB4XRTVddEYpQJgLDmHsra\nhhPndDpS6N2kZGxaBAlRJl66/0zee+QiYiKMNDptvLbvLVSoODftrB7X2Xb0CGVvvYHKYCDq4kt6\nXN4PjQRUQgjRyxRFobQ5PYBKBcMTW5MBtg0qOuP2KH7DY9nNc4gyenG7kBNpPGQh729/wZ6TTejM\nWSTffR9qXccrzZrazPHZn12Fq3AUikuHNvkIr63a41+uvfXa74q/4zvrx+iSstGEVRGqjuTOKb/g\nnz+7gBljvZPxW4a75iR5l+Q/vv4/OD1dt9/xgidMZNif/0ribb/GNH4CtsOHKP7vi+T8/ndUf/0V\nHvvAJaJ8Yslu1u0ppqzahgLENwdULZtRVzfvndhZ8Ncyxyot3vs31nZ+3cbirdjdDi4Yfg6jI3s2\nVGzPz6f4pRcBSL7zbgxJyT0q74dIAiohhOhlRZWNtPz8/fa6Kdx/bes+d397YzsAq7bkcsfTa1m5\nvv3cHrfHg7a5h8rlcXGo+ghatZbkkMQ+rbfi8VCx7AMKHn8Ut7WO6MuvJOGWW30/0o/fdhojjls9\n1pLewOX2kFtqRWkKwVWcjkrjxhVr8QsEsou9c8huOH80m8s3Y1AbcWSPw35oKpnOyxgRnk5shNE3\nodrZHFDNTJjK9PjJFFvLKLAWntS7qTQaQqdNJ+Xu+0j/+z8JnX0aruoqyt99m7x//I3GrIMnVW5v\nWLwqiw++886RS2gJqJo3o84vr+M9y8fcv/ZPrCvc5HffrkPl5JR0nOl7X8VBPj7yGQaNnrlJszu8\nJlC2Y0cpfO5pXFVVRF5w0ZBaOdmfJKASQohe1nbe1MjkcIwGra/nobjS23O192glNruL73YW+N3r\nURRsdjcajTeIWXHsC0oby5kWNwmtum8nAJe8/ipVn61EExFB8t33EX3RQlSa1lQHMeFGRib5D/tt\n3l/ClgOlfsOZrrI0PPYgPNHHOFzjDRhrG1rzTTVFHKLB2ciY4Ezc5Wl4auIYFtdarq65d64loFKp\nVIyN9PbOFdQX9fg99QkJJP7iV6Q/8hhhc87AUVhA4TNP0rBvb4/LPll7jnqHR1tWdsZGGNGH1/C9\n7gPWFm6kyW1nieUjPs3+ktKGMhRF4eP12Z2Wtzr3GxQU7pj0C8INJ7dfnaIoVH/9Ffn/+Buuqiqi\nLlpI7JVXnVRZpwKZni+EEL2ssTmb+E/OGe2bXB4ZovcNA36zs4CsvBrQNVETlMW3BY24PC5GR4zg\npSXeHpjsYiuKorCtZBchumCuNV/eZ/VVPB7Kl7yDddNGDKmpJN3+G3SxsR1ee9Hpw6i3OXA4Pew4\nVM7H67w/6ndfNRGAMJOOukZwHpuIIWMrn+d8TUpIEja7t6dq0ng9K459glEbxMTwaWzFmx/pjImt\nvW/G5nxV5TU2hiV4g4GU0CQACqw9D6ha6KKjSfj5LYRMnkzRi89T+MyT3jQQp83ptWd0xqDXdDjh\nvCXwtrpr0I7ZigcPZtNEfjR6Jov2v8Nn2V/yWfaXhOvDMCaMgooo0mIj/MpYfnA1R2tzyIwey8ge\nLGKo/ORjqlYsRx0URPzPf0HI1J5Pav8hkx4qIYToZQ3Ny+GD22SqDjG1TiZ/a/Uh1OHlBI3fSG34\nLpYeWs5HRz7l8e3PUWHYC3h7ZnLq8qh11JERNQZ9H01GVzweKj9eRs3Xa9BGR5N4252dBlMAYSY9\nv1yY6ZfyAOCZpd75UtPGxrHowQXMTBuLpz4cS/VhHtnyNBUN1ahDqjli/AyA68dehcbVWkbbuT/T\nm+dQffd9a/CUEByPRqWmoL645y/drKbejtvjIWTKNFLu/x1qo5GSRd5eur7mcnnabSkTHqzHoNOg\nKAqfZX+JovLgzB7PtOCzyYgewx9m3cu15suZFjcJm7uJkqCdGDI3MeOMerJrczlak8OKo5/z7t6P\nCdWFcNnIC0+qboqiUPrOm1StWI42Koq0Pz5MqGw83SUJqIQQope19FCZ2iSuvHr+SN9nVVA9+tG7\nQONCUzmKGNtEQhtHo1Fp0KUexjB+I9rEozy/+zUApsRN6LO6lv3vbe8wX3gEaQ/9GX1cXNc3gW9I\n8niVtd7NoMODDdizZpCsHU2No4YXLc+hz9iCR+Xi/PSzmRQ7HnOat2fl6rP8M6GnxIYQGWrw9egB\n6NRahkemkVuXT2EvBFW5JVbufX4DS7/xzl0ymceS9Ou70ISFU7HsA6q/Wt1nqwAVRcHtUUiOCeah\nG6b7zv/6Cu9/52/y17GtdBfhmijcFck02r1/T+H6MGyFyTQdnsh9E+4lpGEUamMDn+V9zr92vMBT\nO1/k89yv0am13JR5HUkh3c9grrjdVCx9j9pvvkaXkEDynfegj+95MtBTgQz5CSFEL+uohyomwsjw\nxFCyy6owZGxFpfbgODIJR3Ui9c2/23decyEv7XoXTUQ5atNhnB4N15mvYGIf7N2nKAqlbyyibv06\n9ElJJN91H9rQsK5vbKbupLeiZTNerUYNHi1520bijtKgS7OgUkGYOpqLh5+LSqUiIsTAogcXdFhO\ng82Jw+XB5W7NyXXFuAt4fP1/WFe4uUdDoHUNDl9Khy+353Pt2d75WSbzWJLvvIv8Jx6jfMm7qPR6\nIvogE7jL7f0PrtWqGZEUxl9vnkmQQUNMuJEaey2f5azBpDVyYezVLCKHj9cdY8HUZHJKrCz5+ggA\nu49UEh6cico9nBuuiibPWoBGpSE6KIrzM+fSWBv4XogtvIsSllK9+nM04RGk3H0fupjOeyuFPwmo\nhBCil7X0UAUb/f+JjQk3kucqQaVzMNowBWfoWA5WVfu+r7eqcByahiaqGHVIDfdddBEjwtN7vX6K\nolD12UpvMJWQSNIdd6GLju5WGWp1xwFVy7BQS2DlcAKl6Si2EDQR5Vy34LyAho5aUiZs2lfCGZO8\n86cmJ2ai1+g53Jw1/mQUVzbwh1da9707vhMqKH04w/74F/IeeZiyNxfjtlqJvmjhST+vIy2T7fXN\nbZTSPHzq9Lh4eud/sblsXD7qIibFpAA52OxuHn59O2dOTvKV4XJ7qKyzkxgdysyEqX77OwbrTTTS\n8eq/Eyl943XqNqxDGx3NsD8+jCYkpOubhI8M+QkhRC9r8A35+c+R0RlcaBNyUBSYFD4dk8E/4MrK\n9QZX7qpEnHkZfRJMAdR8+QWVH32I2hRM8r0PnNSQTmcBVYuWgKqFpy4GZ14GExO63ui4LZe7NXGo\nVq1hVPhwShrLqLV3P2AA2HawrMtr9AkJJN99H9rIKCo/+pDC557B3dBwUs/riLP5nY5vo2/y11Fh\nq2R24nQWpJ5BqMk7pwqgoLzetxJwbFrrJPS2W8ycLMXjofStxdRtWIchNZXUBx6UYOokSEAlhBC9\nrMHWMuTnHzCV6fegNjbgrkgmwhBBWLD/RPOO9mTrbWVL3qX8/SWoTSbSfv9HdFFRJ1WOppOAKina\nu0otv6y+3XdnTQ08GeToFG8aheDjJm6PifTORVuV81XAZbWVW+ofiHUWFhpHjiL57nvRJ6fQ8P1u\n8v7xN+wF+Sf1zOM5Xd7hOF2b5K0bi7ax/OgqgjQGLht5oW/PPXubxKl7j3kDqnmTWnuqehpQKYpC\n1acrqP3uW3Sxcd5FCTLMd1IkoBJCiF5SUWvjtU8PUF5jw6DT+O3H5/a4KVcdRXHpcOZkotdqSI3v\n316Ahv37qPlqNdqoaO9k44TuT1pu0dkcqoua95BzHbep78yMOK47O/BM73MneNMoOI8rZ07SLJKC\nE1hXuKnbk9MbmpzsOlzhd+5E084NySkM+/NfCTtjHs7SEgqefIL6XTsDfp7D6ebh17dx6xPfUFXX\n5Dvf8k4tPVRbS3bynmUZRq2Re6beRqi+878LvVZNaJsVo6agns3cqVr5CZXLP0IdEkLqg78PeFGC\naE8CKiGE6CUvfLSPDXtLqKhtIkiv8ftuTf5aHNhwVyaCokanVZMS0/kPZ9tgrDc05WRT+OzToFKR\n+MtfYRzds21sOhryu/WScei03vcOajOcOd0cy88vzOjWO+l03mttdhfFlQ0UV3qH3Ew6I2elngHA\nkZrOE1t2pLOs4scHbW2p1GoSbryZ2Gt/irveStF/nqd2/bouVwA6XR5e+mQ/uaVWXG6F+1/c6Bu+\nbHmeVqvG6qjnf5ZlqFQqbhp3rS/fVmcuPj2dMamtSVD1upP/O6ld9x2Vn3yMJiKCtAcfQhse0fVN\nolMyKV0IIXpJbpsf7HHpkb7PDreTT7O/xKQ1UVWcDnh7J0JNHe+Pd/a0FM6ZltJr9XJWV1Py+mvg\ndpN4620YR4/pcZkdDfnNHtfa43XtglFoNWouO2M4Yabu59AyNAdm73512HduxZOXAjAy3NsLdqTm\nGGemnB5wmdpOhikram0kRgef8N7Ic36EIS2NwqeeoHTxa7jraom68OJOr1+y5nC73rBN+0uYNCqG\npd94V+ppNPDmwfdwuB1cNeZSxse039Jl7sRE1u9p7YnTadXotBqev3seq7fl8aMZqSesd0cURaFu\n4wZK31yMSm8g8ZZbe9RbKbykh0oIIXqBR1F8q7ZuON/Mzy9s/XE8WpuNy+PitMTpKA7vHCO9Vk14\ncMfzX64+a5QvY3ZPKR4PRS88i6OwgLA5ZxA6c1avlNvVpHRTkI4bzjOfVDAFoNdpOv0uzhRLrDGa\n3eX7KKovCbjMlu1xpo2JZXZmvC9oLa+xBXS/aYyZtD89jCY8goplH1D65uud9lRtOdA6H25M83yw\nytom7n52PftzvIsPrOoiDlRaGB6Wxpykjv+73HT+WN/fFbSuDDQFabnsjBF+qTkCVfP1V5S+/iqo\nVCT/+jeYMsZ1uwzRngRUQgjRC0qrGnG4PEweFcP8ycl+w1tZVd5elrFRrcNs3p6G9v8EazWqDs+f\nDMXjofilF7HnZBMyfSbxN93cK+VC53OoektHbeD2eIMXlUrFxcPPxaN42FtxIOAyWyZ4jx0Wya0L\nMxnVHOiUVAUWUAEYkpJJufcB9Mkp1K79jrxH/oqjxD+os9ldvmSccyckcuMFYwH4ZEOO33XVePdx\nXDjifHSd7NOoVquYP6V1Mn/LkOrJql2/1rsoITiYtIf+LMFUL5KASgghesF/l+8HYPcR/2GeClsl\n6wu3oNfoGRUx3He+s/lEkaE9XwbfonbdWup3bMeQNoy4n17fq1uHtB3ymzwqhsf/32m9VjbgSxfQ\nlq05SAEY0bxHXZ61MKDy6hodFFV452G1zG+LjTAC3uG5btUtOZmUe+7DlJGJPSeb3L88RO36tb7v\nW3q8FkxN5uaLMoiNMHYwRKpQ4clDp9b53qUzV53VmmW/J3OmGg7sp/StN1Dr9ST+8lcEpQ076bJE\nexJQCSFELwhrng914/lmv/Orc7+hyd3EVaMvRa/R+35YOxvSOtkhsuPV7/mesnffQmUwkHTn3d3K\ngh6ItkN+40dEEdMcnPSWjgKHxuZ0FACRhgiCdSYKAgyo/u+lTb4eopZgLamLeVMnoo2IJOW+B4i/\n6WZUOh2lixdR9u7bKB6PL/BrGY7TatSkxYf63a+Jz6VeqWFctLnT3infterWtjg+d1mgrNu3Uvj0\nv8DjIfFXtxE8fuJJlSM6JwGVEEL0Ak1zj9Osca1JMhVFYV9FFqG6EGYnTgPg8dtO53c/meLbGHf2\neP/JwCeaOxQoxeOh4l5lx9MAACAASURBVIP3wOMh6bZfo4uM7PqmbmobUPX2ikRobU/wznmC1i19\nwDvslxqSTEVTFTbXiYfsnlyyC5u9NZ+TobmHyqDXMCY1AnR2NhRuxeF2dlZEp8LnziPl3gfQxcRS\n8/VXFD77DC++sR7wT2nwy4X+Q2vamCLUqLlmzGXdel6QvnsBlaepiZLFiyj+74uodDqS775Pgqk+\nIqv8hBCihzweBUt+DeA/VJVvLaTWUceU2Am+RI2RoQa/Yb07fjyZ6WMKiY0w8urKA1x/bs9X4JUu\nXoSjqIiw0+YQPL5vNlbWttkcubMknz0RExbErHHxTB0TS15zMs5PN2RzTZtNpoeHp5FVfZhNRdtY\nkDavw3LsTrdvEniLtv+NoqJdGKI28a6liQ1FW7h98s2E6LrXcxU0fARpf/oLhU8/SeO+PdyizsIS\nkkZcvh1Hmh5dXByxEUFkDItEo1axvygfdXAd8fo0wg2B9Rwa9BrsDjfGAPNOeRwO6jZtoPLjZbit\nVvTJKcT99GeYxpi7vlmcFAmohBCih77ZVYjd4UatUvnNU/rk2OcAzE2e3em9EaEGpjb3wDx888we\n18V27Bh1G9ejT04h5sdX97i8zrRdoajR9H5ApVar+NUl3k2h6xocAHyxOZfzp6cQ3pwdfH7qXNbk\nr2N90dZOA6qW4bfwYD21zeW07TlyxB5EXetNuplrzefTY6u55iQ2XtaYgkn9/R85vGwl7tWf/n/2\nzjuwreps47+rLdny3iu2E0fOInsnZJAQQsLe0MEqHXRQ+NrSr5N+3QO6oFBG2auMQICwIZvsxHGG\n4sR7L9mSbe17vz9kySNOPGI5MZzfP1xdXZ1zdC2kJ+/7nudlqv04bDhO6YaXkDQaJJ2OK1VqfOYo\nJslNtO2EpBgPTa3rUTweZLcbub0dT0M93ro6/G0OJLUabVIykTNm8Iul46jRxJKecHqxJ3s8NGze\nSvnzL+KprgZJImblKuIvuRS1aegpTkH/CEElEAgEZ8ixzuhU0CUcoMPrxGo7TpY5o8fuvnDitdmo\n+fdDACTdcBOa6Oh+XjF04qK6BJVGFd7qkUVTUlm3uZh2lw+Xx0/wXUVqIxhjzuB4SwkunwuDxnDS\na4OCauq4BFbPzaKwpDkkShqdzRyzH0XtMeMpXEjKwl1sqtpOdlQWcztTtINBkiR2RI7nk2wTqe5G\n7pofg6+iFE9tLYrPh+LzotTXkOOXoQ6ggKbdBT0HUanQxiegTU5G8Xrx1FTT/NZ6ACKA4oQEdMkp\n6FJTMYzJQZucjM/WjLPoGM7jx3FXlIPfD5JE1OLziVt1sfCYGiGEoBIIBIIzJLhFfu2CLkF1uOko\nsiIzpQ+zxnDRvH4dvsZGYlasxGjJD+tc3YujwxGh6o5ep2bepBQ+2lOJp5ereaY5naKWYirbanrs\nogwSrJ0y6TUkx5lC/l6KovBIwZP4FT/J3gmU+uCq3Ct54uhT/LfoTaYlTUGvHvwGgU/2VYEk0WxO\nIXHVkh7Pba7azovW19G1adAUTOXnV52Hyu9F0ulR6fSoTCa0cXFImq57K7uctB8+jOtEEe6KCtyV\nFXQcKqTjUOFJc0saDfqMTOKmTEQ/bzG6lNRBr18wdISgEggEglNQVusgKkLXr5WBy+1DrZJCxdkd\nXievn3gHgPMSJoV9nQCN616jddNGtMkpJF57w7BaJPRF9/G1YShK703Ql6p3m5hMc8CjqcJRdQpB\nFRC7Rn3PYv9GZzPV7bWMjx2HzmGhlAYyI7JYnrGId8s+5kBDIXNSZgx5vQ/d3TMFqSgKmyq3o5bU\n2I8vRNEYMU/oX2yrDEbMM2ZintEVMfM7nXiqq3CVlOCzNaGOiMQwLg9DTg4qrY7ERDMNDX232RGE\nD7HLTyAQCPqgpqmd+57cxT9fK+j3WqfHj1GvCYmMPfUHaHG3sjxzcb+92YaDtoIDNL/1JuroaFJu\nvg0pzCm43gynd9ap0IUElb/H+THmgNt5b4PP6sZ2HnztIHW2DgCMvewGjtkC7V+mJ04OpSz9foVZ\nKdORkHjJug6Hp23Q6zTpNaQnRpwkaPc1HKS6vZaJcfkonjOzmFAbjRjHjiN2xUoSr7meuIvXYhpv\nQaUdHssNwdAQgkogEAj64K1tpQCU1HT9S/+Jd47wg4e29mg3IisKTXYX0RGBH7Nml40Pyj5BJalY\n3tnEN5y4qyqpfvDvIEmkfes7Z9z0eDDcc900Lp43hrR+CqWHg2CEqnfKLzkiifzYPKy241Q4qkPn\nX/y4iD3HGnj2/WNAT0ElKzJ76wNCeXzsuJBFg0+WSY1IZm3uKlx+F7vr9g96nU6P7yTx5pf9vGR9\nHY1Kw+qc5Vy1JJe7r5066LEF5zZCUAkEAkEvGluc7DhcD8DYtChkWcHmcLOloIYmu5t2V5djd5vT\ni9vjD9XmPH/0VZpcNpakLyDWEBPWdcoeD/UvPAd+Pym3fQ3j2HFhna83k3LiuHrp2LCnF6Gr5Urv\nlB/ArORpAJTay0Pnutd4SRLkpnXZE+xvKOSorYhxMTkkmxJDTZP9/oBQXpA2G5WkYlPVtn49rroj\nKwqKcnIT5hJ7OW3eduamzGRMVCZr5mczOTd+wOMKRgdCUAkEAkE3FEXhkTcPIXdGobw+mZ8+toN7\nHtwausbmcIeOPZ394fRaNRWOKo40H2NsdDZX5V0S9rU2vPgczqNHME2YiHnu8LZ+OdfQhSJUgfu9\n+2g9J6page51VJVd13fzmpppSSK1myv6gYZAQfe14y9HkqRQhCrYKzBKZ2Z28nTqOxp54ehrA16j\n3Pn63o2j99YfABjRDQqCkWdARekWi2Uu8Aer1brUYrGMA54EFKAQuNNqtcoWi+UXwBrAB9xltVp3\nhmnNAoFAEDaKKls5UW0PPS6vP7mOpqapHa9P5v1d5ayclQmASuvl4YInAVg5ZmnYozbuinJat25B\nm5xM2re/NyJRorNJqCjdG4hQPbQuIIqeuHc5qRHJaKSAoA3S2uYJHUd2853yy34ONVmJ1ceQFhGw\nEwgak/r8XdGvm/Kvpqa9jj31BxhTnsnyzMX93uO+BFVJaxmbKrdj1kViiR3ZCKJgZOk3QmWxWH4I\nPAYEDT7uB35qtVoXAxJwmcVimQEsAeYC1wMPhme5AsHAqWpoo6XN3f+FAkE33tpe2u81D79xiF8/\ns5M9jbt5+uDraNJOUKh9nRZ3Kxdknc+UhIn9jnEm+NvaqPjzH8DvJ+GyK1Hpw18UfrYJCSq/HBIu\nEIgoqlVq0iJTqWqrpcxegawoVDYEhHBynIkLOkUvwIbSj3D6nExPmhISSEHbB3+3cdUqNavS16BB\ny2vH36KopbjfNQZfr+4mvHbV7UNB4ab8q9ENwYZBMHoYSMrvBHBlt8czgY2dxxuAFcAi4H2r1apY\nrdZyQGOxWBKHdaUCwSBobHHys8d3cvc/t+L2+vt/gUDQSXld4If4hzdM77F77aoluUzOiQs8UHvR\n5hagyzlMo+4w2owivJKLJRkLuSx3dVjXp8gyDf99Cbm9nbhLLsM8Z25Y5ztX0HXWUL27o5xDpc2h\n8weLmwBYkbUEWZH5z6HnaXd6sTncTMmN53d3zAsZecqKzOaq7Zi1kVycszI0Rtcuv571WQcP+mg/\nGige31Z9+qRLVWM7r20KiK5ghMov+9lffxCTxsjEONHy5fNOvyk/q9X6qsViye52SrJarUEZ7wCi\ngSigqds1wfMNpxs7NtaERnPmjUAHQmKiuf+LBJ+b+7TneNfHsbiujfOnZwzr+J+X+xRuRtt9UhSF\ndqcXS1Ysi2dl8fT71tBz51mSqba1oY6vRpNehMrgRG6LxluTg6Txcum0Ody6cGitYwZzn6reeBP7\n1s0YUlOwfOV6VLovRtQj0RYoDm9sdfHAywdC5//63wLW/+UyLkpcxFH7UbZV7KFVFRBcMVGGHvf2\ncH0Rbd52VuQuIiu169/8UVGBBEykuef17W4/sj0e2WViV90+yo+b+dut159UIwVw+x8+JhjgMhkD\nXlBP73+VVo+D5TkLSEkO7waF3oy2//fOFsN5n4Zi7NldwpuBFsDeedz7/GmxdfqDhBthcjYwPk/3\naUdhTej4gLWeCRnD14Lj83SfwslouE9tTi///eQ4ly/OJdasp8Plwy8r6LUqGhocONq76nAqmis4\non0T3djAV5uvNgtv5XiQA1+jcbqYIb3fwdwnn8NOxX9fQ2U0knr3j2hqdQNfjLR2+ynS9xEGTej+\nTYiewLaKPfx7z1MgzcDv84eeK2kt4/69/wIgLzKvxz13u7wANDV39Djf6nABEp6i6RimbKWaAk6U\nrSQmsmeKtaapnW7ZQrxeHyXVtbxX9ClxhlhWZ6wa0f8XRsP/e+cCQ7lPpxNgQ9nlt89isSztPF4N\nbAa2AqssFovKYrFkASqr1do4hLEFgmHhWLmNCIMGtUriRHXr2V6O4BzlhQ+L2FxQw3MfBLyKyuoC\nX64pnRYIIXsESWZD7Trc6hbktmjcR2fhLZ8QElMAybGmsK5VURSq/no/foeDmBUXoo2NDet85xo6\nbd8/V9PHd0WapiVOZnriFJrcTahiGkLO9TZXC08ffglZkVmeuZiJ8T3Tb+qQbULPlF9bp9BSnGb8\nLQmozS18VnGA3ryzvazHY5VK4WXrOryyj2UZCzFpz8zIUzA6GIqguge4z2KxbAd0wCtWq3UPAWG1\nHXgVuHP4ligQDA5ZVrB3eMlIjCQ6UkeLw9P/iwRfSGqb2wGoaw5Ey4NNji2Z3dIzkh9d/k6aPY1E\nu8bhPjyfDGM2d10zlfPGdnkJJcWF90ezveAA7rJSIqZOI/6Sy8I617nIqdrbdC9Q31JQi70k0E9R\nk1SOWq2gKApPH36JemcjyzMXc1XeJaiknmOFBFX3MBPQ1uENHXsr81BkFR/Wvous9BRerl51mjZN\nMXvqD5AemcqCtKGlgQWjjwGl/KxWaykwr/P4GIEdfb2v+SXwy+FbmkAwNIKNaiOMWhxOL9WN7fj8\ncuhfqwJBkNbOlF7whzQoqPI6BdXlqyPYUP0OKr0TS8x4sj3ns45KJuXEcd7YBNqcXgpOBOr1zEZt\n2Nbpqa+n9vFHAYi/7IoRby1zLqDV9l1vW9HN1uLJDUcByF6UTl10FSXKVh4u+IxjLSeYGGfhynFr\n+xxD080pPYiiKLQ5vahVEn5ZQemIxt+UijOxin1VRczM6Ipy7bEGyoWTMpzYNCeo0NWgVWn55nm3\nYNAYEHwxEM2RBZ8rjle28ttn9wBgMmiobgxEIF759ATXXzByLTkE5z5Hy2w02wN1OV6fH5fHx7GK\nFrKSIok0annzxLu81/QxGoOK2ckzud5yJWpJTV5KQkhwRZm6CsLD5QPldzqpf+5p5I52Eq65DkPW\nmLDMc64TNPbsTUV9G4UlTUzO6YoWSqWzkOObqNMfo64J4g1xXJV3ySn/RupeTukALo8fv6wwJTee\nrORIZoxP5DfrGtAkVvH8wbeYljYOtUrdafKqoE4uw5F2FA2gyGpusFwZdqd8wbmFEFSCzwUlNXb2\nWBt457OuWoZIQ1fEYEtBjRBUAiAQedh+qJbKhvbQObdXxuZw45cVxqSYaXLaeL/sE+INcXz9vK+S\nHpkaunZCdlzoONIUvqhUkJqHH6TjUCH6MdnErlwV9vnOVbSnEFQA9790gN/dMS/0uKTSjdQwm/HT\n7MzITWd55mLUqlPvKNf0ckqHwIYFgEijlquWjAVgUsJ4rK0luKLr2Fm3j/mps3j+g2No0orRZhSh\nRU9HVTpqezpzV8w8o/crGH0IQSX4XPDkhqM9Qv8QiFAF6XD7aLa7iIsS4fcvMvUtTl744BgHTjT1\nON89dRdp1LLuxNsoKKzJWdlDTPXGpA/vV6h921Y6DhVizBtP+vfu/kKm+oLoO1N+SbFG0hMi2FfU\nc9/Thh3lPR4r7ghumLiUrOT+t8WHjD27FaU3tboAiI7sikJetnAsv3lxMqqpm3jt6LvUNDg5KO9E\nm1FHpCaSu6Z/g3c6GlmyLH1ob1IwqhGCSjDqOVHdepKYgkANVXd+9O8t/OSO8fhkP2OiMtGqxMf/\ni8Z9/9mJ09230etLHx8HoE1fxt76AjIj05iRPPW04yXFmvjyhePJTRs+W44gzuIT1D7xKJJGQ+IN\nN6EyfLH/MaBRq3j2votwtDrRaVV8tKeS5z8sCj1f09Te4/pZ+UkDElPQvfVMV4QqWE83Lr3rb6vX\nqVE8JvzNKXTE1/JR43rUcWCQY/jG1C+Rak7itrVJQ36PgtGN+EURjHp+8/SePs9HdItQqZPK0GYe\n40+73wdgXEwOt0y6kRj98P8QCs5d+hJTk3PjKCzudN6W/FSpCpCQuG3ylwckupfNGF7TWABfayt1\nTz8JQNq3v/eFrZvqTXSkHo8zsJFgybS0HoKqqLKnPYpBN3DT6GBz5Bc+KiI9MYKJ2XFYOwXV+G47\nPoPfKd7iKcitCUgaL3JHFMsmTSMnOmtob0rwueGLGz8WfC4I1jn0hcmg4fLFOagim9FmBXb/LEyb\nQ5TOzPGWEp478spILVNwDnCqz8oVi3OZMyEJ1B50lt3UdNQxNXESiab4Pq8PN4qiUPfUE3gqKzDP\nm0/E5ClnZR3nOn25lXdnMLsuNequsf784n58fpkjZTYgkAIOEhOp57JFOaCo8Tdm4KvNQbbHMz1P\nRKUEQlAJRjnBOgeAKxbn8MtbZpMQ3dlGwqhl3nQz+vzdSCoFz/Fp3Jh/Nb9Z+BPyYnI53GxlffF7\nJ3nKCEY/Lo+PHzy0lXWbuxraltUGTDtXz+0ZSfCpHTiSt2GY8THqKBuT4/P58oRrR3S9QRS/n5qH\nH6S94ADG8RZSbrvjrKxjNKA6xY69r186iVn5SaxdkD3gsczGnu17gjYIfXHZohzGdeu88Ktb5zA2\nDClfwehDpPwEo5ome5egumRhDgC/uGU2x8pbyE6J4q3i90El4ymdgNyaiKwoqCQVV+at5Z/7HuPd\n0o+I0UezOH3eqaYQjEKKq+002d28ubWUyxfnAvDezkDRcm5aVNeFkszLJS9T3VFDmimVKYn5rMpe\njkGj72vYsOIqL6PmkX/hratFPyablNvuCJsVw+eBU92bGeMTmDsxeVBjRUX0FFSPvHkIOLU7e3cL\nh7TOxssCgYhQCUY1jZ0Rqu7/YowwaJk+PhGP38PO2r1oVRommgNpE5fbT5vTS5Y5gx/PuQuVpOKd\nkg9ocYv2NJ8nyutO3qRQ3rlxYWyoyFgha66V6vYa5qXO4qfzv89l41afFTHVVnCAqgf+greulsiZ\ns8j4nx+hjT87KcfRyL/uXsLaBdlcu2wcWs3Aa6eCxETqOH9q2knnb714Qp/XG3RdsYj+Uo+CLw5C\nUAlGNY2tgQ70N/ThMfVB+UaaXM0sSptHvDkSgFc2nuC7f9vMweImYg0xXJy9ArvHwfbqXSO6bkF4\nWbelK9Xnl2Va2z3Y2z2kxpuIidRz/QV56GJtNMhl5EZnc03e2WnloigKdR99TM1D/8Df5iDxxi+R\n9s1vozaK3m8D4de3z+XP31qAXqfmyvNzuWju0ArDJUni5tX5PVoJAczO77s2KjMpckjzCD7fCEEl\nGNW0tgV2/MSaT44q7K8/iFalYW3uKtITA1+An+6rAuCTvYH/LslYiEpScbj52AitWBBuKhva8Hi7\n6uK+9sdP+WhPJQBLOqMQMyZHED/ZCsDVeZeclaiUv62Nmocf5PjfH0TSakn/3t3ELl8x4usYzaQl\nRAyrt9zS6T39o06VVsxOGZgdg+CLhaihEoxqnJ19+3obLNa211PdXsvk+AkYNPqT6hxCr9MayYhM\npdxegdfvRasOv/O1ILz05Un21rZSAKaOSwAIpXmXZy5mTFTmSC4PAHdFBVX/eABfczNREycQ/5Vb\n0SYkjvg6BD2ZNi6BZTPS+WRv1Snrp6ArbbxgcspILU0wChCCShAWGlqcmE3aHrUG4aDD7UOtknq0\npVAUhWeOvAzAzE5jxvRegkpWugz8xsXkUu6o4pPKLVw4ZllY1ysIP47Ohsd9ER9toLi1jF11+0gx\nJXHFuDUjuLIAHcesVN3/JxSfj7iL15J/+1dobO4Y8XUI+kbpbD+jO00tVqRRy0N3n3/adjiCLx7i\n0yAYdrYX1vKjh7fz3PvhT6O1u3yYDJoeofni1jJK7eVMjs9ndvJ04ORdPEWVrTS2BOqvVo1ZjlFj\nZEvVZ2FfryC87Dpaz4udjue3XjyBeZN67vZSqeCpwy+iKAqXj7sYlTSyX4EtGz+h8k+/R5FlUm6/\ng4Qrr0ZSD76IWhA+3N6A+Wuw1c2pMOg0qL/ArYAEJyM+DYJh59G3DgNwpNwW1nmaWl3UNXfg8nS5\nX3d4O3jp2OsArMha0kNoJcX2LPT984v7AYjURZATlUWTy0abt2f7CsHo4pn3rKHjvIxo7rhkEkum\nde3eOt5STKOziTkpM5iSMHHE1qUoCo3rXqX+2adRmUykffNOouYtGLH5BQMnWJM1RtRJCQaJSPkJ\nhpUjpc2hY4nwbifedbQegNQ4U+jcu2UfU9VWw7TEyYyLye1xfVZSJPU2Z+hxQ2vXcZY5ncPNVirs\nVUyIHx/WdQvCR2ZSZMjhOhiVvHbZOLw+mckTtDx1+CUAFqTNGbE1KbJM84a3aX5rPeroaNK+9R2M\nY8eN2PyCwbFyViZajYoVM0e+tk4wuhERKsGwcrCkS1A12V3YT1PPciY0211sLqgG4K5rA3VSn1Rs\n4dOKrZh1kdw86caTduismZ/N5Jy40OPu9V2Z5sDunsq26rCsVxB+ZEUJiam1C8Zg7NyoYNRruHVN\nPrvsn9LibmVtzirGRmePyJoURaHuP4/T9PqrqEwmsu79qRBT5zhRETouXZiDySDiDYLBIQSVYFiJ\n62VfUFprH/Y5FEXh3kc+o6apI+Qr5PK5eOPEO+jUWm6ZeGOfTW3HpJi5+7ppocdGfVeNRFBQ7arb\nh18+uYGu4NynurErXXvF4p7RyVeK1nPUVsS4mBwuyl4+Yg7k9c8/g337VvRZYxjzy1+jTRQ7+QSC\nzytCUAmGjWMVLaHu79M6t6d3r28aLkprHfj8AZ+h1XPHAHCw8Qhe2ceyzMVY4gYWAWi2u0PH8cY4\n5qTMoKqthqKW4tO8SnCucqyiBYCbV+f3EEy17XVsqtxGkjGB2yd/ecTElP2zbbR+8jG61DTSvvVt\ntHFx/b9IIBCMWoSgEgwbv39ub+g4WADuPkNBZS238fAbhew71sBvnt5Nh8vL4c46rRtW5LHovFSc\nPidvFr8LwMyk8wY1vtLNPmFa4mQASu3lZ7RmwdkhKKgsmTGhc7Ii859DL6CgcMW4NZh1I+Nw3bZ/\nH7WP/RvUalJuu0N4TAkEXwBEklgQFpI7C8Vf31yMRqPC7fGf5ELcH+0uL394fh8AO48ECtC3FNTw\n6sZABCn4w7mn7gDNLhsrs5aSEjG4pqhtTi9mU6B4OSd6DBISe+oOsDJrKWqV2M4+mqhp6kCvVffY\nzVnhqKKyrZrpSedxXuKkEVmHfcdn1D35OJJGQ8YP7sWQnT0i8woEgrOLiFAJhoXgjrsgwVqqljYP\nj64/zNPvWXF0DK5A/fkPTvaxanZ0pemCu7j21B0A4PyM+QMat7truq37eDozc1JmUN1ey9slHwxq\nrYKzi6wo1NucxJj1PVJ6x2wnAJiaMDJiyrF7F3X/eQxUKpJvvV0UoAsEXyCEoBKcMdWN7fxrXWGP\ncwbdydGdqobBeTw53SenC9/fVRE6jo7Qsa16J8daTpAbnU2cIXZA4/7fbXO48vxA0XJTq6vHc9dZ\nriBCa2J7zS5kRe7r5YJzkDe3lOD2+snrbAkSJCioxseODfsa7Nu3UfPwgyiyTOrXvkHUnHlhn1Mg\nEJw7CEElOGMau/k5BYkwntwTr77FiaIo+GTfgMbVnKatw0VzsnD6XLx+/G2MGgM35V814PVKksS4\nzh/e3daGHs/p1TqmJU7B7nFwsPHIgMcUjDwHjjfytT9+Qnmdgz2df8crzu/a3XeipZQjzcfIjEwj\nWh8VtnUoikLDKy9T+/i/kXQ6Mu/9KZHTpodtPoFAcG4iBJXgjOlulglw/tS0UF1Sd0pby/nT7n9y\n98af8frxt3sUhPdFU6sLtSqQvtHr1Fy6MDv0nFrj5x/7H6XD5xxS7ZQlK4Yok5bth2rZV9RTVM1P\nnQXAM0dexuVz9fVywTnAQ+sK8csKr2w8QVVjO+eNjSe2m23Hjto9ncXoa8O2Bn9HO5V//B22d99B\nm5hE5g/uxZib2/8LBQLB5w4hqARnTH1Ll6D6zdfmcvPqfCKNPfc7SEY7O71vUOaoQAI+LN9IYdPp\nI0DNdhdxUXr+cudC/vTNBd0akcqcYDvljkqmJU5meebiQa9ZkiRmWJIA2LCj566+nOgxLMtYhNPn\nFBYK5ygPrSvE6wukZAuLA7s+4ztbhgQ50VqKTq1jXExOWNbgKimm9Cf34iw6hmnSZDL+54cYcoSY\nEgi+qAhBJTgj7B0ePtxdCcBfv7uI1PhAwXf3pqFSRCv6iTtQJD+3Tf4Sd834BgCPHXyGktaeYkaW\nFVweH/YOD63tHpJiTcSa9UQatWjUgTE1mcco8x0m0RjPVydej1Z9cnpxIKyclQFASrfWNbKicP/L\n+9m1MzCXtfn4kMYWhJfdvTZBQMCZP0i7t4Pa9jpyorLCslvTsXsnlQ/8BX9bG7Gr15D+vbvRxicM\n+zwCgWD0IASV4Ix4Z3tZ6DiqjzQfgCalBEntx1tuYVxEPjnRY7jRchV+ReZfB55ge83u0LUvfXyc\nu/+5lR2H6gAY381TyKZUo5vwGdrUUuL0sdwz80506r7nHAjBbvJHSptD6cfyOgeFxc00VOlRZBWF\nTUfx+L1DnkMw/PjlvjcLLJySGjreUxdofD3cLWYURaHlk4+oefQRFI+bpJu+TOJV1yCpxFepQPBF\nR3wLCM6IyD6KSg6hogAAIABJREFUz7ujiq1FHVuH7IzAV5vN8x8GrBAWps/lyry1eGQPzx55mZ21\ne1EUhQ92V+Dy+Hnho4DjetBrqrDxCJvbX0NtbsFvj+UbU28+Y5NGXaegarK7eeezgDB0dHSKJ0WN\nvzGdBmcjn1ZsOe04stuNp74eV2kpnppqfC02ZJer3xoxwdAI/o1m5yexdkHAKf+nX5nF7PxACldW\nZN4u+QCDWs/C9LnDNq8iyzSvf4P6555BUqtJv/sHxCxdPmzjCwSC0Y0w9hScEcEozzcu68PnR+VH\nl3sQFAlv2QRAQpa7RMbyzMVgT2Bd7XM8dehlnnmjGjD1GCI+yoCiKLxT+iEA7iOzkR3xpF+eypmi\n7baL8EiZjTXzs2nuljbyVuShTarkYNNhLsxeFjqvyDLtBwtw7N5F24F9yG1tfY6vjo4mcsZMzDNn\nYxxvEVGMYaK1LeBnFh2h4/LFuVw8b0yPRtfVbbW0eduZmzKTGH30qYYZNPXPPkXrpo2oo2PI/NH/\noktKGraxBQLB6EcIKsEZ4fEFvKKM+pM/SlevjebtWj/e6hy0zmTc+NH38qd6dn0NqpjJ6MfvxZd6\nAOyzwN8V9dJpVTx95CXK7BWkarMpdsQP29q7C6rg7rCmzv5+uWlRFFfbSTGkU9JaTru3A4Nbxv7Z\nNso+/gB3fWBnoDo6GtOkyWiio1GZIlA8HmSXE3+HE1dpMa2ffBzo55aSSvSSpUQvXY5KO7SaL0GA\n1vbA3yg6UodKknqIKYDDzVYA8uPyhmU+RZZDYkqXnkH6d74nWskIBIKTEIJKcEZ4vIF6Fl0vzyiv\n7KOwYwcAcksiPm9AeLW2ebA53MSa9SH/KrklEb8tEXVsA/qJnyHb41HcBnwNmbxe+jo7a/eSZc5g\nedxa/sVxzp+aNixrV0kSa+aP4e3tZfj8gchZMEKVlhBBcbWdTGMurbYyjjzwG6KL61B8PiSNhqgF\nC4lesgxDdg6Suu+iZ8Xvx3nMin37Vuzbt9Hw0gs0v7eBhEuvIGrR4s9txMrj9YfSqeGgK0KlP+m5\nFncrH5dvRkJiQtz4M57L73BQ9+xTtO3ZjTY5JdDkWIgpgUDQB0MSVBaLRQs8BWQDfuBrgA94ElCA\nQuBOq9UqrKY/5wQjVL1/QA80FFJmryCWdKrbuhzMC0uauefBrfzlzoX88F/bO89KeIpmoB17AE18\nLSpjwFFdm3WMHbWQZc7gm1NvIUpnJuuOBOJ6bY8/E1bNyeLt7WWhLfiNrS4kIDHagMHvZvqeBubu\naEKlgCYtnegFC8lZcyGt/v7/15HUakwTJmKaMJGEq67F9u47tGzaSN3T/8H2/rvErbkE89x5o15Y\n7T3WQHpCBMlxJvYea+Ch1wv58ZdmkJhoDst8DZ3u9rFRJwuq7dW7cXjbWJOz8oxr7Nr27aHh5Zfw\nNtSjS88g84c/Rh0R0f8LBQLBF5KhRqguBjRWq3WBxWJZCfwG0AI/tVqtn1osloeBy4DXh2mdgnMU\nj6/vCNWJlhIArhi/mgd3Vp70Omu5rdcZiXmRFzE9X4tP1cFzOzejMtlZMGYKl+RehK7TGiE5znTS\nWGdCMO3n9ckcLbNxrKKFCIOG6Npivlb+BoYSFx6zka0WNedf8xVy4i3o4szQ4BjUPJroaBKvu4GY\nC1bQuO41HJ9tp/bxf9N+6CBJ192I2hwe8RFuXt14grc7d3p+ZZWFJrsLWVHYWljLvGkZYZmzsdP3\nLLlbE2QIWCXsqtuHWlKzLHPRkMdXFAX7ti3UPfUfkGWil11A0vU3njISKRAIBDB0QXUM0FgsFhUQ\nBXiBecDGzuc3ABciBNXnHo+37whVqb0CjaQmNyYDCAgqS2YM1ooWADYdqD5prAlj4piWlgLArEun\nhnHVXWjVQUHl548v7ANFYUrNPlIK9yEj4Zq7DM1FUykoep7E5iImxFvObL6ERFJv/zpxq9dQ+9gj\nOD7bjru0lLTvfR9d4ugrci6v6yrIf/o9KwsnB/5+n+6rYsXcMaTFDF80MYjP3ynie33mnih8jrqO\neuamzMSoMfb10n6RvV6a1r2G7b0NSBoN6ff8EJMl/4zXLBAIPv8MNdfQRiDddxR4FPg7IFmt1uAW\nLgcwfNtrBOcs3j4iVK1uO1VtNWSY0zEbu35Qf3TTDH53R6Bh7NHylpPGmjZu5I0RVSoJtUrC65fJ\n0Lm5sep9ljbtw2+K5Nn0i+hYsIpxaRMxqA1srd5Jk7N3ZG1o6NMzyLz3p0QvWYantoayX/yUjmPW\nYRl7JInrlXbbWlgbOv7pw9uQZYWapnaOV7YiD5ONhL9zp2iwLREEdvYdtRWRF5PLlyZcM7Rx29up\n/Msfsb23AU1CAlk/v0+IKYFAMGCGGqH6PvCe1Wr9scViyQQ+Bro7LJqBk38xexEba0KjGZkwerjq\nOT5vDPo+SQEhlZYajckQSMs9ueU5/IqflXmLSE2J5r475pMYYyQx0UxCQiRmkzbkJTR3Ugq3XjKJ\n1IQIJEk65TThxKRWyKvcz3kl21HJfiKnT6d+wRqq3ysnIlJPeko8t8y4hn/teoa3K94lP+uOYfo8\nmUm661vUThhH8b8fp/JPvyfjqivIvOE6VJpzf79IcVUrG/efHGnsjk+l4ieP7gg9vuaCPL5y8cQz\nmlfd+Z2RlGjGZNDi9nn4y75XALh00gqSkwb/b7n2snIKf/YLfHY7cXNmk/uNr6GPH74dpf0hvp8G\njrhXA0Pcp4ExnPdpqN/aNgJpPoBmAvVT+ywWy1Kr1fopsBr4pN9BbB1DnH5wJCaaaRhkzcsXkaHc\nJ0fnFvbWlg7a1SpkRWZ/zSFSIpKZGjWVhgYHmXGB9Etw7DizISSorl06Fi0KjY19ezmFG+eJ41xX\n8hYJrmY8Gj0fx8/mG1+7nRJrwBbB1uKkocHBpMjJpJiS2FtdiM3Ziq9t+ArJNbMWkq43U//cM1S+\n8hp1m7aScvvXz/kmux/tKA0d33BBXsiMtTsHrcEWMQrarKO82fgpEXvXcH7m0A03Xa7AZ8fW3E67\nVs3Gym0U28qZnjiFbF3uoD/D9s+2UffUf1C8XuLWXkL82suwy5pB18kNFfH9NHDEvRoY4j4NjKHc\np9MJsKH+KjwAzLBYLJsJRKf+F7gTuM9isWwnEK16ZYhjC0YJPr9MWa2D+Ch9qM9eg7MJr+xjjDnj\nlBGn7mmiqIiz48nkrq6i8i9/ouJ3vybB1UyBeSzvzriOwrh8dDoNanVg7dWNgR2HkiQxL3UWXtnL\nHa/8gprW4Un9BYmYch6ZP/4pUYsW462vo+K3v6LyL3+ivbBgWOcZTjpcvtDxBTMzWDGzqwj95tWB\nVFmb04MqugH91I1oUspQ6V28XPQ6e+sD78vj9eP2+Ac1bzDlp1JJ1LTXsaHkQzQqDddZrkAlDe4r\nrWXTp9Q9+QSo1CTfcjsJl1+FNAqigwKB4NxjSN8cVqu1Dbi2j6eWnNlyBKOFp949yo7Ddbg8fuZ3\nFiJDoJYFIC0y5VQv7WF7oD4LlgEdR49Q+/i/8dls6DIyedY/nmJTGjRDlCmQTmpxBLyO3t9VwfUX\nBAwiV2Qt4b+bjqJNL+bBA4/xkwXfHnLxc19ooqNJufk2zLPm0PzuO3QcOUTHkUPos3OIXbGSiKnT\nURuHb74zpb5zt90/7lqMSiX1MG2NMKhQx1fzYvl29JZWFFnC15iK3JqIYewhnj78IqUnVLy1sZ7s\nFDM/v3n2SeN/tKeS0lo711+Qh1GnQdVZMxV021dJ8Mzhl3F427gk96JB2yTYP9tG/dNPIun1pH3r\n20RMmjzUWyEQCATC2FMweBpanD1qZyblxIWOC5uOAJAeeerWMBGGs/exaz98iOp//BXF6yXhqmuJ\nW30xxb//OPR8cOdYh7sr+rK9sJb5k1OQJAlf1TgkvRNbQg1/3fsIX514/WnF41CImDwF06TJuEtL\naFz3Gh1HDlP72L9RGY1EL1lG3Oo154QfUpvTi0YtYep0yV8yNY1P91WxZnkM6xueRzc2IK79rfH4\nqsYhd/qRnTchif2eD/nA9gqq2PGUNnpQFOWkiOZzHwT6Pm49WMtFc7K4dvm4wHiKgkqS+KRyC2WO\nCqYnTuGi7MH11LN9+D4NLz6PpNGQ+aP/xZA15ozuhUAgEIxuR0HBWSHoAxQkpdMbqs3Tzo6aPaRE\nJGOJHXfK1+vD6KJ9Ouw7PqPq/j+heL2kfus7xK2++KRrgr5axm7RlkffOtztChXekimM0eVT2VbN\nwwVPUmavGPa1SpKEISeXjO//D9m/+i1xay4BlQrbu+9Q8qN7aFr/BrLXM+zzDoYOlw+TXhMSQvHR\nBq68SsU7TS/Q4KnF15SCq2ARHuts5LZY5k9KBiBVlceyjEVIeif6vP0Ypn3K04f+i1f24XT72FZY\ng7OboAV4d2d56FiWFVSmNl47/hYRWhOXjL1oUOtuXPcqDS8+j9ocRcYPhZgSCATDgxBUgkHjcHp7\nPA5GKCocVSgoTEucfNpaFrV65D92LRs/ofaJR5H0BtK//z+YZ8wMPbdiVlftj8sT+CFfOj29x+vf\n3l6KEtz2r6iYpl/JxdkraHI186fd/+RES2nY1q5LSSHhiqvI/fNfSbjqWiSdjqY3Xqfk3h/Sfqgw\nbPP2R4fbh7FzZ6eiKLxd8gGvFL2JUWPg21Nv55Vv/BzFFUjDnT81lQVTUjuvhSmGxbgL5+OtGgt+\nDTvrd/Nk4Ys88OpuHnvrCE+/191CQkEytFHuqMTpc+H1+9GkBwrgb8q/mmTTwFrByB4PDa+8TPNb\n69HExZP2nbvO+cJ/gUAwehApP8Ggsbf3jIwEGyNXtgXSgBmRp++155dHtiORq6SYhheeQ6XXk/r1\nb51UK3PjivFoVCre3VlOUDP1bvb86sZi8jJiQo/dHh+X5F5IvDGOZ468zL76AsbGZIf1fai0WuJW\nX0z04vNpeutNWj76gKoH/kzsqtXEX35lWJouv/RxEe/trODbV05hxvgu4aIoCh0uL/Gd9XCbqz5j\nQ+mHROvM/GDWd4g1xKBSSeSkRlFSY2fZ9IxQ1MkvK9S3OFGcUfiqovDV5JA6fy/7GwtQ4o+gM0Sz\nx24GbTZfvmASr5S9AOYm/rBrCzqVDleSBpWxg0xzOlMSBmbB4O/ooPaxR2gvOIDKZCL9rnvQpw1P\nT0iBQCAAEaESDAF7R1eEKjvFHGrfUtVWA5y+fgogLz0gTC6cnRmmFXbhrqqi4o+/Q/H5SP7Kzacu\nPO4s31G6mU/etLJnc93Khi5rh4YWF4qiMDN5GlqVhoONh/HKPdNU4UIdGUnS9TeS+aP/RZuUjO29\nDZT97H9x7N7VY/3DwXs7A+nMf752kHWbi7GW2/j+P7ZwtMyGz68QYdDgl/28X/YJWpWG707/OrGG\nLuH5rcsnc9+tcxiTYg4VlftlBZs9YLcxY3wiyBpqPpseiFYpKtQxjWjTSjBM3cgrzf8EcxN+Rwy+\n+ky8fj8qYwey28C3p90+oF19stdL1d/up73gAIax48j57R+FmBIIBMOOiFAJBoWiKJyoagXgV7fN\nIS0hInS+3FGFXq0jwRh3uiEYlxHN3767iAhjeC0TPLU1VD/0dxSvl+Sv3oJ51pxTXpsYHYi0nDe2\ny639gpkZ7DhSx/HKwPsNWigAbDlYg0Gn5saV41mQNoeNldv4rGY3i9PnhendnIxxXB6ZP/4Jzevf\noOXTT6h5+EHM8xeQeM31aKKihn2+N7eW8ubWUgDuf/kAACaDhlePr8fmbmFx+nxSInq2z4mPNhC0\nx1R326VXXG8HYHpeAnuPNYBfi68qj9tmXs4jb+9HnVBNVGYtHqmVscaJFOxOAVmDt2I8ktaN4tUT\nubr/wnyf3U7lH3+Hp7aGyBkzSbntDlT6k5sqCwQCwZkiBJVgUFTUt3GkzMaEMbGkd3M3P9R0lLqO\neqYmTBpQ1MBs0vV7zZmg+P3U/PthvHV1xKy4kOjFp3f0WDw1DZ1WzZwJPQVBZmJkSFB9vLeqx3Mf\n7qnkxpXjWZqxiI2V2yiynRhRQQWgMUeRdOOXiblgJdUP/gPH9m24jheR/NVbMeVPOKOxe28+6E7Q\nCyomVmFT5XYSjfGszb3wtOMFI1Q+f0CUJ8YYmDsxmcffPhK6Zu7EZCobxhFlmsiKWRnIiozLI/Od\nTzd3TqxF8Wv5yqr+eyq6SkuoeeQhvA0NmOfOI/nLNwsxJRAIwoZI+QkGRXVTIEozdWx8j23uBzvt\nElaOWXo2ltUDxe+n8oE/4y4vwzxvPknX39jvazRqFQunpKLt1QpJqzn5f5Hp3WqJ3F4/icZ4IrUR\nFLeWnfnih4guOYWsn/yc2FWr8TY0UPnnP9C47lX8bUN3oD9Y0tzvNfqUwEaE5ZnnE6k9fcQoGKFq\nbHXS7vKRnRKFRq3iskU5gbE6d1ZetWQsK2dnIkkSapWaCIOWH1w/LTTOsunpJ20a6E1bwQGq/no/\n3oYGYpavIOX2r6MyDH+jZoFAIAgiBJVgUPz7zYCFQHx0T4PJmrY6JKR+C9LDjaIoNL25DufRIxjz\nJ5B045fOaDxXHy7eF8zOCh0fLbPxiyd2kaxPx+Zuwebqt4Vl2FDp9SRecx0ZP7gXtTmK5rfWU3bf\nz2j55OMh1VY1dEaoLJkxPc6vmR+wGdDENvBR5Sfo1DpmJJ/X73hBQVVa29mCqNMxf+WsDCZlx/L9\na6ae8rUTsuO457ppLJuezuWLc055neL3Y3v/Par/8Vf8bQ6SbvwSSTd+6az1iRQIBF8chKASDAhZ\nVnhza0nocV5mVwNaRVGoba8j0RiPVn12WskEsb23gea316OONJN6xzdRm87MALOsLvDjPy6j6/1G\nRei4dGE2AA+/eYjKhjZqywJeXB+Wbzyj+YYDkyWf7P/7LXFrL8XvcFD/3NNU/vF3tJ84PqhxgjVj\nd145hSfuXY6uM1p35fm5rFkRSfSEI6gkFXdOva3f6BR0pfxsjkBBemRnDZ3JoOWe66czvpdw682k\nnDi+vMpyynSxs+gYlX/5Iw0vv4Ck05H5o58Qs3zFwN6sQCAQnCFCUAkGxKaCatZtDgiqpdPTier2\no+bwttHu6yA1IvlsLQ+A+uefpfGVl1FFRJD5k58NS2H2lecHfIpuuCCP5TMCaabc9OhQ+5xgH7pY\nTx7xhli2Ve/E6/f2PdgIoo6MJOHyK8n5/Z8wTZqMs+gYVb/7Nbt+/mu8DYHGzwUnmthcUH3KMaoa\n2omO0IWEz5/vXMj9317IidZStrS9QYevg0tyVzEu5tQRox5rUvWMEs2ZMDyfF9nrofG1V6j48x9w\nHrNizBtP9q9+izEvb1jGFwgEgoEgitIFA6LB1lWg3DsFFLRLSDmLgqp162ZaPv4QbWIiKbd/HV1i\nUv8vGgBTcuN54t5AW5PsFDM3rhxPdKS+R4NnALPRgCVxCh9VbKKg8TAzk0+dvhpJNDGxZHz/f9i6\nfjPu994ko/o4J35yLylfuZm/b3YhS2oWTUk9KSXmdPtosruYMCY2dC7SqKXSUc3f9j2CrMjcNvlL\nzEjqP9UXRK/r+rpRq6SQh9VQURSFtt27aHz9Vbz1dahMEaTcfgcRU84TKT6BQDDiCEElGBCt3cw8\n87qlvwA2Vm4FOG27mXDSdmA/df95HEmjIe1b30WfGR5/K0mSgnZVxEb2FFRjUszMTJ3FRxWbeObI\nS6REJPXrxzWSPHXUjz99FVPtx1neuJv6Jx/nq7pY3k2aj9vrx6Dr+VVQ1LmzMTetK8onKzLvlHyA\nrMh8acK1gxJTAFGmrnRwQowxlAIcCq7yMmqfeAxPZQWSRkP0kqUkXnO9KDwXCARnDSGoBAOiuwdT\nXLfIgtfv5VCTlYzINMbHjh3xdblKiql76glQq8n4wb1hE1O96e2kLgFpkSlck3cZ/y16gw2lH3H7\n5DMriB8uOlxefH4ZJBX7o8dTZUhkUfMBLO3lfKlyA7ZtKaQsWdwjqnO03AZAflYgQuXwtPHfY29w\noPEQaREpzEuZ2edcp0OSJNbMH8ORMhvXLx9aOs7b2EDrlk00b3gH/H7Mc+YSf+kV6FKGt0G1QCAQ\nDBYhqAT90tLmDu3M+uUts3s8V9Neh6zI5ESPGfE0i9dmo+rBv+O320m45jqMY0cuQqbX9bRXkDt3\n0S3JWMC2mp3sqy/g5WNvcO34y0ZsTaciGF1MjjUye0ISb22D11OWYGkvZ23dFhzPPoG6tZnYNZeg\n1aixOdx8sq+KCIOGcenRWJuP81jhM3T4nKSYkvjGebcM+W991ZLBi27Z66XjyGFaN31Ke8EBkGXU\nMTGk3HL7qZ3vBQKBYIQRgkrQL5X1AS+jBZNTyEo293xugO1mhhtvUxPl//dL/G0O4i+/krhVq0d0\nfr22p6AKuhJIksRXJ17Pg/sfZ2PlVpZmLCTJlNDHCCOHo7NV0Kz8JGqbOgInJQlr5BiatVHcZt9C\ny/p17NxSSNm8Syita8OttLNiXgaba7fwxokNSEhcMW4NS9IXjNhOTq/Nhr2zNs5vDzir69LSiFlx\nIeZZc1CbTCOyDoFAIBgIQlAJ+sXtDexkG9NLTAFUhRoij5ygcldXU/PQP/C3OYhbewlxF68dsbmD\naNQ9N8jKcpfPU3pkKpeNXc3TR17iJevrfGvqrahV6t5DjBguT6DHoEGnZlZ+ErutDaHnGvSxKDd8\njfonHmW87TgRG5+kZE4ixvwWPu4AjkOE1sQdU7464N18Z4K/rY3WzRtx7N6Fu6wUAJXRGBBRc+Zh\nzM0N+xoEAoFgKAhBJeiXoKDqneby+L0UNh1FJalIGyFB5Sw+Qc3DD+FrbiJ6yVLiL7vyrO3oys+K\nweH0UtXQHkr5AZ1Nk6eyvWYXR21FFDYdYWri2UtNeX0yADqNmtn5SUiShL3dQ0OLk/d3VWAzxvF8\n5gqusL1LdrONmz5rZePkOOIWzyEpIp65KTN7NDwebhSfj45jVhzbt2HfsR1kGdRqTBMmETFtGlEL\nFqE2GvsfSCAQCM4iQlAJ+sXt7fxB1vaMyuyu20ejs4mlGQvRq8Pcm09RsG/bSv0zT6L4fMRfejnx\nl14e1jn744c3zuB4VSu/fWZPSFBtKajhuQ+O8YtbZnPt+Mv5zc772VS5/ZwQVFqNCkmSmJ0fsJRY\nv60UgIbWduSxRbwRb2BWgYo5hx1cvLuRCH8tiVcvQTfMYkqRZTzVVTiPF9Fx5DAdhw8hOwO2HNqU\nFKIXnk/0kqUipScQCEYVQlAJ+iVoXtm7bshqCzhvj0RD4KY319G8/o2ANcKd3yVy+oywzzkQVJ3R\nMUUOiL4n3gn0NDxW0cL5U9PIi8nlqK2IXbX7mJ0y/ayssbug6o5WrQIUdnd8hCahGrnDzGbPfLKu\nimXM9jdp37eX9v37iJhyHuY5c4mcNh2VYXCRItnlwmdrxmuz4ampxmk9SscxK3K3HoOa2FjM8+Zj\nnj0X47g8JJXwGxYIBKMPIagE/dLmDBQ1Bx2zISAejreUYNZGkmwaHhPNvlAUhbqnnsC+ZTOauHjS\n77oHfdrZ7RfYneBvv6wo2DtOdki/Mf9q7vvsj3xWs/vsCSp/34LK6XWin7yNRpUDucPM8qir0S8y\nsGx+NtKqmTh27qDlw/dpLzgQ2F0nSWjjE1BHR6M2m9ElJ6NLTUNlMAaEU4sNb1MjvuZmfDYbJ1pt\n+Ns7TlqPJi6OiPkLMI4dh2niZLSJicKIUyAQjHqEoBL0i71z231URFda73hLCS3uVqYnhc+VWpFl\nGl95GfuWzejSM0j7xrfQpZ47Ygq6IlSyouDoZn7a2hboV5dkSiA9MpXjrSV4/B50YU6N9uav/z1A\nwYkmIBiR6mJb06eozA78rfF4iqeQdmEMC6d01cJFzZ2Hec5cPJWVOPbswll0DE9dLd7SEvD7aefU\nqEwRGBITICcGbVwsmtg4tPEJGPLy0CYIASUQCD5/CEEl6JcmuwuAmG7u4MGt9MsyFoVlTp/DTu3j\nj9FRWIA2JYX0734fbXx8WOY6E6RuKT9HR5eg2nGknksWBnbFTYyzUNVWw47aPSxOn09DixOtRtXj\nfvamrNZBhEFDQszQi7HrbR0hMQU9NxXsrS+gw3wC2WXCc2wGKGrSEk5ucCxJEvrMzB6GqYqiILe3\n46mpxlNTg+z1oNLp0MTGoomNRxsfj8pgIDHRTEODY8jrFwgEgtGEEFSC09Lh8lJaaych2hCqofL6\nvZQ7KskyZzA2JnvY55Tdbqr+9gDu0hKM4y2kffu7qE0n/9ifCwS7p8iKgsPZlfKrbmynvsVJUoyR\neamz2FS1jVeL3iLCNYZ//vcoGYmR/Oq2OX2O6XT7uO/JXQChPoJD4cDxph6Pk2MDRd5+2c+mym0A\neIqmg6JGo1aRkzqwZtKSJKGOjMSYNx5j3vghr08gEAg+T4jqT8FpeXNrKU63nyXTulJtFW3V+BU/\n2dHD3+bF39FO2f/9AndpCeY588i4+wfnrJgCQv3oPtlXxSNvHAJAow6c+8NzewFIiUhiZdYyvLKX\nT4p3A1DZ0Bbyh+rNcx8cG5a1VTW29XgcbOj8n8MvUNRSzPiYsaSYAg2tLVnhs0UQCASCLwJCUAlO\nSZvTy/u7KgCYnpcYOl9qLwcgOyprWOfzOxzU/OtBvLW1mOfOJ/mrtyBpzu0gqqpbLVDQier2tROB\nQApQ6bRTmNNZkH5CtQUpogXoKvbvjdPdJbQ+6Lz/Q2FbYW2Px5Ik0eJuZX/9QdIjU7l18k2YOnsS\nBncCCgQCgWBoCEElOCXW8pbQcXJcoJbH4/ewsWIrEhJjo7OHbS7Z46H6kYfoOHIYoyWflFtuQ6U/\ndY3RuYKkOrm4eqYlkQljYvH5FaoaAqXb8cY4cpiDJIFubAGqmHpq7c19jllvc4aOX/yoCAB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e6phLhOxsH4W4ib+Dre+EacNi+pDeP4xjV3Eu+PY8vq1ymrcq/wy5tz6mDmwpxk8jITOVTZwGMv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\nUkElIiIi0kP/H4edqSNKzd7OAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1130305f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2010-12-31    True\n",
       "2011-01-03    True\n",
       "2011-01-04    True\n",
       "2011-01-05    True\n",
       "2011-01-06    True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data['SMA1'] > data['SMA2']).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Position'] = np.where(data['SMA1'] > data['SMA2'], 1, -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Sxph3hVDNeeNTSdLQmLdUVwYuaUDqcCKpw3tUORpzXVzuRB1ZomoycEmSSlfD\nqY7S3Ri4pD7V8TziyVO9ctJ8cR5n1WLgkiQNjXeaV10ZuCRJpbO3RnVn4JJUnN0T6lGjloPvPfI4\nqyQDlzQofkhKHXmYqK4MXFKfHCqROmscviuEiUv1ZOCSJA2PeUs1ZeCSJA2NeUt1ZeCSVJgnS/Wq\n4dh7YR5n1WTgkgbED0lpcYfjlgeKasrAJUkaGifNq64MXJK65vCQuuZvV3fNw6xaDFySpNKZHVR3\nBi5JUvkadnGp3gxc0oDU4Q7adXiPKsdcD5e7UGceZ9Vk4JIkDY9pQjVl4JL6VMcJ5PV7x+qXI4rd\n8we/q8XAJUmSVDIDlySpdHM9wY4oqq4MXNLA1OFMUof3qHK5D6meDFySpNId/paieUs1ZeCS+lTL\naa21fNPqi/tM96xZpUz08+KI+G/AmZl51gLrzgNeABwA3piZ/xgRxwCXAWuBm4BzMnO2nzZIkpY/\n78Oluuu5hysiLgLevNC/ERHHAucDjwWeBLw5IlYDrwUuy8zHAdfTDGSSpKrzvhCquX56uL4I/AML\nh6ZHA1sycy+wNyK2Ag8DTgLe1HrOFa3H7+yjDdKycdOts3z+Kz8AYMPkGnbO7BlxiwbvplvtkFZ/\nfnTbrsPHyaBV5bi7fWbvqJugEnQMXBHxPOCl8xafk5kfjYiTF3nZkcD2tr9ngI3zls8tW9SmTeuY\nmFjRqYkDMTU1OZTtjDvrdE8Tq1cCsPWH29n6w+0dnj3+Gg2493Eb2TS5ZiD/nvtUMeNep1VrV9Fo\nwLdv2sG3b9ox6uYse2tXT3CvqclSb6w87vvUsAyqTh0DV2ZeDFzc5b+7A2hv4SRwR9vy3W3LFrVt\n23CupqemJpmenhnKtsaZdVrcK591PLe3XVkfObmWHTO7R9ii8myeXMOBPfuZ3rO/73/LfaqYqtTp\nlc86ntt2lNcDVaXj7rij13PrrTtL+/ersk+Vrds6LRXO+po0v4TrgD+NiDXAauAhwNeALcAZwIeA\n04GrS9q+NFQPvM9G2jts/TCT7ukB997IA+695MBGXzzutJwN9LYQEXFBRDwtM28G3kUzUF0FvCoz\n9wBvBJ4ZEVuAE4H3DHL7kiRJy1Hj0DK+C9309MxQGudVUTHWqThrVYx1KsY6FWOdirNWxfQwpLjo\npDtvfCpJklQyA5ckSVLJDFySJEklM3BJkiSVzMAlSZJUMgOXJElSyQxckiRJJTNwSZIklczAJUmS\nVLJlfad5SZKkKrCHS5IkqWQGLkmSpJIZuCRJkkpm4JIkSSqZgUuSJKlkBi5JkioqIhqjboOaDFyS\nhiIi/LxZQkSsjYg1o27HcueFwvfmAAAIfklEQVR+VFxEHAUcPep2qKnSO+5cso+IJ0TEGe3LdE8R\ncX5EvCYifmXUbVnuIuLciHh2RPzUqNuynEXE0yLiz0bdjuUuIl4CXAw8eNRtWc4i4o+At0TEY0bd\nluUuIp4LfBV42qjbspxFxHkR8dyIOK7sbVU6cGXm3F1dXwycHhFHtS1TS0RsiogrgJ8HvgW8MiIe\nO+JmLUsRsTEiPgv8MhDASyLi2BE3azl7FPCiiHhwZt4ZEROjbtByEhE/GRHfAe4FvCgz/7NtnReH\nLRGxPiIuBY

99_day_2_exercises.ipynb

btc_usd.csv

mvp_class.py

Titanic.csv