Backtesting_a _Trading_Strategy_Chapter_7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantitative Trading Strategies Using Python\n",
    "## Technical Analysis, Statistical Testing,and Machine Learning\n",
    "—\n",
    "### Peng Liu"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#######################################################################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CHAPTER 7\n",
    "## Backtesting a Trading Strategy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the Max Drawdown"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Downloading the stock price data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: yfinance in ./Library/Python/3.9/lib/python/site-packages (0.2.40)\n",
      "Requirement already satisfied: pandas>=1.3.0 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (2.2.0)\n",
      "Requirement already satisfied: numpy>=1.16.5 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (1.26.2)\n",
      "Requirement already satisfied: requests>=2.31 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (2.31.0)\n",
      "Requirement already satisfied: multitasking>=0.0.7 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (0.0.11)\n",
      "Requirement already satisfied: lxml>=4.9.1 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (5.2.2)\n",
      "Requirement already satisfied: platformdirs>=2.0.0 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (3.5.1)\n",
      "Requirement already satisfied: pytz>=2022.5 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (2023.3.post1)\n",
      "Requirement already satisfied: frozendict>=2.3.4 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (2.4.4)\n",
      "Requirement already satisfied: peewee>=3.16.2 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (3.17.5)\n",
      "Requirement already satisfied: beautifulsoup4>=4.11.1 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (4.12.3)\n",
      "Requirement already satisfied: html5lib>=1.1 in ./Library/Python/3.9/lib/python/site-packages (from yfinance) (1.1)\n",
      "Requirement already satisfied: soupsieve>1.2 in ./Library/Python/3.9/lib/python/site-packages (from beautifulsoup4>=4.11.1->yfinance) (2.5)\n",
      "Requirement already satisfied: six>=1.9 in /Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/site-packages (from html5lib>=1.1->yfinance) (1.15.0)\n",
      "Requirement already satisfied: webencodings in ./Library/Python/3.9/lib/python/site-packages (from html5lib>=1.1->yfinance) (0.5.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in ./Library/Python/3.9/lib/python/site-packages (from pandas>=1.3.0->yfinance) (2.8.2)\n",
      "Requirement already satisfied: tzdata>=2022.7 in ./Library/Python/3.9/lib/python/site-packages (from pandas>=1.3.0->yfinance) (2023.4)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in ./Library/Python/3.9/lib/python/site-packages (from requests>=2.31->yfinance) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in ./Library/Python/3.9/lib/python/site-packages (from requests>=2.31->yfinance) (3.6)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in ./Library/Python/3.9/lib/python/site-packages (from requests>=2.31->yfinance) (1.26.19)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in ./Library/Python/3.9/lib/python/site-packages (from requests>=2.31->yfinance) (2023.11.17)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1.2\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49m/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install botorch\n",
    "!pip install -U statsmodels\n",
    "!pip install ta\n",
    "!pip install yfinance\n",
    "from botorch.acquisition import ExpectedImprovement\n",
    "from botorch.acquisition import qExpectedImprovement\n",
    "from botorch.acquisition import UpperConfidenceBound\n",
    "from botorch.acquisition.knowledge_gradient import qKnowledgeGradient\n",
    "from botorch.fit import fit_gpytorch_mll\n",
    "from bs4 import BeautifulSoup\n",
    "from datetime import datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "from itertools import combinations\n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "import random\n",
    "import requests\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "from statsmodels.regression.linear_model import OLS\n",
    "import statsmodels.api as sm\n",
    "import ta\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import yfinance as yf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  2 of 2 completed\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>Price</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Adj Close</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Close</th>\n",
       "      <th colspan=\"2\" halign=\"left\">High</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Low</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Open</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</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>2023-01-03</th>\n",
       "      <td>89.598038</td>\n",
       "      <td>236.609238</td>\n",
       "      <td>89.699997</td>\n",
       "      <td>239.580002</td>\n",
       "      <td>91.550003</td>\n",
       "      <td>245.750000</td>\n",
       "      <td>89.019997</td>\n",
       "      <td>237.399994</td>\n",
       "      <td>89.830002</td>\n",
       "      <td>243.080002</td>\n",
       "      <td>20738500</td>\n",
       "      <td>25740000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>88.609169</td>\n",
       "      <td>226.259186</td>\n",
       "      <td>88.709999</td>\n",
       "      <td>229.100006</td>\n",
       "      <td>91.239998</td>\n",
       "      <td>232.869995</td>\n",
       "      <td>87.800003</td>\n",
       "      <td>225.960007</td>\n",
       "      <td>91.010002</td>\n",
       "      <td>232.279999</td>\n",
       "      <td>27046500</td>\n",
       "      <td>50623400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>86.671371</td>\n",
       "      <td>219.553360</td>\n",
       "      <td>86.769997</td>\n",
       "      <td>222.309998</td>\n",
       "      <td>88.209999</td>\n",
       "      <td>227.550003</td>\n",
       "      <td>86.559998</td>\n",
       "      <td>221.759995</td>\n",
       "      <td>88.070000</td>\n",
       "      <td>227.199997</td>\n",
       "      <td>23136100</td>\n",
       "      <td>39585600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>88.059799</td>\n",
       "      <td>222.140869</td>\n",
       "      <td>88.160004</td>\n",
       "      <td>224.929993</td>\n",
       "      <td>88.470001</td>\n",
       "      <td>225.759995</td>\n",
       "      <td>85.570000</td>\n",
       "      <td>219.350006</td>\n",
       "      <td>87.360001</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>26612600</td>\n",
       "      <td>43613600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>88.699066</td>\n",
       "      <td>224.303726</td>\n",
       "      <td>88.800003</td>\n",
       "      <td>227.119995</td>\n",
       "      <td>90.830002</td>\n",
       "      <td>231.240005</td>\n",
       "      <td>88.580002</td>\n",
       "      <td>226.410004</td>\n",
       "      <td>89.195000</td>\n",
       "      <td>226.449997</td>\n",
       "      <td>22996700</td>\n",
       "      <td>27369800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Price       Adj Close                  Close                   High  \\\n",
       "Ticker           GOOG        MSFT       GOOG        MSFT       GOOG   \n",
       "Date                                                                  \n",
       "2023-01-03  89.598038  236.609238  89.699997  239.580002  91.550003   \n",
       "2023-01-04  88.609169  226.259186  88.709999  229.100006  91.239998   \n",
       "2023-01-05  86.671371  219.553360  86.769997  222.309998  88.209999   \n",
       "2023-01-06  88.059799  222.140869  88.160004  224.929993  88.470001   \n",
       "2023-01-09  88.699066  224.303726  88.800003  227.119995  90.830002   \n",
       "\n",
       "Price                         Low                   Open              \\\n",
       "Ticker            MSFT       GOOG        MSFT       GOOG        MSFT   \n",
       "Date                                                                   \n",
       "2023-01-03  245.750000  89.019997  237.399994  89.830002  243.080002   \n",
       "2023-01-04  232.869995  87.800003  225.960007  91.010002  232.279999   \n",
       "2023-01-05  227.550003  86.559998  221.759995  88.070000  227.199997   \n",
       "2023-01-06  225.759995  85.570000  219.350006  87.360001  223.000000   \n",
       "2023-01-09  231.240005  88.580002  226.410004  89.195000  226.449997   \n",
       "\n",
       "Price         Volume            \n",
       "Ticker          GOOG      MSFT  \n",
       "Date                            \n",
       "2023-01-03  20738500  25740000  \n",
       "2023-01-04  27046500  50623400  \n",
       "2023-01-05  23136100  39585600  \n",
       "2023-01-06  26612600  43613600  \n",
       "2023-01-09  22996700  27369800  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_date = \"2023-01-01\"\n",
    "end_date = \"2023-02-11\"\n",
    "df = yf.download(['GOOG', 'MSFT'], start=start_date, end=end_date)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df['Adj Close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2023-01-03', '2023-01-04', '2023-01-05', '2023-01-06',\n",
       "               '2023-01-09', '2023-01-10', '2023-01-11', '2023-01-12',\n",
       "               '2023-01-13', '2023-01-17', '2023-01-18', '2023-01-19',\n",
       "               '2023-01-20', '2023-01-23', '2023-01-24', '2023-01-25',\n",
       "               '2023-01-26', '2023-01-27', '2023-01-30', '2023-01-31',\n",
       "               '2023-02-01', '2023-02-02', '2023-02-03', '2023-02-06',\n",
       "               '2023-02-07', '2023-02-08', '2023-02-09', '2023-02-10'],\n",
       "              dtype='datetime64[ns]', name='Date', freq=None)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-02-01</th>\n",
       "      <td>101.314713</td>\n",
       "      <td>249.615936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-02</th>\n",
       "      <td>108.676331</td>\n",
       "      <td>261.318970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-03</th>\n",
       "      <td>105.100403</td>\n",
       "      <td>255.146469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-06</th>\n",
       "      <td>103.352394</td>\n",
       "      <td>253.586029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-07</th>\n",
       "      <td>107.917198</td>\n",
       "      <td>264.242310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-08</th>\n",
       "      <td>99.886337</td>\n",
       "      <td>263.422546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-09</th>\n",
       "      <td>95.351494</td>\n",
       "      <td>260.351074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-10</th>\n",
       "      <td>94.752174</td>\n",
       "      <td>259.837585</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker            GOOG        MSFT\n",
       "Date                              \n",
       "2023-02-01  101.314713  249.615936\n",
       "2023-02-02  108.676331  261.318970\n",
       "2023-02-03  105.100403  255.146469\n",
       "2023-02-06  103.352394  253.586029\n",
       "2023-02-07  107.917198  264.242310\n",
       "2023-02-08   99.886337  263.422546\n",
       "2023-02-09   95.351494  260.351074\n",
       "2023-02-10   94.752174  259.837585"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.loc[\"2023-02\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 28 entries, 2023-01-03 to 2023-02-10\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   GOOG    28 non-null     float64\n",
      " 1   MSFT    28 non-null     float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 672.0 bytes\n"
     ]
    }
   ],
   "source": [
    "df2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>-0.011037</td>\n",
       "      <td>-0.043743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>-0.021869</td>\n",
       "      <td>-0.029638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>0.016019</td>\n",
       "      <td>0.011785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>0.007259</td>\n",
       "      <td>0.009736</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker          GOOG      MSFT\n",
       "Date                          \n",
       "2023-01-03       NaN       NaN\n",
       "2023-01-04 -0.011037 -0.043743\n",
       "2023-01-05 -0.021869 -0.029638\n",
       "2023-01-06  0.016019  0.011785\n",
       "2023-01-09  0.007259  0.009736"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns_df = df2.pct_change()\n",
    "returns_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "returns_df.plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Constructing the wealth curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>988.963277</td>\n",
       "      <td>956.256772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>967.335599</td>\n",
       "      <td>927.915419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>982.831783</td>\n",
       "      <td>938.851210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>989.966616</td>\n",
       "      <td>947.992261</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker            GOOG        MSFT\n",
       "Date                              \n",
       "2023-01-03         NaN         NaN\n",
       "2023-01-04  988.963277  956.256772\n",
       "2023-01-05  967.335599  927.915419\n",
       "2023-01-06  982.831783  938.851210\n",
       "2023-01-09  989.966616  947.992261"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "initial_wealth = 1000\n",
    "wealth_index_df = initial_wealth*(1+returns_df).cumprod()\n",
    "wealth_index_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>988.963277</td>\n",
       "      <td>956.256772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>967.335599</td>\n",
       "      <td>927.915419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>982.831783</td>\n",
       "      <td>938.851210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>989.966616</td>\n",
       "      <td>947.992261</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker             GOOG         MSFT\n",
       "Date                                \n",
       "2023-01-03  1000.000000  1000.000000\n",
       "2023-01-04   988.963277   956.256772\n",
       "2023-01-05   967.335599   927.915419\n",
       "2023-01-06   982.831783   938.851210\n",
       "2023-01-09   989.966616   947.992261"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wealth_index_df.loc[\"2023-01-03\"] = initial_wealth\n",
    "wealth_index_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wealth_index_df.plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Constructing the cumulative maximum wealth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker        GOOG    MSFT\n",
       "Date                      \n",
       "2023-01-03  1000.0  1000.0\n",
       "2023-01-04  1000.0  1000.0\n",
       "2023-01-05  1000.0  1000.0\n",
       "2023-01-06  1000.0  1000.0\n",
       "2023-01-09  1000.0  1000.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prior_peaks_df = wealth_index_df.cummax()\n",
    "prior_peaks_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjAAAAGrCAYAAADeuK1yAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAABUdklEQVR4nO3deXyM1/4H8M9M9j2yCwmxprYISmOvqlhbpa2g1pZqUWu5rlJ0UdraenuLWxrt5dLeKqo/LrFUSxprrBFrBNlIJCPbJDNzfn+MGRkJEmbyzPJ5v17zysw8T2a+cybJfHKec84jE0IIEBEREVkQudQFEBEREVUVAwwRERFZHAYYIiIisjgMMERERGRxGGCIiIjI4jDAEBERkcVhgCEiIiKLYy91Aaai0WiQlpYGDw8PyGQyqcshIiKiShBC4O7duwgODoZc/vB+FqsNMGlpaQgJCZG6DCIiInoC169fR+3atR+63WoDjIeHBwBtA3h6ekpcDREREVWGQqFASEiI/nP8Yaw2wOgOG3l6ejLAEBERWZjHDf/gIF4iIiKyOAwwREREZHEYYIiIiMjiWO0YmMpSq9UoLS2Vugyr5uDgADs7O6nLICIiK2KzAUYIgYyMDOTm5kpdik3w9vZGUFAQ1+QhIiKjsNkAowsvAQEBcHV15QeriQghUFhYiKysLABAzZo1Ja6IiIisgU0GGLVarQ8vvr6+Updj9VxcXAAAWVlZCAgI4OEkIiJ6ajY5iFc35sXV1VXiSmyHrq053oiIiIzBJgOMDg8bVR+2NRERGZNNBxgiIiKyTDY5BsbcjBw5Erm5udiyZctj901JSUFYWBhOnDiBli1bmrw2IiJzptEIqUuwaTKZdD3sDDAm9rg39sMPP8Ty5cshBH8JiYiqYk9SJiZsOIGiUrXUpdisGT0b492uDSR5bgYYE0tPT9df37RpE+bOnYvk5GT9fe7u7nB3d5eiNL3S0lI4ODhIWgMRUVXFJWUyvNgwBhgTCwoK0l/38vKCTCYzuA8ofwhJo9Hgiy++wOrVq3H9+nUEBgbi7bffxuzZs8s9vlqtxpgxY3Do0CHs2rULoaGh2Lp1K+bPn49z584hODgYI0aMwOzZs2Fvr327ZTIZ/vnPf2LHjh3Ys2cP3n//fcybN89kbUBEZAoZecUAgDl9m2BAZC2Jq7FNLo7SLYvBAGOGZs2ahX/9619YunQpOnbsiPT0dJw/f77cfkqlEoMHD0ZKSgr++OMP+Pv7448//sDw4cOxYsUKdOrUCZcvX8bYsWMBaA9X6cybNw+fffYZli1bpg82RESWJFOhBADU83NDDTdHiauh6sZPLjNz9+5dLF++HP/4xz8wYsQIAED9+vXRsWNHg/3y8/PRp08fKJVK7Nu3D15eXgCA+fPn429/+5v+e+vVq4ePPvoIM2bMMAgwQ4YMwahRo6rpVRERGV+mQtsDE+jpLHElJAUGGDOTlJQEpVKJF1544ZH7DR48GLVr18bevXv1K90CwMmTJ3Hw4EF88skn+vvUajWKi4tRWFioX1CuTZs2pnkBRETVoESlQXZBCQAg0NNJ4mpICgwwZqZsGHmU3r1749///jfi4+PRrVs3/f35+fmYP38+BgwYUO57nJ3v/5fi5ub29MUSEUkk666298XBTgYfHj6ySQwwZqZhw4ZwcXHBnj178NZbbz10v3feeQfNmjXDSy+9hN9++w1dunQBALRq1QrJyclo0ECaaW1ERNVBN/4lwMOZK33bKAYYM+Ps7IyZM2dixowZcHR0RIcOHXDr1i2cPXsWb775psG+EydOhFqtRt++fbFjxw507NgRc+fORd++fREaGopXX30VcrkcJ0+exJkzZ/Dxxx9L9KqIiIxLN/4lyIvjX2wVA4wZmjNnDuzt7TF37lykpaWhZs2aGDduXIX7Tp48GRqNBr1798bOnTsRHR2N7du3Y8GCBVi0aBEcHBwQHh7+yN4cIiJLc38AL8e/2CqZsNIlYBUKBby8vJCXlwdPT0+DbcXFxbh69SrCwsIMxoWQ6bDNiciYFu5Iwqrfr2BUh7r4sF9TqcshI3rU53dZPJkjERFZnKx7Y2A4hdp2McAQEZHF0a3CG8QAY7MYYIiIyOJk3ptGHcAxMDaLAYaIiCxOJntgbF6VA8yBAwfQr18/BAcHQyaT6U9ACGjPajxz5kw0b94cbm5uCA4OxvDhw5GWlmbwGDk5ORg6dCg8PT3h7e2NN998E/n5+Qb7nDp1Cp06dYKzszNCQkKwePHiJ3uFRERkVfKVKhSUaM9CzTEwtqvKAaagoAARERH4+uuvy20rLCzE8ePHMWfOHBw/fhybN29GcnIyXnrpJYP9hg4dirNnz2L37t3Yvn07Dhw4oD/hIKAdgdyjRw/UqVMHx44dw+eff4558+Zh9erVT/ASiYjImujGv3g42cPNiauB2Koqv/O9evVCr169Ktzm5eWF3bt3G9z3j3/8A23btkVqaipCQ0ORlJSEnTt34siRI/rz8Xz11Vfo3bs3vvjiCwQHB2P9+vUoKSnB2rVr4ejoiKZNmyIxMRFLliwxCDpERGR7snRrwHARO5tm8jEweXl5kMlk8Pb2BgDEx8fD29vb4GSC3bt3h1wuR0JCgn6fzp07w9Hx/vktoqOjkZycjDt37lT4PEqlEgqFwuBCRETWJ4OL2BFMHGCKi4sxc+ZMDB48WL8YTUZGBgICAgz2s7e3h4+PDzIyMvT7BAYGGuyju63b50ELFy6El5eX/hISEmLsl0NERGbgfoBhD4wtM1mAKS0txeuvvw4hBL755htTPY3erFmzkJeXp79cv37d5M9JRETVj4vYEWCiAKMLL9euXcPu3bsNlgIOCgpCVlaWwf4qlQo5OTkICgrS75OZmWmwj+62bp8HOTk5wdPT0+BirTIyMjBp0iQ0aNAAzs7OCAwMRIcOHfDNN9+gsLBQv9+hQ4fQu3dv1KhRA87OzmjevDmWLFkCtVpd7jG3b9+OLl26wMPDA66urnj22WcRGxtb4fP//PPP6NatG2rUqAEXFxc0btwYo0ePxokTJ0z1komI9LiIHQEmCDC68HLx4kXExcXB19fXYHtUVBRyc3Nx7Ngx/X179+6FRqNBu3bt9PscOHAApaWl+n12796Nxo0bo0aNGsYu2aJcuXIFkZGR2LVrFz799FOcOHEC8fHxmDFjBrZv3464uDgAwC+//IIuXbqgdu3a2LdvH86fP49Jkybh448/RkxMDMqeAuurr77Cyy+/jA4dOiAhIQGnTp1CTEwMxo0bh+nTpxs8/8yZMzFo0CC0bNkS27ZtQ3JyMjZs2IB69eph1qxZ1doWRGSbdIvYcQyMjRNVdPfuXXHixAlx4sQJAUAsWbJEnDhxQly7dk2UlJSIl156SdSuXVskJiaK9PR0/UWpVOofo2fPniIyMlIkJCSIP//8UzRs2FAMHjxYvz03N1cEBgaKYcOGiTNnzoiNGzcKV1dXsWrVqkrXmZeXJwCIvLy8ctuKiorEuXPnRFFRUVVfvuSio6NF7dq1RX5+foXbNRqNyM/PF76+vmLAgAHltm/btk0AEBs3bhRCCJGamiocHBzE1KlTy+27YsUKAUD89ddfQggh4uPjBQCxfPnyhz73w1hymxOReYn6NE7UmbldHL+WI3UpZAKP+vwuq8oBZt++fQJAucuIESPE1atXK9wGQOzbt0//GNnZ2WLw4MHC3d1deHp6ilGjRom7d+8aPM/JkydFx44dhZOTk6hVq5b47LPPqlRnVQKMRqMRBcpSSS6P+tB/0O3bt4VMJhMLFy585H6bN28WAMShQ4cq3N6oUSPx8ssvCyGEWLJkiQAg0tLSyu2nVCqFu7u7mDRpkhBCiPfee0+4u7uL0tLSSteswwBDRMagVmtE/Vm/iTozt4ubdwqlLodMoLIBpsrrwHTt2tXg8EMFPTqPfQwfHx9s2LDhkfu0aNECf/zxR1XLeyJFpWo0mfu/anmuB51bEA1Xx8q9DZcuXYIQAo0bNza438/PD8XF2i7V8ePHw8fHBwDwzDPPVPg44eHhuHDhAgDgwoUL8PLyQs2aNcvt5+joiHr16hnsW69ePdjb3693yZIlmDt3rv72zZs34eXlVanXQ0RUVdkFJVBpBGQywN+Dh5BsGc+FZAUOHz6MxMRENG3aFEqlUn9/ZcLk0xo9ejQSExOxatUqFBQUVMtzEpHtyrw3hdrXzQkOdvwIs2VcgxmAi4Mdzi2Iluy5K6tBgwaQyWRITk42uL9evXrax3JxAQA0atQIAJCUlIT27duXe5ykpCQ0adJEv29eXh7S0tIQHBxssF9JSQkuX76M559/HgDQsGFD/PnnnygtLYWDgwMAwNvbG97e3rhx40alXwcR0ZPSBZggL/a+2DrGVwAymQyujvaSXGQyWaXr9PX1xYsvvoh//OMfKCgoeOh+PXr0gI+PD7788sty27Zt24aLFy9i8ODBAICBAwfCwcGhwn1XrlyJgoIC/b6DBw9Gfn4+/vnPf1a6ZiIiY8rUrQHjwSnUto49MBbmn//8Jzp06IA2bdpg3rx5aNGiBeRyOY4cOYLz58+jdevWcHNzw6pVqxATE4OxY8diwoQJ8PT0xJ49e/D+++/j1Vdfxeuvvw4ACA0NxeLFizFt2jQ4Oztj2LBhcHBwwNatW/H3v/8d06ZNM5jePm3aNEybNg3Xrl3DgAEDEBISgvT0dKxZswYymQxyOTMxEZlOBs+DRPcwwFiY+vXr48SJE/j0008xa9Ys3LhxA05OTmjSpAmmT5+Od999FwDw6quvYt++ffjkk0/QqVMnFBcXo2HDhpg9ezYmT55s0PMzefJk1KtXD1988QWWL18OtVqNpk2b4ptvvsGoUaMMnv+LL75A27Zt8c0332Dt2rUoLCxEYGAgOnfujPj4eKteQJCIpKc/kSN7YGyeTFjpqEuFQgEvLy/k5eWV+1AtLi7G1atXERYWBmdn/hJUB7Y5ERnDyO8OY3/yLSwa2ByDng2VuhwygUd9fpfF/n4iIrIYujEwATyNgM1jgCEiIouhn4XEAGPzGGCIiMgiKFVq5BSUAGCAIQYYIiKyEFn3Dh852svh7eogcTUkNQYYIiKyCLrDR4GeTlVaQ4usEwMMERFZBC5iR2UxwBARkUXgInZUFgMMERFZBC5iR2UxwBARkUXI4IkcqQwGGCIisgj3B/GyB4YYYCzOyJEjIZPJMG7cuHLbxo8fD5lMhpEjRwIAbt26hXfeeQehoaFwcnJCUFAQoqOjcfDgQf331K1bFzKZzOBSu3ZtzJs3r9z9D16IiKqTfhAvAwyBJ3O0SCEhIdi4cSOWLl0KFxcXANpzDW3YsAGhoffPDTJw4ECUlJRg3bp1qFevHjIzM7Fnzx5kZ2cbPN6CBQswZswY/W07Ozu4uLgYhKRnn30WY8eONdiPiKi6CCHYA0MGGGAsUKtWrXD58mVs3rwZQ4cOBQBs3rwZoaGhCAsLAwDk5ubijz/+wP79+9GlSxcAQJ06ddC2bdtyj+fh4YGgoKBy97u7u+uv29nZPXQ/IiJTu6tUobBEDUC7DgwRDyEBgBBASYE0lyc8Gfjo0aPx3Xff6W+vXbsWo0aN0t92d3eHu7s7tmzZAqVS+dRNREQkJd0MJA9ne7g68n9vYg+MVmkh8GmwNM/99zTA0a3K3/bGG29g1qxZuHbtGgDg4MGD2LhxI/bv3w8AsLe3R2xsLMaMGYOVK1eiVatW6NKlC2JiYtCiRQuDx5o5cyY++OAD/e1PP/0U77333pO/JiIiI8vI0/4jxnMgkQ4DjIXy9/dHnz59EBsbCyEE+vTpAz8/P4N9Bg4ciD59+uCPP/7AX3/9hR07dmDx4sX49ttv9QN9AeD99983uP3g4xARSY3jX+hBDDAA4OCq7QmR6rmf0OjRozFhwgQAwNdff13hPs7OznjxxRfx4osvYs6cOXjrrbfw4YcflgssDRo0eOI6iIhMLYMBhh7AAAMAMtkTHcaRWs+ePVFSUgKZTIbo6OhKfU+TJk2wZcsW0xZGRGRkWVzEjh7AAGPB7OzskJSUpL9eVnZ2Nl577TWMHj0aLVq0gIeHB44ePYrFixfj5ZdflqJcIqInxh4YehADjIXz9PSs8H53d3e0a9cOS5cuxeXLl1FaWoqQkBCMGTMGf//736u5SiKip8NF7OhBMiGecB6vmVMoFPDy8kJeXl65D/ni4mJcvXoVYWFhcHbmL0N1YJsT0dOIWrgH6XnF2DK+A1qGeEtdDpnQoz6/y+I6MEREZNbUGoGsu5xGTYYYYIiIyKxlFyih1gjIZYCfu6PU5ZCZYIAhIiKzlnlvETs/dyfY2/Fji7T4k0BERGaNi9hRRWw6wFjp+GWzxLYmoifFKdRUEZsMMA4ODgCAwsJCiSuxHbq21rU9EVFlZekDDBexo/tsch0YOzs7eHt7IysrCwDg6uoKmUwmcVXWSQiBwsJCZGVlwdvbu9yCe0REj6PrgeEMJCrLJgMMAAQFBQGAPsSQaXl7e+vbnIioKriIHVXEZgOMTCZDzZo1ERAQgNLSUqnLsWoODg7seSGiJ6YfxOvFAEP32WyA0bGzs+OHKxGRGcvkGBiqgE0O4iUiIstQXKrGnUJtLznHwFBZDDBERGS2bt07hYCjvRxeLpzFSPcxwBARkdkqOwOJs0WpLAYYIiIyW5mcQk0PwQBDRERmKyNPG2ACOICXHsAAQ0REZivr3hgY9sDQgxhgiIjIbOl6YLiIHT2IAYaIiMxWBhexo4dggCEiIrOlP5GjB8fAkCEGGCIiMktCiPvTqNkDQw9ggCEiIrOkKFahuFQDgGNgqDwGGCIiMku6NWC8XBzg7MBz1pEhBhgiIjJLPIkjPQoDDBERmSVOoaZHYYAhIiKzpFvEjgGGKsIAQ0REZknXA8NVeKkiDDBERGSWOAaGHoUBhoiIzNL9AMMeGCqPAYaIiMxSpuLeiRy5iB1VgAGGiIjMjlojcCufg3jp4RhgiIjI7GTnK6HWCMhlgJ87x8BQeQwwRERkdnTnQPL3cIKdXCZxNWSOqhxgDhw4gH79+iE4OBgymQxbtmwx2L5582b06NEDvr6+kMlkSExMLPcYXbt2hUwmM7iMGzfOYJ/U1FT06dMHrq6uCAgIwPvvvw+VSlXVcomIyALpx7/w8BE9RJUDTEFBASIiIvD1118/dHvHjh2xaNGiRz7OmDFjkJ6err8sXrxYv02tVqNPnz4oKSnBoUOHsG7dOsTGxmLu3LlVLZeIiCyQrgcmgAGGHsK+qt/Qq1cv9OrV66Hbhw0bBgBISUl55OO4uroiKCiowm27du3CuXPnEBcXh8DAQLRs2RIfffQRZs6ciXnz5sHR0bGqZRMRkQXJ5CJ29BiSjYFZv349/Pz80KxZM8yaNQuFhYX6bfHx8WjevDkCAwP190VHR0OhUODs2bMVPp5SqYRCoTC4EBGRZeIidvQ4Ve6BMYYhQ4agTp06CA4OxqlTpzBz5kwkJydj8+bNAICMjAyD8AJAfzsjI6PCx1y4cCHmz59v2sKJiKhaZHARO3oMSQLM2LFj9debN2+OmjVr4oUXXsDly5dRv379J3rMWbNmYerUqfrbCoUCISEhT10rERFVvywF14ChRzOLadTt2rUDAFy6dAkAEBQUhMzMTIN9dLcfNm7GyckJnp6eBhciIrJMuh4YrsJLD2MWAUY31bpmzZoAgKioKJw+fRpZWVn6fXbv3g1PT080adJEihKJiKiaFJeqkVdUCgAI9GCAoYpV+RBSfn6+vqcEAK5evYrExET4+PggNDQUOTk5SE1NRVpaGgAgOTkZgLbnJCgoCJcvX8aGDRvQu3dv+Pr64tSpU5gyZQo6d+6MFi1aAAB69OiBJk2aYNiwYVi8eDEyMjLwwQcfYPz48XBy4oAuIiJrphvA6+wgh6eLJCMdyAJUuQfm6NGjiIyMRGRkJABg6tSpiIyM1K/Rsm3bNkRGRqJPnz4AgJiYGERGRmLlypUAAEdHR8TFxaFHjx4IDw/HtGnTMHDgQPz666/657Czs8P27dthZ2eHqKgovPHGGxg+fDgWLFjw1C+YiIjMW2aZ8S8yGVfhpYrJhBBC6iJMQaFQwMvLC3l5eRwPQ0RkQbadTMN7/zmBtmE++PHtKKnLoWpW2c9vsxgDQ0REpJOl4CJ29HgMMEREZFYy8riIHT0eAwwREZmVzLtcA4YejwGGiIjMSmYeV+Glx2OAISIis5J5l4vY0eMxwBARkdkQQtwfA8NF7OgRGGCIiMhs5BWVQqnSAAACOIiXHoEBhoiIzIZuETtvVwc4O9hJXA2ZMwYYIiIyGxlcA4YqiQGGiIjMhu48SAEMMPQYDDBERGQ2dFOogzj+hR6DAYaIiMyGbgo114Chx2GAISIis5GRx1V4qXIYYIiIyGxksQeGKokBhoiIzEZGHmchUeUwwBARkVlQqTW4na87hMRBvPRoDDBERGQWbueXQCMAO7kMvu4MMPRoDDBERGQW9GvAeDjBTi6TuBoydwwwREQkOZVag+OpdwBwETuqHHupCyAiItt0O1+J35NvYV9yFg5cuAVFsQoAULuGi8SVkSVggCEiomqh1gicupGLfcm38HtyFk7eyDPY7uXigM6N/DHphYYSVUiWhAGGiKyeUqVGXlGp1GXYpFK1wNGUHOxPvoXfL9xCTkGJwfamwZ54vnEAng/3R0Rtb9jbcWQDVQ4DDBFZtbhzmZj6Y6L+8ARJy8PJHp0a+aFr4wB0beTP8S70xBhgiMgqCSGw5s+r+OT/kiAEIJMBnNdS/WQyGRoGuKNr4wA839gfrerUgAN7WcgIGGCIyOqUqDSYu/UMNh65DgAY0i4U819qyg9OIivCAENEViW3sATv/Ps44q9kQy4DPujTBKM61IVMxv4XImvCAENEVuPKrXy8ue4ort4ugLuTPb4aHInnwwOkLouITIABhoiswqFLt/HO+uPIKypFLW8XrBnZBuFBnlKXRUQmwgBDRBbvP4dTMWfLGag0Aq1CvbF6eBv48Vw6RFaNAYaILJZaI7Dw/5Lw7Z9XAQAvtwzGooEt4OxgJ3FlRGRqDDBEZJHylSpM+s8J7DmfBQCY9mIjTOjWgIN1iWwEAwwRWZybuUV4M/YIzmfchZO9HF++HoG+LYKlLouIqhEDDBFZlBOpdzDm+2O4na+En7sTvh3RBi1DvKUui4iqGQMMEVmMbSfTMP2nkyhRafBMTU98O6INannzzMVEtogBhojMnhACy/dcxLK4iwCA7s8EYnlMS7g58U8Yka3ibz8RmbXiUjVm/PcUtp1MAwCM7VwPM3uGw07OwbpEtowBhojMVtbdYoz9/hgSr+fCXi7DJ680w6BnQ6Uui4jMAAMMEZmlpHQF3lp3FDdzi+Dt6oBvhrZGVH1fqcsiko5GA2hKpa7CkMwOsJMmSjDAEJHZ2ZOUiff+cwIFJWrU83PDmpHPIszPTeqyiKSTcxVYGw3kZ0pdiaEXPgQ6TZXkqRlgiMhsCCGw5s+r+OT/kiAE0L6+L74Z2hperg5Sl0YkHY0a+GWc+YUXiTHAEJFZKFVrMHfrGfzn8HUAwOC2oVjwclM42MklroxIYoe+Aq7/BTh6AGP2AB41pa7oPnvpzjnGAENEksstLMG764/j0OVsyGXA7D5NMLpDXZ4WgCjjDLDvE+31Xp8B/o2lrceMMMAQkaSu3MrHm+uO4urtArg52uGrIZHoFh4odVlE0lMpgV/eBtQlQOM+QMuhUldkVhhgiEgyhy7fxjv/Po68olLU8nbBmpFtEB7kKXVZROZh36dA5hnA1Q/otxxgj6QBBhgiksTGw6n4YMsZqDQCkaHeWD2sDfw9pDueTmRWrsUDB5drr/dbDrj7S1uPGWKAIaJqpdYIfLYjCf/64yoA4KWIYCx+tQWcHewkrozITCjvAlvGARDaw0bP9JW6IrPEAENE1aZAqcKkjScQl5QFAJjSvRHee6EBB+sSlbXrA+BOCuAVAvRcKHU1ZosBhoiqxc3cIry17iiS0hVwspfji9ci0C8iWOqyiMzLhf8Bx2K11/t/Azh7SVqOOWOAISKTO5F6B2O+P4bb+Ur4uTvhX8NbIzK0htRlEZmXgmxg6wTt9efGA2GdpK3HzDHAEJFJ/XoyDdN/OgmlSoPwIA+sGfksanm7SF0WkXkRAvhtClCQBfg1Bl6YI3VFZo8BhohMQgiBFXsuYWncBQBA92cCsCwmEu5O/LNDVM7pn4BzWwG5PTBgFeDAkP84/EtCREZXXKrGjP+ewraTaQCAMZ3C8Ldez8BOzsG6ROXk3QR+m6693mUmEBwpbT0WggGGiIzugy1nsO1kGuzlMnzcvxli2oZKXRKRedJogK3vAso8oFZroKM0Z3a2RAwwRGR0By7cAgCsGByJ3s3N6MRzRObmyLfAlf2AvQvwyirAjh/LlcXTvBKRURWWqJB1VwkA6FDfT+JqiMzY7YvA7rna6y8uAPwaSluPhWHUIyKjSrldCADwdnWAl6uDxNWQVUtLBHbMBEoLpK7kydzNAFRFQL3ngWffkroai8MAQ0RGdS1b+2FS19dN4krI6h1dA1z/S+oqno6zN/Dy14CcB0SqigGGiIwqJVvbA1PX11XiSsjqZSVpv3b5GxDSVtpanlTAM4AnV6R+EgwwRGRUKbe1PTB12ANDpiTE/QDTbADg31jaeqjaVbnP6sCBA+jXrx+Cg4Mhk8mwZcsWg+2bN29Gjx494OvrC5lMhsTExHKPUVxcjPHjx8PX1xfu7u4YOHAgMjMzDfZJTU1Fnz594OrqioCAALz//vtQqVRVLZeIqlnKvUNIYX4MMGRCedeBknzAzhHwqSd1NSSBKgeYgoICRERE4Ouvv37o9o4dO2LRokUPfYwpU6bg119/xU8//YTff/8daWlpGDBggH67Wq1Gnz59UFJSgkOHDmHdunWIjY3F3Llzq1ouEVUzXYCpw0NIZEq63he/RoAdB4vboiofQurVqxd69er10O3Dhg0DAKSkpFS4PS8vD2vWrMGGDRvQrVs3AMB3332HZ555Bn/99Reee+457Nq1C+fOnUNcXBwCAwPRsmVLfPTRR5g5cybmzZsHR0fHco+rVCqhVCr1txUKRVVfGhE9pcISFTIV2t9D9sCQSWWe1X4NeEbaOkgy1T7s+dixYygtLUX37t3194WHhyM0NBTx8fEAgPj4eDRv3hyBgYH6faKjo6FQKHD27NkKH3fhwoXw8vLSX0JCQkz7QoionNQc7QBeLxcHeLuW/0eDyGh0PTAMMDar2gNMRkYGHB0d4e3tbXB/YGAgMjIy9PuUDS+67bptFZk1axby8vL0l+vXrxu/eCJ6JN0AXs5AIpPTB5gm0tZBkrGaWUhOTk5wcnKSugwim6afQs3DR2RKahVwO1l7nT0wNqvae2CCgoJQUlKC3Nxcg/szMzMRFBSk3+fBWUm627p9iMj8cAo1VYucK4C6BHBwA7x4olBbVe0BpnXr1nBwcMCePXv09yUnJyM1NRVRUVEAgKioKJw+fRpZWVn6fXbv3g1PT080acLuQiJzdX8KNQ8hkQllndN+DQjnCrY2rMqHkPLz83Hp0iX97atXryIxMRE+Pj4IDQ1FTk4OUlNTkZaWBkAbTgBtz0lQUBC8vLzw5ptvYurUqfDx8YGnpycmTpyIqKgoPPfccwCAHj16oEmTJhg2bBgWL16MjIwMfPDBBxg/fjwPExGZsWv3DiGxB4ZMigN4CU/QA3P06FFERkYiMjISADB16lRERkbq12jZtm0bIiMj0adPHwBATEwMIiMjsXLlSv1jLF26FH379sXAgQPRuXNnBAUFYfPmzfrtdnZ22L59O+zs7BAVFYU33ngDw4cPx4IFC57qxRKR6RSVqJGeVwyA50EiE9P3wLBH3pbJhBBC6iJMQaFQwMvLC3l5efD09JS6HCKrl5xxF9HLDsDT2R4nP+wBmUwmdUlkrb5qA2RfBIb9AtTvJnU1ZGSV/fzmwUMiMoqruinUfm4ML2Q6pcVAzmXtdfbA2DQGGCIyimvZujVgePiITOj2BUBoAJcagHvg4/cnq8UAQ0RGoV8DhovYkSmVXcCOPX02jQGGiIyCa8BQtdAP4OUMJFvHAENERqE/hMRVeMmUeAoBuocBhoieWnGpGmn6KdQ8hEQmxCnUdA8DDBE9Nd1ZqD2c7eHjxrNQk4kUK4C8eyfqDQiXthaSHAMMET21+2eh5hRqMqFb57VfPYK1s5DIpjHAENFT050DqQ4PH5EpcQAvlcEAQ0RPTTeFOowDeMmUeA4kKoMBhoieGqdQU7XgAF4qgwGGiJ7aNX0PDA8hkQmxB4bKYIAhoqeinUJdBIA9MGRC+beAglsAZIB/Y6mrITPAAENET+V6TiGEADyc7OHLKdRkKrfu9b7UqAs4MigTAwwRPSXdAN46fq6cQk2mwxV46QEMMET0VDiAl6oFp1DTAxhgiOip6NaACWOAIVPiAF56AAMMET0V3QwkLmJHJiMEDyFROQwwRPRUrt47hMRF7MhkFDcBpQKQ2wO+DaSuhswEAwwRPTGlilOoqRpk3hv/4tsQsOdMN9JigCGiJ6abQu3maAc/d36wkInoBvAG8vAR3ccAQ0RPLOW2dvxLXT+ehZpMiAN4qQIMMET0xHQzkOry8BGZEs+BRBVggCGiJ6YPMDwHEpmKRg3cStZeZw8MlcEAQ0RP7P4UavbAkInkXAXUSsDeBfCuK3U1ZEYYYIjoiemmUPMQEpmM/vBROCDnRxbdx58GInoiSpUaabnaKdQ8hEQmwwXs6CEYYIjoidy4UwTNvSnU/u5OUpdD1ornQKKHYIAhoidS9iSOnEJNJsMp1PQQDDBE9ERSsnVrwPDwEZmISglkX9Je5yEkegADDBE9kbI9MEQmcfsiINSAsxfgUVPqasjMMMAQ0RPRrQETxgBDplJ2AC8PU9IDGGCI6IncXwOGh5DIRDiAlx6BAYaIqqxEpcGNO9oAE+bHHhgyEZ5CgB6BAYaIquzGnUJoBODqaAd/D06hJhNhDww9AgMMEVWZbvwLp1CTySjvArmp2uvsgaEKMMAQUZWl3L43hZrjX8hUdCdwdA8CXH2krYXMEgMMEVXZtWxOoSYT4+EjegwGGCKqsqvZugG87IEhE+E5kOgxGGCIqMrYA0Mmxx4YegwGGCKqklK1BjfuaM9CzSnUZDLsgaHHYIAhoiq5cacIao2As4McAZxCTaZQkA3kZ2qv+zeWthYyWwwwRFQluinUdTmFmkzl1r3eF+86gJO7tLWQ2WKAIaIq0Z3EsS7Hv5Cp8PARVQIDDBFVif4cSJyBRKbCAbxUCQwwRFQlV2/zLNRkYuyBoUpggCGiKuEUajIpIdgDQ5XCAENElVZ2CnVdHkIiU1CkAcV5gMwO8GsodTVkxhhgiKjSbt4pgureFOpAD2epyyFrpDt85NsAsOc0fXo4BhgiqjT9Wah93CCXcwo1mQAPH1ElMcAQUaXpp1Dz8BGZCgfwUiUxwBBRpaXcm0LNNWDIZNgDQ5XEAENElcYZSGRSGjVwK1l7PbCptLWQ2WOAIaJK0/fA8BASmcKdFEBVBNg7AzXqSl0NmTkGGCKqFJVag+s5PIREJqQ7fOTfGJDbSVsLmT0GGCKqlJu52inUTvZyBHlyCjWZwJmftV+DW0lbB1kEBhgiqhTd4aM6vq6cQk3Gd+cacG6r9vqzb0lbC1kEBhgiqhQO4CWTOrwaEBqgXlcgqJnU1ZAFqHKAOXDgAPr164fg4GDIZDJs2bLFYLsQAnPnzkXNmjXh4uKC7t274+LFiwb71K1bFzKZzODy2WefGexz6tQpdOrUCc7OzggJCcHixYur/uqIyGj0J3H0Y4AhIytWAMfWaa8/N17aWshiVDnAFBQUICIiAl9//XWF2xcvXowVK1Zg5cqVSEhIgJubG6Kjo1FcXGyw34IFC5Cenq6/TJw4Ub9NoVCgR48eqFOnDo4dO4bPP/8c8+bNw+rVq6taLhEZybUyh5CIjOrED0DJXcCvEdCgu9TVkIWwr+o39OrVC7169apwmxACy5YtwwcffICXX34ZAPD9998jMDAQW7ZsQUxMjH5fDw8PBAUFVfg469evR0lJCdauXQtHR0c0bdoUiYmJWLJkCcaOHVvVkonICHSr8IbxEBIZk1oFJKzUXn/uXUDOkQ1UOUb9Sbl69SoyMjLQvfv9BO3l5YV27dohPj7eYN/PPvsMvr6+iIyMxOeffw6VSqXfFh8fj86dO8PR0VF/X3R0NJKTk3Hnzp0Kn1upVEKhUBhciMg4VGoNrt+51wPDQ0hkTOe3A7mpgIsPEBHz+P2J7qlyD8yjZGRkAAACAwMN7g8MDNRvA4D33nsPrVq1go+PDw4dOoRZs2YhPT0dS5Ys0T9OWFhYucfQbatRo0a55164cCHmz59vzJdDRPek5xWjVC3gaC9HTU6hJmOKvzcc4dm3AAcXaWshi2LUAFNZU6dO1V9v0aIFHB0d8fbbb2PhwoVwcnqy06fPmjXL4HEVCgVCQkKeulYiuj+At44Pp1CTEV0/Atw4DNg5cuo0VZlRDyHpxrRkZmYa3J+ZmfnQ8S4A0K5dO6hUKqSkpOgfp6LHKPscD3JycoKnp6fBhYiMg1OoyST+utf70vw1wCPw0fsSPcCoASYsLAxBQUHYs2eP/j6FQoGEhARERUU99PsSExMhl8sREBAAAIiKisKBAwdQWlqq32f37t1o3LhxhYePiMi0rt7Wjn8J4zmQyFjKLlz33LvS1kIWqcqHkPLz83Hp0iX97atXryIxMRE+Pj4IDQ3F5MmT8fHHH6Nhw4YICwvDnDlzEBwcjP79+wPQDtBNSEjA888/Dw8PD8THx2PKlCl444039OFkyJAhmD9/Pt58803MnDkTZ86cwfLly7F06VLjvGoiqrTsfCW2nbwJAGgY6CFxNWQ1uHAdPaUqB5ijR4/i+eef19/WjTsZMWIEYmNjMWPGDBQUFGDs2LHIzc1Fx44dsXPnTjg7awf+OTk5YePGjZg3bx6USiXCwsIwZcoUg/ErXl5e2LVrF8aPH4/WrVvDz88Pc+fO5RRqomomhMDffzmN2/klaBzogZcigqUuiaxB2YXroiZIWwtZLJkQQkhdhCkoFAp4eXkhLy+P42GIntDPx25g2k8n4WAnw5bxHdA02EvqksgaxH8N/O/vgF9j4N2/uPYLGajs5zd/aoioQjdzizBv21kAwOTujRheyDgMFq57h+GFnhh/coioHI1G4P2fTuKuUoVWod54u3M9qUsia8GF68hIGGCIqJx18Sk4dDkbLg52+PL1lrC3458KMhIuXEdGwr9KRGTgUlY+PttxHgDw9z7P8OzTZDzXD3PhOjIaBhgi0itVazD1x0QoVRp0buSPN9qFSl0SWRNd70vz17lwHT01Bhgi0vt63yWcupEHLxcHLB7YAjIZTxtARnLnGpC0TXs9igvX0dNjgCEiAMCpG7n4aq92kcqP+jdDkBdP2khGVHbhusCmUldDVoABhohQXKrGlE2JUGsE+raoyQXryLi4cB2ZAAMMEWHxzmRcvlWAAA8nfPQyl3UnIzvxA1ByV7twXf0XpK6GrAQDDJGNO3TpNtYevAoAWPRqC9Rwc5S4IrIqZReui3qXC9eR0fAniciGKYpLMf2nkwCAIe1C8XzjAIkrIqujW7jO1RdoMUjqasiKVPlkjkRkPeZvO4e0vGKE+rhidu9npC6HyhICKMkHCrO1Y0gs1aGvtF/bvMmF68ioGGCIbNTOMxn4+fgNyGXAktcj4ObEPwfVQl0KpP4F5Gdqw0m5S8796+oSqas1Di5cRybAv1hE9ySlK3Docjas9ATt5Xyz/zIA4O0u9dGmro/E1diQPQuAQysqv7+9M+DkCcgs9Ii/TA60fYsL15HRMcCQzVOpNfh632Ws2HsRao1thBed8CAPTO7eUOoybIdKqZ2RAwC1nwU8g7VjQwwuPoa3HXkqB6KKMMCQTUvNLsSUHxNx7NodAED7+r7w93CSuKrq4Wgnx7vPN4CTvZ3UpdiOCzuBojuAR01g9P8AOdue6EkxwJBNEkLg5+M3MW/bWeQrVfBwssdH/Zuhf2QtqUsja3ZivfZrRAzDC9FTYoAhm5NbWILZv5zBb6fTAQBt6/rgy9cjEOLjKnFlZNXuZgCX4rTXI4ZIWwuRFWCAIZty6NJtTP3xJDIUxbCXyzDlxUYY16U+7OQ8aSGZ2KkfAaHWjn3xbyR1NUQWjwGGbIJSpcYX/0vGv/7Qrjhbz88Ny2JaokVtb2kLI9sgBJB47/BRy6HS1kJkJRhgyOpdyLyLSRsTkZSuXQxscNtQzOn7DFwd+eNP1STtOHDrvHZKdNNXpK6GyCrwLzhZlOJSNVSVnOoshMDm4zfx6f8lQanSwMfNEZ8NaI4eTYNMXCXRA3SDd8P7Ai7ekpZCZC0YYMhibDqSilmbT+NJlmrp0sgfn7/WAgEezsYvjOhRSouBM//VXo/k4SMiY2GAIYuxPiG1yuHF3cke03s0woj2dSGTcaAuSSD5/4DiPMCzFhDWRepqiKwGAwxZhExFMU7dyAMAHPxbN/i6OVbq+xzs5JxhRNLSDd6NGMy1X4iMiAGGLMK+81kAgIgQb9Ty5hltyUIo0oDLe7XXW3LtFyJjstCzg5GtiUvSBpju4QESV0JUBac2AUIDhDwH+NaXuhoiq8IAQ2avuFSNg5duAwC6PcMAQxZCiPuzjzh4l8joGGDI7MVfyUZRqRo1vZzRpKan1OUQVc6No0D2RcDeBWjSX+pqiKwOAwyZvT1JmQCAbuEBnElElkM3eLfJS4AzgzeRsTHAkFkTQmDvvfEvL/DwEVmK0iLgzGbtdZ46gMgkGGDIrCWl30VaXjGcHeRoX99P6nKIKuf8b4AyD/AKAep2kroaIqvEAENmbe957eGjjg384OzANTTIQpz4t/ZrxGBAzj+zRKbA3ywya3vO6w4fBUpcCVEl5d0AruzXXm85WNJSiKwZAwyZrdv5SiRezwUAPN+Y41/IQpzcCEAAdToAPvWkrobIajHAkNnadz4LQgDNankiyIsnYSQLIMT92UdceZfIpBhgyGzt1R0+CufhI7IQ1xOAnCuAgxvXfiEyMQYYMktKlRoHLtwCwOnTZEH0a7+8DDi5S1sLkZVjgCGzdPhqDgpK1PD3cEKzYC+pyyF6vJIC4Mwv2us8dQCRyTHAkFnao1u8LjwAcjlX3yULkLQdKLkLeNcBQttLXQ2R1WOAIbMjhMCe8/dPH0BkEcoO3uXaL0Qmx98yMjuXsvJxPacIjvZydGzI1XfJAuSmAlcPaK9HcO0XourAAENmJ+7e4aP29X3h6mgvcTVElaBb+6VuJ6BGHamrIbIJDDBkdnSnD3iBh4/IEmg0ZQ4fcfAuUXXhv7dkVu4UlODYtTsAgG48fQA9LZUSuLgLOLsFKLxtuue4kwI4ugNNXjLNcxBROQwwZFb2X8iCRgDhQR6o5e0idTlkiYQAbhzRHtY5uxkoulM9z9v8NcDRrXqei4gYYMi86KZPd2fvC1VVzlXg1I/AqY3a1XB13IOA5q8CQS0AmYmm5Ns5Ag1fNM1jE1GFGGDIbJSqNfj93uq73bj6LlVG0R3t4aGTG4Hrf92/38EVeKYf0GIQUK8rILeTqkIiMhEGGDIbR1JycLdYBV83R0TU9pa6HDJXqhLgUhxw8j/AhZ2AuuTeBhlQrwvQIkYbXriUP5FVY4Ahs7H33uGj58MDYMfVd6ksIYCbx7Wh5czPQFHO/W0BTbQ9Lc1fA7xqSVcjEVUrBhgyG3vO3z99ABEA4M61++Nasi/dv98tQBtYImKAoOamG9tCRGaLAYbMwpVb+bh6uwAOdjKuvmvrivO041pObQKuHbx/v70L8Exf7SGiel0BO/75IrJl/AtAZkE3++i5er7wcHaQuBqqdupS4NIebU/L+f8D1Mp7G2RAWCdtaGnyEuDkIWmZRGQ+GGDILPDkjTZICCDthLan5fR/DRea8w/Xjmtp8TrgVVu6GonIbDHAkOTyikpxJEW72NgL4Vz/xerlXteGllObgNsX7t/v5q8d19JiEFAzguNaiOiRGGBIcr9fuAW1RqBhgDtCfV2lLodMoVgBnNuqDS0pf9y/394ZCO+jPURUvxvHtRBRpfGvBUlub9K9w0dcvM66qFXA5b33xrX8BqiK72+r20nb09LkZcDZU7oaichiMcCQpFRqDfbfW32Xpw94DI0aKMwG7mYA+VlAfua9y73rBbe0+5iL7IvamnT8Gt0f1+IdKl1dRGQVGGBIUsdTc5FbWApvVwdEhnhLXU71EwJQ3q0gkFQQUgpuAUIjdcVV4+qnPQ9Ri0FAcCTHtRCR0VQ5wBw4cACff/45jh07hvT0dPzyyy/o37+/frsQAh9++CH+9a9/ITc3Fx06dMA333yDhg0b6vfJycnBxIkT8euvv0Iul2PgwIFYvnw53N3vL/196tQpjB8/HkeOHIG/vz8mTpyIGTNmPN2rJbOjm33UtZE/7O3kEldjRKoSbeAwCCIPBBJdT4qqqAoPLNMOdnUPBNwDtF89ArVf3fwBOzOagu7sBdTpYF41EZHVqHKAKSgoQEREBEaPHo0BAwaU27548WKsWLEC69atQ1hYGObMmYPo6GicO3cOzs7OAIChQ4ciPT0du3fvRmlpKUaNGoWxY8diw4YNAACFQoEePXqge/fuWLlyJU6fPo3Ro0fD29sbY8eOfcqXTOZEt/7LC5Zw+EgI7ckDHzx0c7eCkFJ2qfvKcPTQBhKPoPvBRP9Vdz0IcPXlQFciIgAyIYR44m+WyQx6YIQQCA4OxrRp0zB9+nQAQF5eHgIDAxEbG4uYmBgkJSWhSZMmOHLkCNq0aQMA2LlzJ3r37o0bN24gODgY33zzDWbPno2MjAw4OjoCAP72t79hy5YtOH/+fKVqUygU8PLyQl5eHjw9jTdI8PrFk7hz46LRHs+WFZSosPL3K7CTAV8NaQU3RzP4YC4tfKC35IGvmtLKP5bc/oEgUjaQlA0mAYCjm+leExGRBans57dRPzGuXr2KjIwMdO/eXX+fl5cX2rVrh/j4eMTExCA+Ph7e3t768AIA3bt3h1wuR0JCAl555RXEx8ejc+fO+vACANHR0Vi0aBHu3LmDGjVqlHtupVIJpVKpv61QKIz50vRu7FuDqLR1JnlsWxSle4t/krSMqnGpYdgrUq6nJFDbk+LsDcit6LAYEZEZMWqAycjIAAAEBhoeDggMDNRvy8jIQECA4XRZe3t7+Pj4GOwTFhZW7jF02yoKMAsXLsT8+fON80IeQe5ZE5cy65v8eWyFTAYEejrD3dFO6lK07J3LB5Kyh3Xc/AF7J6mrJCKyeWbQZ28cs2bNwtSpU/W3FQoFQkJCjP487WJmAZhl9MclIiKiyjNq/3ZQUBAAIDMz0+D+zMxM/bagoCBkZWUZbFepVMjJyTHYp6LHKPscD3JycoKnp6fBhYiIiKyTUQNMWFgYgoKCsGfPHv19CoUCCQkJiIqKAgBERUUhNzcXx44d0++zd+9eaDQatGvXTr/PgQMHUFp6f8Dk7t270bhx4woPHxEREZFtqXKAyc/PR2JiIhITEwFoB+4mJiYiNTUVMpkMkydPxscff4xt27bh9OnTGD58OIKDg/UzlZ555hn07NkTY8aMweHDh3Hw4EFMmDABMTExCA4OBgAMGTIEjo6OePPNN3H27Fls2rQJy5cvNzhERERERDZMVNG+ffsEgHKXESNGCCGE0Gg0Ys6cOSIwMFA4OTmJF154QSQnJxs8RnZ2thg8eLBwd3cXnp6eYtSoUeLu3bsG+5w8eVJ07NhRODk5iVq1aonPPvusSnXm5eUJACIvL6+qL5GIiIgkUtnP76daB8acmWodGCIiIjKdyn5+c5EKIiIisjgMMERERGRxGGCIiIjI4jDAEBERkcVhgCEiIiKLwwBDREREFocBhoiIiCyO1ZzM8UG65W0UCoXElRAREVFl6T63H7dMndUGmLt37wKASc5ITURERKZ19+5deHl5PXS71a7Eq9FokJaWBg8PD8hkMqnLsVgKhQIhISG4fv06VzR+SmxL42FbWi++t8ZjqW0phMDdu3cRHBwMufzhI12stgdGLpejdu3aUpdhNTw9PS3qF8CcsS2Nh21pvfjeGo8ltuWjel50OIiXiIiILA4DDBEREVkcBhh6JCcnJ3z44YdwcnKSuhSLx7Y0Hral9eJ7azzW3pZWO4iXiIiIrBd7YIiIiMjiMMAQERGRxWGAISIiIovDAENEREQWhwGGiIiILA4DDJGRqFQqqUsgIrIZDDA2KjMzE8uWLcPmzZtx4cIFAI8/8ydVLC0tDW3btsXcuXOlLsXi5eTk4PTp08jMzJS6FDKyoqIiKJVKqcuwCpmZmVizZg327t2LW7duSV2OZBhgbNDcuXNRv359bN++HRMmTMCIESNw7tw5yGQyhpgqmjJlCurWrYugoCBMmDBB6nIs2t/+9jc0a9YMw4cPR7NmzfDTTz+hqKhI6rLICObMmYM2bdogISFB6lIs3uzZs9GgQQP88MMP6N+/PyZMmICUlBSpy5IEA4yN+eGHH/Dbb79h69atiIuLww8//ACNRoP4+HgA4Jm7Kyk1NRW1atXCtm3b8Oeff2Lbtm0IDg6WuiyLlJKSgn79+iEuLg4bN25EbGwsBg4ciBkzZuDSpUtSl0dPISMjA8OHD8dvv/2GlJQUxMbGIi8vT+qyLNayZcvwv//9D9u3b8e+ffvwzTffICkpyWZ/TxhgrJyuR0X3defOnfD398cLL7wAAPqvbdu2Lfc99HD29vaoVasW2rZti7Zt2+L48eOYMWMGlixZgri4OBQXF0tdosU4evQoZDIZYmNj0blzZ0RERGDlypXIycnBlStXAPBn0lLl5eXB398fy5cvx6ZNm7Bu3Tr88ccfUpdlcXQ//3FxcWjWrBm6dOkCmUyGAQMGAADq1asnZXmSsZe6ADKdkpISCCHg5OQEmUyG4uJi+Pv7IyUlBSdOnEBoaCjGjh2L69ev48MPP0S7du0wffp02NnZSV262RFCQCaTQaVSwd7eHsHBwViwYAF69+6NnJwcnD9/HhEREdi5cycyMzMxYMAA/POf/2SPVgVUKhXs7Oz0bdOhQwd4enqiWbNm+n1yc3MREhICuVz7Pxbb0TKoVCrI5XL9+1anTh1MmjQJoaGhAIBu3bph0aJFaNWqFXssH6NsW8pkMigUCtjb26O4uBjXrl2Dj48Phg4dipKSEnz00Ufo2bMnXn/9dZv6XWEPjJWaN28eOnbsiJdffhmrV69GdnY2nJ2d8dJLL6FGjRqYOXMmAgICkJubi1WrVqFevXpYtWoVxo0bBwDQaDQSvwLz8dVXX2HevHkAtD0vuv+GOnXqhLfffhs5OTn473//i02bNuHUqVOYPXs24uPjsXLlSgmrNk8LFy7EK6+8giFDhmDbtm3Iz89HzZo10aNHDwD3f+4yMzNx/fp1NGrUSMpyqQoWLFiAHj16YPDgwdixYwfy8/Ph7OyM0NBQ/fu6evVqHDx4EFu3bkVpaanEFZuvB9tSoVDA09MTAwcOxM2bN/HWW2/By8sLBQUFmD9/PoqKirBgwQJ88MEHUpdevQRZldLSUjFs2DDRoEEDsW7dOjF48GDRtGlT0bt3b/0+arVarFq1SvTp00cUFhbq7//uu+9EYGCgyMrKkqJ0s5OYmCiio6OFTCYTzZs3F3v27BFCCKFSqfT7XLhwQcTHxwu1Wi3UarUQQojs7GwRHR0tJkyYYLCvLUtISBAtW7YUzZo1E0uXLhVdunQRkZGRYunSpQb7aTQaIYQQ3377rYiMjDS4j8xTYWGh6N+/v2jYsKFYsWKFeP7550XTpk3F22+/bbCf7ndhwoQJok6dOiIpKUmKcs3aw9pyzJgxQgjt74JSqRQff/yxGDBggCgpKRFCaP+mL1iwQLRp00bk5uZK+RKqFXtgrMz169dx5MgRLFmyBMOHD8eGDRuwdOlS7Nu3D0uXLgUAyOVynD9/HgEBAXBxcTH43sDAQPa+3LNnzx44OTkhNjYWISEhiI2N1R/+0LVRgwYN8Nxzz+m7ejUaDXx8fJCSkoKSkhIejgNw+/ZtrFmzBs8++yzi4+MxefJk7N+/H40aNUJSUpLBf+K67u8jR46gS5cu+vsOHz7MsRNm6vz58zh79iy+//57TJw4EXv37sXEiRPx73//Gz/++CMAQK1W69/bFStWIDc3F7GxscjNzcX27dv1+9m6h7Xlhg0b8OOPP0Imk0EulyM5ORlNmzaFg4MDAO3f9LS0NDg5ORn0Els7BhgrU1paiuTkZEREROjve/HFFzFnzhwsWLAAqampALSzA3JycnDo0CEAwIULF7B//35069YNgYGBktRuboYMGYJp06Zh+PDh6NGjBy5cuID169cDuP9B++DxZrlcjj179sDT0xMjRoyo9prNVXBwMMaNGwd3d3d9YAkJCUFiYqL+j7BOQUEBDh48iO7duyM1NRW9e/dGVFQUcnJypCidHqOwsBCpqalo0KCB/r6YmBiMGDEC7733HgDoxzzpgszixYuxdOlStG/fHq+88grXh7mnMm1pb2+Pixcv4tq1a/rZR0lJSUhKSkJ0dDTc3NxsZhwMA4yVUavViIiIwKZNmwzuHz9+PHx8fPDll1/qb2dkZKBfv37o378/2rRpg5o1a+Kjjz6SomyzFBQUhM6dOwMABg4ciNDQUPz000/IzMyETCYz6KlKSkrC77//jkmTJuG1115Dx44d8eyzz0pVulnx8/PD7Nmz0apVKwDaP8AAcOvWLXTo0KHc/ufPn8fNmzexfv16NGzYEE5OTsjMzMTLL79crXVT5RQXFyM8PBxxcXH6+7y8vPDuu+8CABYvXgxAOxDezs4O165dw8mTJ1FaWornnnsOGRkZGDZsmCS1m5vHteUnn3wCQDvGMS4uDj179sSgQYPQtm1bhIaGYurUqZLULRUGGCsTGhqKxo0bIyEhQb+4kUajgaenJ9555x388ssvKCwsRIcOHbBmzRosW7YMbdu2xf79+/Hvf/8b7u7u0r4AM6TRaFC7dm288soryMnJwZo1awBAP9MCAE6ePIlPPvkEx48fx44dO7BkyZJyPQu2Sghh0K2t++/w0qVLiIyM1O+jk5iYiNzcXNy4cQP79+/HL7/8Aj8/v+ovnAA8fgp7mzZt4OzsjEOHDuH27dv6++vUqYOYmBj8+uuvUCqVkMvlKCwsxLx587B161YkJCRg7dq18PX1NfVLMBtP25Y7duxAUVERoqOjsX79ekyaNAlhYWHYv38/vv/+e7i5uZn6JZgXCcffUBXpBolWNDC0tLRUf/0///mPaNGihVi0aJHBPqtXrxbNmjUTKSkppi3UAlS2LcveLiwsFG+//bbo0qWLOHnypBBCiMOHDwshhMjPzxcXLlwwZclmqyptqdvn6tWrwsPDQ5w6dUq/7ebNm0IIIdLT08WWLVtMVS5VgUKhEEqlUn9b914LYfjeLlu2TNSvX19s2rTJ4Ps/+OAD0aFDB5Gfn6+/Lz093YQVmy9jtaVCoTB9sRaCPTAWYurUqXjjjTcAwGBgqLiX6O3t7aFWq7F+/XrExMSgffv2+OWXX7B9+3b9vrdv34a3tzdq165dvcWbmcq0pRAC69at09/WaDRwcXHBoEGDYG9vj08//RS9evVCu3btkJaWBjc3NzRs2LD6X4zEqtqWun127NiB+vXro3nz5rh58yYGDRqE/v37Izs7G0FBQTxcJDEhBKZMmYLo6Gj07t0bc+fORVFREeRyuX4Mk+5vzs6dOzFp0iTUr18fsbGx+Ouvv/SPU1hYCC8vL4PJAkFBQdX+eqRk7La0uV6WR5EwPFElHD9+XHTv3l34+/sLuVwudu7cKYQo/5/t6tWrRUBAgOjRo4coKSkRSUlJYvTo0cLe3l688847YsKECcLLy0t89dVXQgjbnJpa1bbs3bu3yMzMNNiWmZkpmjZtKmQymXjllVdstjfrSdqy7PT8KVOmiEmTJolPP/1UuLi4iG7duokbN25U62ugiv3++++iSZMm4rnnnhM///yzGDNmjGjSpImYNGmSwX6rVq0Sfn5+IiYmRgghxKFDh0Tfvn2Fn5+fmD9/vpg6darw9vYWP/zwgwSvwjywLU2LAcbMrVq1SowYMUL89ttv4o033hDNmjUrt88PP/wgQkJCxJo1a8p9gHzxxRdi7NixIjo6Wr+Oia2qals+eEgkPj5e+Pj4iPDwcPHnn39WV9lm6WnasqCgQNStW1fIZDLRqFEjsWvXruosnR6hoKBATJgwQbz55pv6NaJUKpVYtGiR6Nq1q36NkRUrVghnZ2exdu1ag7852dnZYsaMGWLQoEGiU6dONv03h21pegwwZi4jI0M/TmDfvn2iZs2aYsmSJUIIoV/ESAhR7rioLfawPM6TtqVOfn4+/wO652naMjs7WwwbNkysX7++eoqlSsvNzRU//PCDfmyXbpzGxx9/LFq3bq0PohqNRty5c+ehj1P2Z8BWsS1NTyaEjax4YwEWLlyIrKwshIeHY9SoUXB0dDTYnpubi0WLFmHt2rW4dOkSPDw8oFaruVhaBYzdluLeuZBskTHb0pbb0Rw97r3VvY8zZ87ElStX8NNPP/E9fAi2ZfXjIF4zoFtV8T//+Q/S09Mxa9YsREdHIyEhAcD9AZHe3t4YNGgQAgICMH36dAA8yd2DTNWWttjOpmhLW2xHc/Sw91Y3aFS3xpHu/Tp8+DDat28vWb3mjG0pIcn6fkjvyy+/FFFRUfrjn+np6SIiIkK8/vrr4tKlS0KI+4Mji4uLxT/+8Q/h4eEhzp49K4TQduE/qgvSlrAtjYdtab0q897qDnlkZGQIf39/cfToUf336/bhub7YllJiD4zEVCoVzp49i4CAAH2Xe1BQEGbPno3U1FT9omm66ahOTk7o3bs3OnbsiKFDh6Jjx47o06cPMjMzpXwZZoFtaTxsS+tV2fdWt1BjXFwc/Pz80Lp1a5w7dw5du3ZFixYtUFRUZPOHr9mW0mKAkZi9vT2USiWKioqg0WigVqsBAK+99hpat26NhIQEnDhxAsD9LnuVSoWcnBycPHkS4eHhyMjIQOPGjSV7DeaCbWk8bEvrVZX3FgDOnTuHhg0bYtasWWjRogVq166N9PR0g7VdbBXbUmJSdv/YOl2X4b59+4RcLhcnTpwQQtzvlt+/f79o0KCB+PHHH/Xfc+TIEdGoUSPRsmVLfVc9sS2NiW1pvZ7kvW3WrJmQyWSiffv24tixY9Ves7liW0qPAcbE7t69a3C77PRm3Q96UVGR6NKli+jevXu5ferXry8WLFigv3379m2bXYOEbWk8bEvrZYz3dv78+UII7TT4L774Qvz666+mLtsssS3NGw8hmUhJSQkmTpyI/v37Y8CAAdi0aZN+ytyDy0fn5eVh/vz5+P3337Fy5Up9l/ydO3fg5uYGHx8fANquel9f3wrP4GvN2JbGw7a0XsZ8b3UnWPTw8MC0adPQt29fyV6XFNiWFkKS2GTlvv/+e1GzZk3RtWtX8f3334vu3buLqKgosWPHDoP9li9fLhwdHUVsbKwQQrvAUUBAgHjrrbfEgQMHxJQpU0RYWJhISkqS4mWYBbal8bAtrRffW+NhW1oOBhgjS05OFq+++qpYunSp/r6UlBQRGBgodu/eLYTQrtA4ZMgQERwcLNatW2fQ5bhixQrRqVMn0bx5cxERESESEhKq+yWYDbal8bAtrRffW+NhW1oWBhgjy8nJEQkJCQbrXxw/flz06NFDxMfH64+bJiQkiLy8PP0+ZU+trlarxZUrV6qtZnPFtjQetqX14ntrPGxLy8IA85R++uknsXv3bpGWllbh9vHjxwt7e3vRsmVL4efnJ3r16iX++OMPIQQXLnoQ29J42JbWi++t8bAtLRsDzBP6/vvvRUBAgGjbtq3w9/cXHTp0EJs3bxZCGKbxmJgYsXPnTpGfny8OHjwoXn/9dREVFSVV2WaJbWk8bEvrxffWeNiW1oEBpopKS0vFsmXLxDPPPCO+/fZboVQqxcGDB8Xw4cNFr169RHFxsX4/IcqfFfqDDz4QkZGR4ubNm9Veu7lhWxoP29J68b01HraldeE06ioqKCjArVu3MGLECP0ZR9u3b48mTZpAoVBApVIBuL/EetmT16nValy+fBmtW7dGcHCwVC/BbLAtjYdtab343hoP29K62EtdgCW4ePEiGjRoAJlMBi8vL7z66qto3rw55HI5NBoN5HI5QkJCUFBQAAcHB/336X74i4qKkJOTg3nz5uH48eNYuXIlANjkqdTZlsbDtrRefG+Nh21pxaTq+rEEmzZtEnXr1hWNGzcWbdu2Fd9++63B9rLHSocMGSJGjhwphDAc3PXzzz+L9957TwQGBoquXbuKixcvVk/xZoZtaTxsS+vF99Z42JbWjz0wD7F7927MnDkT77//PurXr49du3bhnXfegUajwbBhw+Ds7AyZTAYhBJRKJc6cOYP3338fAAzOKhoeHo6rV69i/fr1eOGFF6R6OZJiWxoP29J68b01HraljZA0Ppkh3aCt+fPni9atW4uSkhL9tnfffVe0adNGP1pd5+bNm6Ju3briwoULQgghLly4ICZPnlx9RZsptqXxsC2tF99b42Fb2hYO4n2A7pjmuXPnUL9+fTg4OOjPffHxxx/D2dkZW7duRUZGhv574uLiEBISgpo1a2LSpElo0qQJUlNTUVpaqj8vhi1iWxoP29J68b01HraljZE0PpmBXbt2iYkTJ4qlS5caLPu8evVq4eHhoT8eqkvyq1evFo0aNRL79u0TQmgT/2uvvSZq1KghfH19RdOmTcWRI0eq/XWYA7al8bAtrRffW+NhW9o2mw0waWlpom/fviIgIEAMHTpUNG/eXHh5eel/CZKTk0WtWrXEnDlzhBBCKJVK/fcGBQXpz5VRUFAg+vbtK2rXri02btxY7a/DHLAtjYdtab343hoP25KEsNEAU1BQIEaMGCEGDRpkcM6Ktm3b6keiKxQK8fHHHwsXFxeRmpoqhLh/fLVLly7irbfe0n/f0aNHq7F688K2NB62pfXie2s8bEvSsckxMK6urnBycsLIkSMRFhamX7yod+/eSEpKghACHh4eGDJkCFq1aoXXX38d165dg0wmQ2pqKrKystC/f3/947Vu3VqiVyI9tqXxsC2tF99b42Fbko5MCNscpVRaWqpftEi3mNHQoUPh5uaG1atX6/e7efMmunbtCpVKhTZt2uDQoUMIDw/Hhg0bEBgYKFX5ZoVtaTxsS+vF99Z42JYE2HCAqUjHjh0xZswYjBgxAhqNBgAgl8tx6dIlHDt2DAkJCYiIiMCIESMkrtT8sS2Nh21pvfjeGg/b0vYwwNxz5coVtG/fHr/99pu+S7GkpASOjo4SV2Z52JbGw7a0XnxvjYdtaZtscgxMWbr89ueff8Ld3V3/wz9//nxMmjQJWVlZUpZnUdiWxsO2tF58b42HbWnbbP5UArqFjw4fPoyBAwdi9+7dGDt2LAoLC/HDDz8gICBA4gotB9vSeNiW1ovvrfGwLW1c9U98Mj9FRUWiQYMGQiaTCScnJ/HZZ59JXZLFYlsaD9vSevG9NR62pe3iGJh7XnzxRTRs2BBLliyBs7Oz1OVYNLal8bAtrRffW+NhW9omBph71Gq1wVlI6cmxLY2HbWm9+N4aD9vSNjHAEBERkcWx+VlIREREZHkYYIiIiMjiMMAQERGRxWGAISIiIovDAENEREQWhwGGiIiILA4DDBEREVkcBhgikszIkSMhk8kgk8ng4OCAwMBAvPjii1i7di00Gk2lHyc2Nhbe3t6mK5SIzA4DDBFJqmfPnkhPT0dKSgp27NiB559/HpMmTULfvn2hUqmkLo+IzBQDDBFJysnJCUFBQahVqxZatWqFv//979i6dSt27NiB2NhYAMCSJUvQvHlzuLm5ISQkBO+++y7y8/MBAPv378eoUaOQl5en782ZN28eAECpVGL69OmoVasW3Nzc0K5dO+zfv1+aF0pERsUAQ0Rmp1u3boiIiMDmzZsBAHK5HCtWrMDZs2exbt067N27FzNmzAAAtG/fHsuWLYOnpyfS09ORnp6O6dOnAwAmTJiA+Ph4bNy4EadOncJrr72Gnj174uLFi5K9NiIyDp4LiYgkM3LkSOTm5mLLli3ltsXExODUqVM4d+5cuW3//e9/MW7cONy+fRuAdgzM5MmTkZubq98nNTUV9erVQ2pqKoKDg/X3d+/eHW3btsWnn35q9NdDRNXHXuoCiIgqIoSATCYDAMTFxWHhwoU4f/48FAoFVCoViouLUVhYCFdX1wq///Tp01Cr1WjUqJHB/UqlEr6+viavn4hMiwGGiMxSUlISwsLCkJKSgr59++Kdd97BJ598Ah8fH/z555948803UVJS8tAAk5+fDzs7Oxw7dgx2dnYG29zd3avjJRCRCTHAEJHZ2bt3L06fPo0pU6bg2LFj0Gg0+PLLLyGXa4ft/fjjjwb7Ozo6Qq1WG9wXGRkJtVqNrKwsdOrUqdpqJ6LqwQBDRJJSKpXIyMiAWq1GZmYmdu7ciYULF6Jv374YPnw4zpw5g9LSUnz11Vfo168fDh48iJUrVxo8Rt26dZGfn489e/YgIiICrq6uaNSoEYYOHYrhw4fjyy+/RGRkJG7duoU9e/agRYsW6NOnj0SvmIiMgbOQiEhSO3fuRM2aNVG3bl307NkT+/btw4oVK7B161bY2dkhIiICS5YswaJFi9CsWTOsX78eCxcuNHiM9u3bY9y4cRg0aBD8/f2xePFiAMB3332H4cOHY9q0aWjcuDH69++PI0eOIDQ0VIqXSkRGxFlIREREZHHYA0NEREQWhwGGiIiILA4DDBEREVkcBhgiIiKyOAwwREREZHEYYIiIiMjiMMAQERGRxWGAISIiIovDAENEREQWhwGGiIiILA4DDBEREVmc/wcCB0oIolPvuQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prior_peaks_df.plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the daily drawdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Ticker</th>\n",
       "      <th>GOOG</th>\n",
       "      <th>MSFT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>-0.011037</td>\n",
       "      <td>-0.043743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>-0.032664</td>\n",
       "      <td>-0.072085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>-0.017168</td>\n",
       "      <td>-0.061149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>-0.010033</td>\n",
       "      <td>-0.052008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker          GOOG      MSFT\n",
       "Date                          \n",
       "2023-01-03  0.000000  0.000000\n",
       "2023-01-04 -0.011037 -0.043743\n",
       "2023-01-05 -0.032664 -0.072085\n",
       "2023-01-06 -0.017168 -0.061149\n",
       "2023-01-09 -0.010033 -0.052008"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df = (wealth_index_df - prior_peaks_df) / prior_peaks_df\n",
    "drawdown_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df.plot.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the max drawdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ticker\n",
       "GOOG   -0.128125\n",
       "MSFT   -0.072085\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ticker\n",
       "GOOG   2023-02-10\n",
       "MSFT   2023-01-05\n",
       "dtype: datetime64[ns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df.idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ticker\n",
       "GOOG   -0.044264\n",
       "MSFT   -0.072085\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df.loc[\"2023-01\"].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ticker\n",
       "GOOG   2023-01-25\n",
       "MSFT   2023-01-05\n",
       "dtype: datetime64[ns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown_df.loc[\"2023-01\"].idxmin()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Defining a function to calculate the wealth index, prior peak, and drawdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def drawdown(return_series: pd.Series):\n",
    "    \"\"\"\n",
    "    Input: a time series of asset returns\n",
    "    Output: a DataFrame that contains:\n",
    "    - the wealth index\n",
    "    - the prior peaks\n",
    "    - percentage drawdowns\n",
    "    \"\"\"\n",
    "    wealth_index_series = initial_wealth*(1+return_series).cumprod()\n",
    "    prior_peaks_series = wealth_index_series.cummax()\n",
    "    drawdown_series = (wealth_index_series - prior_peaks_series) / prior_peaks_series\n",
    "    return pd.DataFrame({\n",
    "    \"Wealth index\": wealth_index_series,\n",
    "    \"Prior peaks\": prior_peaks_series,\n",
    "    \"Drawdown\": drawdown_series\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Wealth index</th>\n",
       "      <th>Prior peaks</th>\n",
       "      <th>Drawdown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>988.963277</td>\n",
       "      <td>988.963277</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>967.335599</td>\n",
       "      <td>988.963277</td>\n",
       "      <td>-0.021869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>982.831783</td>\n",
       "      <td>988.963277</td>\n",
       "      <td>-0.006200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>989.966616</td>\n",
       "      <td>989.966616</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Wealth index  Prior peaks  Drawdown\n",
       "Date                                           \n",
       "2023-01-03           NaN          NaN       NaN\n",
       "2023-01-04    988.963277   988.963277  0.000000\n",
       "2023-01-05    967.335599   988.963277 -0.021869\n",
       "2023-01-06    982.831783   988.963277 -0.006200\n",
       "2023-01-09    989.966616   989.966616  0.000000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df[\"GOOG\"]).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df[\"GOOG\"])[['Wealth index', 'Prior peaks']].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df.loc[\"2023-01\",\"GOOG\"])[['Wealth index', 'Prior peaks']].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2023-01-19 00:00:00')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df[\"GOOG\"])['Drawdown'].min()\n",
    "drawdown(returns_df[\"GOOG\"])['Drawdown'].idxmin()\n",
    "drawdown(returns_df[\"MSFT\"])['Drawdown'].min()\n",
    "drawdown(returns_df[\"MSFT\"])['Drawdown'].idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.04426431835618261"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df.loc[\"2023-01\",\"GOOG\"])['Drawdown'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.03503220376005605"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drawdown(returns_df.loc[\"2023-01\",\"MSFT\"])['Drawdown'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Backtesting the Trend-Following Strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-03</th>\n",
       "      <td>144.909592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>144.252350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>137.497040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>137.394653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>136.848770</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Adj Close\n",
       "Date                  \n",
       "2022-01-03  144.909592\n",
       "2022-01-04  144.252350\n",
       "2022-01-05  137.497040\n",
       "2022-01-06  137.394653\n",
       "2022-01-07  136.848770"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_goog = yf.download(['GOOG'], start=\"2022-01-01\", end=\"2023-01-01\")['Adj Close']\n",
    "df_goog = pd.DataFrame(df_goog)\n",
    "df_goog.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the short and long moving averages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Adj Close</th>\n",
       "      <th>sma30</th>\n",
       "      <th>ema5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-03</th>\n",
       "      <td>144.909592</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.909592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-04</th>\n",
       "      <td>144.252350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>144.515247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05</th>\n",
       "      <td>137.497040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>141.190833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06</th>\n",
       "      <td>137.394653</td>\n",
       "      <td>NaN</td>\n",
       "      <td>139.613958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>136.848770</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138.552441</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Adj Close  sma30        ema5\n",
       "Date                                     \n",
       "2022-01-03  144.909592    NaN  144.909592\n",
       "2022-01-04  144.252350    NaN  144.515247\n",
       "2022-01-05  137.497040    NaN  141.190833\n",
       "2022-01-06  137.394653    NaN  139.613958\n",
       "2022-01-07  136.848770    NaN  138.552441"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sma_span = 30\n",
    "ema_span = 5\n",
    "short_ma = 'ema'+str(ema_span)\n",
    "long_ma ='sma'+str(sma_span)\n",
    "df_goog[long_ma] = df_goog['Adj Close'].rolling(sma_span).mean()\n",
    "df_goog[short_ma] = df_goog['Adj Close'].ewm(span=ema_span).mean()\n",
    "df_goog.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_goog.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1174d2d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14,7))\n",
    "plt.plot(df_goog.index, df_goog['Adj Close'], linewidth=1.5, label='Daily Adj Close')\n",
    "plt.plot(df_goog.index, df_goog[long_ma], linewidth=2, label=long_ma)\n",
    "plt.plot(df_goog.index, df_goog[short_ma], linewidth=2, label=short_ma)\n",
    "plt.title(\"Trend following strategy\")\n",
    "plt.ylabel('Price($)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the log returns of the buy-and-hold strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_goog['log_return_buy_n_hold'] = np.log(df_goog['Adj Close'] / df_goog['Adj Close'].shift(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### An equivalent way of calculating the log returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_goog['log_return_buy_n_hold'] = np.log(df_goog['Adj Close']).diff()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Creating the signal column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Adj Close</th>\n",
       "      <th>sma30</th>\n",
       "      <th>ema5</th>\n",
       "      <th>log_return_buy_n_hold</th>\n",
       "      <th>signal</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-02-15</th>\n",
       "      <td>136.270432</td>\n",
       "      <td>136.891673</td>\n",
       "      <td>136.696001</td>\n",
       "      <td>0.008284</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-16</th>\n",
       "      <td>137.331223</td>\n",
       "      <td>136.660968</td>\n",
       "      <td>136.907742</td>\n",
       "      <td>0.007754</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-17</th>\n",
       "      <td>132.158112</td>\n",
       "      <td>136.483004</td>\n",
       "      <td>135.324530</td>\n",
       "      <td>-0.038397</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-18</th>\n",
       "      <td>130.319199</td>\n",
       "      <td>136.247156</td>\n",
       "      <td>133.656084</td>\n",
       "      <td>-0.014012</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-22</th>\n",
       "      <td>129.255417</td>\n",
       "      <td>135.994044</td>\n",
       "      <td>132.189194</td>\n",
       "      <td>-0.008196</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Adj Close       sma30        ema5  log_return_buy_n_hold  signal\n",
       "Date                                                                         \n",
       "2022-02-15  136.270432  136.891673  136.696001               0.008284      -1\n",
       "2022-02-16  137.331223  136.660968  136.907742               0.007754       1\n",
       "2022-02-17  132.158112  136.483004  135.324530              -0.038397      -1\n",
       "2022-02-18  130.319199  136.247156  133.656084              -0.014012      -1\n",
       "2022-02-22  129.255417  135.994044  132.189194              -0.008196      -1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# identify buy signal\n",
    "df_goog['signal'] = np.where(df_goog[short_ma] > df_goog[long_ma], 1, 0)\n",
    "# identify sell signal\n",
    "df_goog['signal'] = np.where(df_goog[short_ma] < df_goog[long_ma], -1, df_goog['signal'])\n",
    "df_goog.dropna(inplace=True)\n",
    "df_goog.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the periodic log returns of the buy-and-hold strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_goog['log_return_trend_follow'] = df_goog['signal'] * df_goog['log_return_buy_n_hold']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating terminal returns of both strategies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nr/kmlljdx179d88t_l2f30j48h0000gr/T/ipykernel_30148/2158012264.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  np.exp(df_goog['log_return_buy_n_hold']).cumprod()[-1] - 1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-0.34419803132954907"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# terminal return of buy-n-hold\n",
    "np.exp(df_goog['log_return_buy_n_hold']).cumprod()[-1] - 1\n",
    "\n",
    "# another way to calculate\n",
    "np.exp(df_goog['log_return_buy_n_hold']).prod() - 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/nr/kmlljdx179d88t_l2f30j48h0000gr/T/ipykernel_30148/3491466339.py:2: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  np.exp(df_goog['log_return_trend_follow']).cumprod()[-1] -1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.36091483998550555"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# terminal return of trend following\n",
    "np.exp(df_goog['log_return_trend_follow']).cumprod()[-1] -1\n",
    "\n",
    "# another way to calculate\n",
    "np.exp(df_goog['log_return_trend_follow']).prod() - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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>Adj Close</th>\n",
       "      <th>sma30</th>\n",
       "      <th>ema5</th>\n",
       "      <th>log_return_buy_n_hold</th>\n",
       "      <th>signal</th>\n",
       "      <th>log_return_trend_follow</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-02-15</th>\n",
       "      <td>136.270432</td>\n",
       "      <td>136.891673</td>\n",
       "      <td>136.696001</td>\n",
       "      <td>0.008284</td>\n",
       "      <td>-1</td>\n",
       "      <td>-0.008284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-16</th>\n",
       "      <td>137.331223</td>\n",
       "      <td>136.660968</td>\n",
       "      <td>136.907742</td>\n",
       "      <td>0.007754</td>\n",
       "      <td>1</td>\n",
       "      <td>0.007754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-17</th>\n",
       "      <td>132.158112</td>\n",
       "      <td>136.483004</td>\n",
       "      <td>135.324530</td>\n",
       "      <td>-0.038397</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.038397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-18</th>\n",
       "      <td>130.319199</td>\n",
       "      <td>136.247156</td>\n",
       "      <td>133.656084</td>\n",
       "      <td>-0.014012</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.014012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-22</th>\n",
       "      <td>129.255417</td>\n",
       "      <td>135.994044</td>\n",
       "      <td>132.189194</td>\n",
       "      <td>-0.008196</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.008196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-23</th>\n",
       "      <td>89.707916</td>\n",
       "      <td>95.385788</td>\n",
       "      <td>89.768078</td>\n",
       "      <td>0.017409</td>\n",
       "      <td>-1</td>\n",
       "      <td>-0.017409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-27</th>\n",
       "      <td>87.830055</td>\n",
       "      <td>95.092788</td>\n",
       "      <td>89.122071</td>\n",
       "      <td>-0.021155</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.021155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-28</th>\n",
       "      <td>86.361725</td>\n",
       "      <td>94.774151</td>\n",
       "      <td>88.201955</td>\n",
       "      <td>-0.016859</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.016859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-29</th>\n",
       "      <td>88.848892</td>\n",
       "      <td>94.448855</td>\n",
       "      <td>88.417601</td>\n",
       "      <td>0.028393</td>\n",
       "      <td>-1</td>\n",
       "      <td>-0.028393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-30</th>\n",
       "      <td>88.629150</td>\n",
       "      <td>94.107244</td>\n",
       "      <td>88.488117</td>\n",
       "      <td>-0.002476</td>\n",
       "      <td>-1</td>\n",
       "      <td>0.002476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>221 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Adj Close       sma30        ema5  log_return_buy_n_hold  signal  \\\n",
       "Date                                                                            \n",
       "2022-02-15  136.270432  136.891673  136.696001               0.008284      -1   \n",
       "2022-02-16  137.331223  136.660968  136.907742               0.007754       1   \n",
       "2022-02-17  132.158112  136.483004  135.324530              -0.038397      -1   \n",
       "2022-02-18  130.319199  136.247156  133.656084              -0.014012      -1   \n",
       "2022-02-22  129.255417  135.994044  132.189194              -0.008196      -1   \n",
       "...                ...         ...         ...                    ...     ...   \n",
       "2022-12-23   89.707916   95.385788   89.768078               0.017409      -1   \n",
       "2022-12-27   87.830055   95.092788   89.122071              -0.021155      -1   \n",
       "2022-12-28   86.361725   94.774151   88.201955              -0.016859      -1   \n",
       "2022-12-29   88.848892   94.448855   88.417601               0.028393      -1   \n",
       "2022-12-30   88.629150   94.107244   88.488117              -0.002476      -1   \n",
       "\n",
       "            log_return_trend_follow  \n",
       "Date                                 \n",
       "2022-02-15                -0.008284  \n",
       "2022-02-16                 0.007754  \n",
       "2022-02-17                 0.038397  \n",
       "2022-02-18                 0.014012  \n",
       "2022-02-22                 0.008196  \n",
       "...                             ...  \n",
       "2022-12-23                -0.017409  \n",
       "2022-12-27                 0.021155  \n",
       "2022-12-28                 0.016859  \n",
       "2022-12-29                -0.028393  \n",
       "2022-12-30                 0.002476  \n",
       "\n",
       "[221 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_goog"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the annualized return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.3818823406949291"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate annualized return of buy-n-hold\n",
    "annualized_return_buy_n_hold = np.exp(df_goog['log_return_buy_n_hold']).prod()**(252/df_goog.shape[0])-1\n",
    "annualized_return_buy_n_hold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.42103121194126136"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate annualized return of trend following\n",
    "annualized_return_trend_follow = np.exp(df_goog['log_return_trend_follow']).prod()**(252/df_goog.shape[0])-1\n",
    "annualized_return_trend_follow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we can also add up all the log returns and exponentiate the sum to get the\n",
    "same result:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4210312119412587"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.exp(df_goog['log_return_trend_follow'].sum())**(252/df_goog.shape[0])-1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the annualized volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3896836126348582"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate annualized volatility of buy-n-hold\n",
    "annualized_vol_buy_n_hold = (np.exp(df_goog['log_return_buy_n_hold'])-1).std()*(252**0.5)\n",
    "annualized_vol_buy_n_hold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3928554568061577"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# calculate annualized volatility of trend following\n",
    "annualized_vol_trend_follow = (np.exp(df_goog['log_return_trend_follow'])-1).std()*(252**0.5)\n",
    "annualized_vol_trend_follow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the Sharpe ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.056966029210142"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "riskfree_rate = 0.03\n",
    "# calculate Sharpe ratio of buy-n-hold\n",
    "sharpe_ratio_buy_n_hold = (annualized_return_buy_n_hold - riskfree_rate) / annualized_vol_buy_n_hold\n",
    "sharpe_ratio_buy_n_hold\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9953564476875869"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate Sharpe ratio of trend following\n",
    "sharpe_ratio_trend_follow = (annualized_return_trend_follow - riskfree_rate) / annualized_vol_trend_follow\n",
    "sharpe_ratio_trend_follow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Calculating the max drawdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.4187653906097545"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# max drawdown of buy-n-hold\n",
    "max_drawdown_buy_n_hold = drawdown(np.exp(df_goog['log_return_buy_n_hold'])-1)['Drawdown'].min()\n",
    "max_drawdown_buy_n_hold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.20685356966801752"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# max drawdown of trend following\n",
    "max_drawdown_trend_follow = drawdown(np.exp(df_goog['log_return_trend_follow'])-1)['Drawdown'].min()\n",
    "max_drawdown_trend_follow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##########################################################################################################################################"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}