4-quant_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quantitative Analysis of Price & Daily Returns\n",
    "* Can returns be described with a normal distribution?\n",
    "* Is daily change non-zero?\n",
    "* Can price movement be described as a random walk?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Set up environment "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.figsize'] = 8, 6\n",
    "import seaborn as sb\n",
    "sb.set()\n",
    "import pandas_datareader as pdr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.  Download stock price data, store in dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "amzn = pdr.get_data_yahoo('AMZN')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Take a look at the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</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>2016-06-03</th>\n",
       "      <td>727.000000</td>\n",
       "      <td>718.429993</td>\n",
       "      <td>726.739990</td>\n",
       "      <td>725.539978</td>\n",
       "      <td>3367300</td>\n",
       "      <td>725.539978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-06</th>\n",
       "      <td>731.500000</td>\n",
       "      <td>724.419983</td>\n",
       "      <td>726.500000</td>\n",
       "      <td>726.729980</td>\n",
       "      <td>2704800</td>\n",
       "      <td>726.729980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-07</th>\n",
       "      <td>730.000000</td>\n",
       "      <td>720.549988</td>\n",
       "      <td>729.890015</td>\n",
       "      <td>723.739990</td>\n",
       "      <td>2732500</td>\n",
       "      <td>723.739990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>729.419983</td>\n",
       "      <td>721.599976</td>\n",
       "      <td>726.400024</td>\n",
       "      <td>726.640015</td>\n",
       "      <td>2223400</td>\n",
       "      <td>726.640015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>728.909973</td>\n",
       "      <td>722.299988</td>\n",
       "      <td>723.099976</td>\n",
       "      <td>727.650024</td>\n",
       "      <td>2170300</td>\n",
       "      <td>727.650024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  High         Low        Open       Close   Volume  \\\n",
       "Date                                                                  \n",
       "2016-06-03  727.000000  718.429993  726.739990  725.539978  3367300   \n",
       "2016-06-06  731.500000  724.419983  726.500000  726.729980  2704800   \n",
       "2016-06-07  730.000000  720.549988  729.890015  723.739990  2732500   \n",
       "2016-06-08  729.419983  721.599976  726.400024  726.640015  2223400   \n",
       "2016-06-09  728.909973  722.299988  723.099976  727.650024  2170300   \n",
       "\n",
       "             Adj Close  \n",
       "Date                    \n",
       "2016-06-03  725.539978  \n",
       "2016-06-06  726.729980  \n",
       "2016-06-07  723.739990  \n",
       "2016-06-08  726.640015  \n",
       "2016-06-09  727.650024  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Store instantaneous rate of return in separate series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2016-06-06    0.16\n",
       "2016-06-07   -0.41\n",
       "2016-06-08    0.40\n",
       "2016-06-09    0.14\n",
       "2016-06-10   -1.35\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn_return = round(np.log(amzn.Close).diff() * 100, 2)\n",
    "amzn_return.dropna(inplace = True)\n",
    "amzn_return.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. Plot the series "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "amzn_return[-252:].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. Pandas describe function gives descriptive statistics, default assumes you are dealing with a sample Pandas also deals with missing values by omitting them "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1257.000000\n",
       "mean        0.118767\n",
       "std         1.828797\n",
       "min        -8.250000\n",
       "25%        -0.710000\n",
       "50%         0.150000\n",
       "75%         1.040000\n",
       "max        12.410000\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn_return.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7. An alternative more slightly  different table of descriptives from scipy stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "n, minmax, mean, var, skew, kurt = stats.describe(amzn_return)\n",
    "mini, maxi = minmax\n",
    "std = var ** .5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9. for comparision generate random numbers that follow normal distribution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = norm.rvs(mean, std, n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DescribeResult(nobs=1257, minmax=(-5.667586139363219, 6.6025928351128975), mean=0.10969789971833238, variance=3.3950973838450786, skewness=0.04822423578358121, kurtosis=-0.11797296454092399)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.describe(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  3.,  16.,  19.,  66., 131., 165., 224., 219., 156., 131.,  78.,\n",
       "         32.,  12.,   4.,   1.]),\n",
       " array([-5.66758614, -4.84957421, -4.03156228, -3.21355034, -2.39553841,\n",
       "        -1.57752648, -0.75951455,  0.05849738,  0.87650931,  1.69452125,\n",
       "         2.51253318,  3.33054511,  4.14855704,  4.96656897,  5.7845809 ,\n",
       "         6.60259284]),\n",
       " <BarContainer object of 15 artists>)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(x, bins=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(amzn_return, bins = 15)\n",
    "plt.xlim(-6,6);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Is price change normally distributed?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 10. Use scipy stats to test the kurtosis, the null hypothesis is that the sample is drawn from a population where the underlying kurtosis is that of a normally distributed variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Test statistic         p-value\n",
      "     ------------------------------\n",
      "x:            -0.81          0.4168\n",
      "AMZN:         11.47          0.0000\n"
     ]
    }
   ],
   "source": [
    "x_test = stats.kurtosistest(x)\n",
    "amzn_test = stats.kurtosistest(amzn_return)\n",
    "print(f'{\"     Test statistic\":20}{\"p-value\":>15}')\n",
    "print(f'{\" \"*5}{\"-\"* 30}')\n",
    "print(f\"x:{x_test[0]:>17.2f}{x_test[1]:16.4f}\")\n",
    "print(f\"AMZN: {amzn_test[0]:13.2f}{amzn_test[1]:16.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 11. plot histogram of price changes with normal curve overlay\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0OIMZUT/oXefgOVaBL/zjh+R0rd7Ua8moVZPwA8cR0zIQ0dBhWRP1g3rkc8DQUe4bZ3YU7PGPx2i5GaniObOjENEgY1kT9YNy+DPY08ahUR9udhTs9Y2FZgi4wXHU7ChENMhY1kR9pJ87Db3pGOKzrXFWQ7sRixolA7n2oxDAUxyJIhnLmqiPlMNlgCAgfsocs6ME7PGPQ5LUhWvkM2ZHIaJBxLIm6gPDMKAcKoOUMQVyQpLZcQIq/Vno0m24gQeaEUU0ljVRH+iNR2C0N8E2Ic/sKD0okLHPPwbT7Sdhh2J2HCIaJCxroj5QDpcBkg3y2Fyzo1xij38cHIKK6faTZkchokHCsiYKwtBVqEe+gDx6JgR7rNlxLnFUdeOsFo9cHhVOFLFY1kRBaLVVMLztsE240ewovRCwzz8a18hnECv4zA5DRIOAZU0UhHK4DHDEQcqaZnaUXu33j4YkGJhqqzU7ChENApY10RUYmgL1xD7Yxl4PQerTVPqmOKWloFVz8ntrogjFsia6Aq3+IKB4IY8x5wpbfWVAwAFlFCbZ6nlUOFEEYlkTXYF6/EvAFgMpY7LZUYI64B8Fu6Bhsq3e7ChEFGIsa6JeGIYO9fhXkLOmQZDtZscJ6qjqRofuQA6HwokiDsuaqBd641EYnjbIY64zO0qf6BBR4c/CVFstJGhmxyGiEGJZE/VCPf4lIEiQs3LMjtJnB5RRiBUVXGvjXOFEkYRlTXQZhmFAOb4XUuZkCI44s+P02TdKOryGDTk2DoUTRRKWNdFl6OdOw2hrCJsh8ItUSKjyZ2Ka/RQE6GbHIaIQYVkTXYZ6/EsAgDx6pslJ+u+AfxQSRC/GyU1mRyGiEGFZE12GevxLiK5xEOOscznMvqpWMqEYIo8KJ4ogLGui79E7W6E3HQ27IfCL/LChRsnANNtJAIbZcYgoBFjWRN+jnvgKAMK2rAGgShmJFKkTqWKb2VGIKARY1kTfox7/EsLwNIiJ6WZHuWoHlUwAwFQ7L+xBFAlY1kTfYfg90OoPQh49A4IgmB3nqp3T41CnJmGKrc7sKEQUAixrou9Q6w8CugZ51HSzowxYtZKJcXIjYgS/2VGIaIBY1kTfoZ080H3hjtRrzI4yYNVKJiTBwCSZF/YgCncsa6ILDMOAeuoA5Myplr52dV8dV13o1O2YYudQOFG4Y1kTXaC31sHobIE0KnzmAr8SHSJqlAxMsdVB4ClcRGGNZU10gXbqAACE1YU7gqlWRiJB9CJLajY7ChENAMua6AL15AGIyVlhOWtZbw4qGdANYApP4SIKayxrIlw4ZevMIcgRMgR+UacRgxPaCJ7CRRTmWNZEANS6KsDQIEXQEPhF1f6RGC03I0HwmB2FiK4Sy5oIF07ZssdCSp1gdpSQq74wm9lk7l0ThS2WNUW9wClbI7MhiJLZcUKuVktGmx7LoXCiMMaypqint5yC0XUuoo4C70lAtT8TE231EKGbHYaIrgLLmqKeeuGULSlrmslJBk+NkgGnqGCUfNbsKER0FVjWFPW0kwcgjhgN0ZlodpRB842aDt0QMNnGqUeJwhHLmqKa4e+C1nA4gofAu3UZDpzUUjCRZU0UlljWFNXU+oOAoUMamW12lEFXo2RgtNQMzdNhdhQi6ieWNUU1rbbqwlW2xpsdZdDVKBkQBQOe4wfMjkJE/cSypqim1lZCzpgMQQz/q2wFc0IdAY9ug+fofrOjEFE/9amsS0pKsHDhQsybNw8bN27sdb3HH38cW7ZsCSwXFxdjzpw5KCoqQlFREdavXz/wxEQhop9vhHG+EdLIqWZHGRI6RHyjpqPr6D4YBq/CRRROgu5ONDQ0YP369diyZQvsdjvuu+8+zJo1CxMmTOixztq1a1FWVoa8vLzA7ZWVlVizZg0WLVo0OOmJBkCtrQQAyFHwffVFNUoGpp//DHrbaUiJGWbHIaI+CrpnvXv3buTl5SExMRFOpxMFBQUoLS3tsU5JSQl+9KMfYcGCBT1ur6ioQHFxMQoLC/HYY4+hra0ttOmJBkCrrYSQMALCsFSzowyZGiUdAKCdqjQ5CRH1R9CybmxshMvlCiy73W40NDT0WGf58uW45557LtnW5XJh5cqV2L59O9LT0/HMM8+EIDLRwBm6CrXuIOTMbAiCYHacIdOiJ8CWnB4YVSCi8BB0GFzX9R4fZoZh9PnDbcOGDYH/X758OebOnduvcCkp8f1an67M5UowO4JleE/VoEPxIGlqLuKj7O8ldtwMtO/7C0YkxUCQbWbHMRXfE9bA5yG4oGWdlpaG8vLywHJTUxPcbnfQB25vb8f777+PBx54AEB3yUtS/y6S0NzcAV3ngTCh4HIloKmp3ewYluGr/AIQBHTFj4Wnn38v4f7BEjt2Os6X/wlnKr+EnDnF7Dim4XvCGvg8fEsUhV53UoMOg8+ePRtlZWVoaWmBx+PBzp07kZ+fH/SHOp1OvPnmm9i/v/s0kXfeeaffe9ZEg0WtrYToHg/BEWd2lCEXOyYbECVoHAonChtByzo1NRWrVq3CsmXLsHjxYixatAg5OTlYsWIFKioqet1OkiS8/PLLWLduHRYsWICqqiqsXr06pOGJrobh64TedBRyZnScsvV94oXrdqu1vb9/icha+jQTRGFhIQoLC3vc9sYbb1yy3vPPP99jOTc3F8XFxQOIRxR6al01YBhRdcrW90kjp8G/5/fQu9ogOoebHYeIguAMZhR1uqcYjYXoHmd2FNPIFyaC0eqqTE5CRH3BsqaoYhgG1NoKyJlTIIj9O+AxkogpowFHHFSWNVFYYFlTVDHON8DoaI6aKUZ7I4gi5Mwp0GqrOPUoURhgWVNUUWu79ySj+fvqi6TMqTC6zkE/d9rsKEQUBMuaoopWV9U9xWiCK/jKEe7i0fD83prI+ljWFDUMXbswxejUqJpitDfiMBeEYW5OPUoUBljWFDX0pmOA4on676u/S86cCu301zB01ewoRHQFLGuKGt3fVwuQM6J3is3vk0ZOBRQvtIYjZkchoitgWVPU0OqqII4YDSGGF4i5SM6YDAgCv7cmsjiWNUUFw++B1nAkMBkIdRMccRBdYwNHyRORNbGsKSpop78GDA1SlM4HfiVy5lToTUdh+DrNjkJEvWBZU1RQ66oAyQ4p7Rqzo1iONDIbMAyop2vMjkJEvWBZU1TQaqsgpV8LQbKZHcVyJPd4QHZ0z5lORJbEsqaIp3e0QD9XH7WXxAxGkGRI6RM5TziRhbGsKeJdPNKZ51f3Th45FUZbA/T2s2ZHIaLLYFlTxFPrqiDEDoOYPNLsKJYlZXbPlc69ayJrYllTRDMMA1pdNaTMKRAEvtx7IyZlQHAm8ntrIovipxdFNL2lFobnPL+vDkIQBEgjp0Ktq4Kh62bHIaLvYVlTRNMuXKSC51cHJ2dOBXyd0JtPmB2FiL6HZU0RTa2rgpiYATE+2ewolnfxHzSczYzIemSzAxANFkP1Qzv9NWyTbw3cljAsFjEOvuwvR3QOh5ic1X30/MxFZschou/gpxZFLO3MIUBTeswHHuOQUfjotgE9bsmLRQONZlnSyKlQKj+EofogyA6z4xDRBRwGp4il1VUBogQpfZLZUcKGnDkV0NXuudSJyDJY1hSx1NoqSKkTINhizI4SNqT0awFJ5vfWRBbDsqaIpHvOQ28+waPA+0mQHZDSruX1rYkshmVNEUmrqwYAyCOzTU4SfqTMqdBbaqF3nTM7ChFdwLKmiKTWVgKOOIgjxpgdJexcPCCPs5kRWQfLmiJO9xSjVZAzJkMQ+RLvLzFlFISYBM4TTmQh/CSjiKOfOw2jsxUSh8CviiCIkDImQ6urhmEYZschIrCsKQJdnGJU5iUxr5o8MhtG1znorXVmRyEisKwpAql1VRCGp0JMcJkdJWxdHJXQaitMTkJEAMuaIoyhqdDqa3iVrQES45MhJmVAPVVpdhQiAsuaIozWcBhQfZA4BD5g0shp0M58DUP1mR2FKOqxrCmiaLWVgCBBzphidpSwJ4/MBjROPUpkBSxriijqqQpIaRMg2GPNjhL2pPSJgGTjUDiRBbCsKWLoXW3dU4yOnGZ2lIggyHZI6RMDR9cTkXlY1hQxAqdsZfH86lCRR2ZDP1cPvaPZ7ChEUY1lTRFDra2AEDsMYsoos6NEjIujFOopnsJFZCaWNUUEw9Ch1VZBGpkNQeDLOlTEpAwIcckcCicyGT/VKCLoZ0/A8LbzKlshJggC5JHZUOuqYOia2XGIohbLmiJC9zCtwPnAB4GUlQ34PdAbj5odhShq9amsS0pKsHDhQsybNw8bN27sdb3HH38cW7ZsCSzX19fj/vvvx/z58/HQQw+hs7Nz4ImJLkM7VQHRNQZi7DCzo0QcOXMqIAjdlx0lIlMELeuGhgasX78emzZtwtatW/Hee+/h8OHDl6zz4IMPYseOHT1uf/rpp7F06VKUlpYiOzsbr776amjTEwEwfJ3QGo9wCHyQCI44iK5xUDlPOJFpgpb17t27kZeXh8TERDidThQUFKC0tLTHOiUlJfjRj36EBQsWBG5TFAV79uxBQUEBAGDJkiWXbEcUCmpdNWDokLJ4fvVgkUdmQ286BsPbYXYUoqgUtKwbGxvhcn179SK3242GhoYe6yxfvhz33HNPj9taW1sRHx8PWZYBAC6X65LtiEJBq60A7LGQ3OPNjhKx5KxpgGFArasyOwpRVJKDraDrOgRBCCwbhtFjuTeXW68v231XSkp8v9anK3O5EsyOEHKGYeBkfTWcY3PgTk00O07Y6O9rwUjJwYmdCZAbq+HKu32QUg29SHxPhCM+D8EFLeu0tDSUl5cHlpuamuB2u4M+cHJyMtrb26FpGiRJ6vN239Xc3AFdN/q1DV2ey5WApqZ2s2OEnNZaB+38WWjTF/Xp9+OHQrereS2ImdnoPPQlGhvbIuJc9kh9T4QbPg/fEkWh153UoO+42bNno6ysDC0tLfB4PNi5cyfy8/OD/lCbzYbc3Fx88MEHAICtW7f2aTui/tBOHQBwYZiWBpU8ajoMbzv0pmNmRyGKOkHLOjU1FatWrcKyZcuwePFiLFq0CDk5OVixYgUqKq58dOjatWuxefNmLFy4EOXl5XjkkUdClZsIAKCe2A8xeSTE+BSzo0Q8eWR29ylcJ/ebHYUo6gQdBgeAwsJCFBYW9rjtjTfeuGS9559/vsdyZmYm3n777QHEI+qd4euEduYQ7NMXBF+ZBkyIiYfkngD15H44cpeYHYcoqoT/F08UtdTaKsDQII2abnaUqCGNmg797AnoXefMjkIUVVjWFLbUk/sARxxP2RpC8qgcAIB28oDJSYiiC8uawpKh69BOVUDOyoEg8mU8VMTkLAhxyfzemmiI8VOOwpLedLT7KlscAh9SgiBAzsrpvgqXppodhyhqsKwpLKkn9wOCyFO2TCCNygEUL7Qz35gdhShqsKwpLKkn90FKuwaCI87sKFFHzpwCiDKHwomGEMuawo7e0Qy9+RSHwE0i2GIgZUyCxrImGjIsawo76oUjkaVRM8wNEsXkUdOht52Bfr7R7ChEUYFlTWFHPbkPQoILYmK62VGilpzVfQqXemKfuUGIogTLmsKKofqh1R2EPGp6v6/iRqEjDk+FmJQB9cRXZkchigosaworWv1BQPNDHj3D7ChRTx5zPbTTX8PwdpgdhSjisawprKjHvwJsMZDSJ5odJerJY64DDL17JjkiGlQsawobhq5DPfFl96xlks3sOFFPHDEGQlwS1ONfmh2FKOKxrClsaI2HYXjOQx57vdlRCBdmMxt9HdRTlTBUn9lxiCIay5rChnpsLyDKgSORyXzymOsAzd99BTQiGjQsawoLhmFAPb4X0sipEOyxZsehC6SMiYDdyaFwokHGsqawoDefhNF+tntPjixDEGXIo6ZDO7EPhq6ZHYcoYrGsKSyox/cCggB59Eyzo9D3yGOug+Hr4IU9iAYRy5rCgnpsL6S0ayHGDjM7Cn2PnDUNkGQOhRMNIpY1WZ5+7gz01jrIY3PNjkKXIdhiIGVOhXr8SxiGYXYcoojEsibLU47vBQB+X21htjHXw+hoht580uwoRBGJZU2Wpx7fC9E1FmJ8itlRqBfS6BmAIEA9Vm52FKKIxLImS9M7W6E3HoU8hhOhWJkYOwxS+iQoR/dwKJxoEMhmByC6EvXiEPhYDoGHil/R4HIlDOgxvD4V7ec9PW6Tx8+C7+O3oDefhDRi9IAen4h6YlmTpalHvoCYlAEpMcPsKBHDbpNQ+Oi2AT1GyYtFaP/ebbaxufB98jbUI5+zrIlCjMPgZFl6RzO0M99AHp9ndhTqAyEmHtLIqVCOfM6hcKIQY1mTZalHPgcA2CawrMOFbfys7qPCG4+YHYUoorCsybKUw59DdI2DOMxtdhTqI3nMTECSoVz4hxYRhQbLmixJa62H3nyCe9VhRrA7IWflQD26B4aumx2HKGKwrMmS1COfdc8FPv4HZkehfpLHz4LRdY5zhROFEMuaLMcwDCiHP4eUMRmiM9HsONRP8qgZgGwPHHNARAPHsibL0ZuOwTjfABuPAg9Lgs0BedQMqMfKedlMohDhedZkOcqRzwFRhjz20lnLEobFIsbBl63VyRNmQT36BbT6g5BHZpsdhyjs8VOPLMXQdahHPoc8KgeCI+6S+2Mc8oAm9Ch5sWgg8aiP5JHTAFsslENlLGuiEOAwOFmKduZrGF3nOBFKmBNkO2zjZ0E9tgeG3xN8AyK6IpY1WYp6qAywxUAePd3sKDRAtolzANUP5egXZkchCnssa7IMQ/FCOfoF5LG5EGSH2XFogET3eIiJGVC+/tjsKERhj2VNlqEc+RxQvLBPusXsKBQCgiDANvFm6A2HoZ2rNzsOUVhjWZNlKDV/g5iYATF1gtlRKETka2YDggj160/MjkIU1ljWZAlaSy30xiOwTcqHIAhmx6EQEZ3DIY+aDuWbT2DoqtlxiMIWy5osQan5GyBK3XtiFFFsE/NheM5DO1VhdhSisMWyJtMZqh/KoU8hj7keYuwws+NQiEmjpkGIHcYDzYgGoE9lXVJSgoULF2LevHnYuHHjJfcfPHgQS5YsQUFBAZ588kmoavdwV3FxMebMmYOioiIUFRVh/fr1oU1PEUE9/iXg64RtUr7ZUWgQCKIM+ZrZUE/sh97VZnYcorAUtKwbGhqwfv16bNq0CVu3bsV7772Hw4cP91hn9erV+Jd/+Rfs2LEDhmFg8+bNAIDKykqsWbMG27Ztw7Zt27Bq1arB+S0orClf/w1CfAqkzClmR6FBYpt4M2BoUA/vNjsKUVgKWta7d+9GXl4eEhMT4XQ6UVBQgNLS0sD9dXV18Hq9mDFjBgBgyZIlgfsrKipQXFyMwsJCPPbYY2hr47+qqSf9fCO0uuoLB5bxW5lIJSVlQkydAP/B/4Jh8DrXRP0V9NOxsbERLpcrsOx2u9HQ0NDr/S6XK3C/y+XCypUrsX37dqSnp+OZZ54JZXaKAErN3wBBgO3am82OQoPMPvV2GG0NPNCM6CoEvZCHrus9TqUxDKPH8pXu37BhQ+D25cuXY+7cuf0Kl5IS36/16cpcrgSzI/Sgq36cOvQxnOOvQ+rY0WbHoX7q7+vJSL4NJ7/YDHzzV7iunzNIqfrHau+JaMXnIbigZZ2Wloby8vLAclNTE9xud4/7m5qaAstnz56F2+1Ge3s73n//fTzwwAMAuktckqR+hWtu7oCuG/3ahi7P5UpAU1O72TF6UGr+Bq2zDcbEH/U5G9/U1nE1rydp0q3wlG/BmW++hpSUMQip+s6K74loxOfhW6Io9LqTGnQYfPbs2SgrK0NLSws8Hg927tyJ/Pxvj9rNzMyEw+HA3r17AQDbtm1Dfn4+nE4n3nzzTezfvx8A8M477/R7z5oil2EY8FfsgJicBSljstlxaIjYJt8KSDKUyj+bHYUorAQt69TUVKxatQrLli3D4sWLsWjRIuTk5GDFihWoqOj+7umXv/wlnnvuOcyfPx9dXV1YtmwZJEnCyy+/jHXr1mHBggWoqqrC6tWrB/0XovCg1VVBb62DPaeAM5ZFETF2GGwTboRy6FMYvk6z4xCFjaDD4ABQWFiIwsLCHre98cYbgf+fNGkSfv/731+yXW5uLoqLiwcYkSKR/0AphNjhkMfPMjsKDTFb9jwoX38MpWYX7NMXmh2HKCzwXBkaclpLLbTaStiyb4cg2cyOQ0NMSsmClD4J/qq/wNA1s+MQhQWWNQ05pWIHINlhn3yb2VHIJLZpc2F0NHfPXkdEQbGsaUjpXW1QDpXBNnEOhBiemhet5FEzISS44K/onvWQiK6MZU1DSqn+K6CrsGfPMzsKmUgQRdhz5kNvOAytrtrsOESWx7KmIWP4PVCq/gJp1AyIiWlmxyGT2SblQ4hLgn/vVu5dEwXBsqYh46/cCcPXAcf1RWZHIQsQJBvsMxZBazjEvWuiIPp06hbRQBneDvj3lyJmwg1Im5JjdhyyCNukfPj3/RG+vcWQMqfwnHuiXrCsaUj4D5QCihcjbvtvKHx021U/TsmL3CuPJIJkg33mIvg++R20uirII7PNjkRkSRwGp0Gne87DX7kT8vhZsLt5wQ7qyTbxZghxyfDxu2uiXrGsadD5v/oDoClwXL/Y7ChkQRf3rruPDK8yOw6RJbGsaVDpHS1QDv4V8jVzeAQ49Sqwd12+hXvXRJfBsqZB5f+qBDAMOK6/0+woZGGCZIPj+sXQG49CPVxmdhwiy+EBZjRotJZaKDV/g23yLRATXGbHoRDyK9qAri3u9aloP+/pcZs8cQ7Egx/B9/lmyKNnQrDHDjQmUcRgWdOgMAwDvk9+B9hjYM+9y+w4FGJ2mzTgo/rbv3ebIIiIuenH6Nr6r/B/VQLHrHsHFpIognAYnAaFemg3tDPfwDHrXogxV78HRtFFco+HfO0c+Ct2QD93xuw4RJbBsqaQM3yd8H32LkT3eNgm3mx2HAozjh/cDUg2eMs28WAzogtY1hRyvj3vw/B1IGbOMggCX2LUP6IzEY7rF0M7dQDayf1mxyGyBH6SUkhpjUehVH8E29TbIY3gBCh0dWzZt0NMzIB390YYis/sOESmY1lTyBi6Bu8nv4MQOwwOHlRGAyCIMhxzfgKj/Sx8n71rdhwi07GsKWT8X26HfvY4HLOXQrA7zY5DYU7OmAxbTgGUgx9BPbnP7DhEpmJZU0io9TXwf7Ud8jU3wTZ+ltlxKEI4bvg7iMlZ8O76D+ie82bHITINy5oGzPB2wPvRryEMcyPmph+bHYciiCDZEPPD/w7D3wXvrv/g0eEUtVjWNCCGYcC76//C8JxH7A8f4qxTFHJSchYcN9wD7eQ+KDW7zI5DZAqWNQ2IUv0XqCe+guMH90JyjTE7DkUo27S5kDKnwFe2CdrZE2bHIRpyLGu6alrjEfg+exdSVg5s0+aZHYcimCCIiLl1BQRHHDw7fgW9s9XsSERDimVNV0VvOwNP6csQ4pIRc+tyCIJgdiSKcGJcEmILHoHh64Rnx694/jVFFV7Ig/pN72pD1wcvAgCcCx6FGDvM5EQUbq76ql2ubHTK/xMN//k8vB/9GjFzf8FZ8igqsKypXwzFC8+Ol2F0tcFZ+L8gDk81OxKFoYFeteudv38AzX/+DXyf/ydi8v4+hMmIrIllTX1m6Co8H74K/exxxM77H5Dc482ORFFq2A134HzdCSgH/gTBHgP7zDv5VQxFNJY19Ymh+uD58FVopw7AcfMDkEfPMDsSRTFBEOCYfT8MxQt/eTGg+GD/wT0sbIpYLGsKyvB2oGvHy9AbjmD47cuRMmuB2ZGIIIgSYm5dDp/sgH//BzAUHxw33c/vsCkisazpivSOFnj+9CL0tgbE3L4SKbN+OKDvGkteLAphOop2giDCMWcZYHNAOVAKQ/UhJv8fIYiS2dGIQoplTb3Smk91H0zm60TswkchZ0w2OxIRgEuPJjcWLce54cPR+vF7UL2tcC9eBTkhqdftvT51KGIShQzLmi5hGAaU6r/A99m7EBzxcBb+b16bmizl8keTO5Brvwl/f+IzNL78C/y2Ix+H1bTLbs8RHgo3LOsokjAsFjGOKz/lWtd5NP3hVfgO7UHs+OvgLvwFpLjhQ5SQaGDK/eNRpyXjH+N34ecJf8YHnhn40JsNAzzwjMIbyzqKxDjkK3zfbGCqrRb3xn2GeMGH7V252LVnMrDnv3qsxT0SsrrTWhJebLsDfx9XhkXOr5BtP4X/7JyFWi3F7GhEV41lTUiTzuEu5x5Msp3GGW043mj/IT/YKKz5YMPvOm9GtZKJxc69eHTYH7Hbdy3+6JmJLsNhdjyifmNZR7EEwYOC2AO4yfENvIYNWzpvwMe+idA5ZTxFBAHl/vGoUrKwIHYfbnZ8jRn2E/izZxp0/zyIvJwrhRGWdRjpy3fOfZEhteKWmGrk2o9BgIGPfRNR6slBlxETgpRE1uIx7NjS9QN85puAu5zluCuuHCdfeRDDcudDH5vPue0pLLCsw8iVv3O+MhtU/G55Bn6esBPX2s7AZ8go812DXd7JaNL5YUWRr15Lxob2eRgtNeGpa5tx7pPfA2XbIY+fBds1N0JKnwRB5KgSWRPLegiFas+4r2xQMdlWjxn248i216Jxiwq35MT2rutQ5ruG391RVDqhuZB2z3L4z9aiYdf7UI58AfWbjyE4EyGPnwV5bC4k91gIIj8eyTr69GosKSnBa6+9BlVV8Q//8A+4//77e9x/8OBBPPnkk+js7ERubi6efvppyLKM+vp6rF69Gs3NzRg7dix++ctfIi4ublB+kXAwkD1jIPiR2DI0jJabcI3tDCbIDRgjN8Em6OjQHSj3jcPdP12KVa8c5nfSFPX8igb7iJHI+rv/AV3xoevwXnRU/g1dVX+BUrEDgj0WsaOzETs2B7Gjp8I2YmSPWdF8fg0O+8BmSRvoY3h9KtrPewaUgcJH0LJuaGjA+vXrsWXLFtjtdtx3332YNWsWJkyYEFhn9erV+Ld/+zfMmDEDTzzxBDZv3oylS5fi6aefxtKlS3HHHXdgw4YNePXVV7F69epB/YV6E4q9Wqu8OUToSBI7MUJsR4bcikypFZlSC1KlNkiCAd0QUKsl42/eSahRMnBYTYMOET8ZMw06jpodn8h0l59UZTJihXG4Vj6DibZ6TKw5iBGH9gAA/IaEOi0JtWoK6rQkrPrZAvz4lQq0GbHAVZ7DXfJi0YD/8d5+1VtTuAnaXrt370ZeXh4SExMBAAUFBSgtLcUvfvELAEBdXR28Xi9mzJgBAFiyZAn+/d//Hffccw/27NmDDRs2BG7/8Y9/bFpZD3SvFhjcN4cIHQ5BRazgg1PwI07wwSn6MEzwYJjY/ef0pn34P8OPIknshCQYgW3P6U7UqUmoULJwQh2Bo2oqPIZ9kJISRS6P4cB+ZTT2K90z9qWI7RgjNyFLbkaW1IIbHEdws6Di9Duf4ZkkwGfIaNbicU53ok13os3o/m+n7kCn4UCX4UCn7oDXsMEPmZOz0FULWtaNjY1wuVyBZbfbjQMHDvR6v8vlQkNDA1pbWxEfHw9Zlnvc3h+iGJoXtqFraK/6BIvTTgVu+/aRjR7rfvd2IXBb9/+f+6wEqtfXvYlhAIYO48J/YRjdj2XogK7B0A1AVwFDA3Qdhq6iUTLweFYTbNAhQ4MsaLALKhyCCpug9ZpfNUR06DEQbDFoir8Gh/R4tGhOtBpxaNKGoUtwADZ0/wGQcOHP5biTBn66ykAfI9y3t0IGs7e3Qoah2T4Wp+DGxU8OAcBwoQv/9uNr8da7u5AidSJR7MQIwYuxogdxQhuu9LHlM2T4L/yp37QfT2R54IcEDSI0Q4IOAaohQkf3H80QoF/4BDIgwLiwrENA86fFsElidypBgADhwgdY93J3YAEXP9W+vXpo9/+omgFZvsJXYkE+flXVgN+n9Hn93pyvdUDr8l3dxgNkt9uu/HcQhBGXAjXl2pDluVLnCYZhGL3eC+C1116Dz+fDI488AgDYvHkzKisr8cwzzwAA9u7dixdffBGbNm0CABw/fhwPPvggfvvb3+Lee+/Frl27AACqqmLmzJmoqKgIxe9EREQUNYL+kyItLQ1NTU2B5aamJrjd7l7vP3v2LNxuN5KTk9He3g5N0y67HREREfVN0LKePXs2ysrK0NLSAo/Hg507dyI/Pz9wf2ZmJhwOB/bu3QsA2LZtG/Lz82Gz2ZCbm4sPPvgAALB169Ye2xEREVHfBB0GB7pP3fr1r38NRVFw9913Y8WKFVixYgUefvhhTJs2DTU1NXjqqafQ0dGBqVOn4rnnnoPdbkddXR3WrFmD5uZmpKen46WXXsLw4byCExERUX/0qayJiIjIPJwdg4iIyOJY1kRERBbHsiYiIrI4ljUREZHFsayJiIgsjmUdRYqLizFnzhwUFRWhqKgI69evNztSVCkpKcHChQsxb948bNy40ew4UesnP/kJ7rjjjsD7YP/+/WZHiiodHR1YtGgRamtrAXRff6KwsBDz5s3jZ9IV8IKtUaSyshJr1qzBokWLzI4Sdfpy9ToafIZh4Pjx4/joo48C1y2gobN//3489dRTOH78OADA6/XiiSeewNtvv4309HT87Gc/w65du3DLLbeYG9SCuGcdRSoqKlBcXIzCwkI89thjaGtrMztS1Pju1eucTmfg6nU0tI4e7b5E7D/90z/hzjvvxDvvvGNyouiyefNmrF27NjD19IEDBzB69GhkZWVBlmUUFhbyfdELlnUUcblcWLlyJbZv34709PTAxVho8F3u6nX9vQodDdz58+dx4403YsOGDXjrrbfw7rvv4tNPPzU7VtR49tlnkZubG1jm+6LvOA4Ugf70pz/hueee63HbuHHj8NZbbwWWly9fjrlz5w5xsuil6zoE4TsXYDWMHss0NGbOnImZM2cGlu+++27s2rULN910k4mpohffF33Hso5ACxYswIIFC3rc1t7ejrfeegsPPPAAgO43hSRJJqSLTmlpaSgvLw8s8yp05igvL4eiKLjxxhsBdL8P+N21eYJd1ZG+xWHwKOF0OvHmm28Gjnx95513uGc9hIJdvY6GRnt7O1544QX4fD50dHSguLiY7wMTTZ8+HceOHcOJEyegaRr+8Ic/8H3RC/6TMkpIkoSXX34Z69atg9frxZgxY/DCCy+YHStqpKamYtWqVVi2bFng6nU5OTlmx4o6t912G/bv34/FixdD13UsXbq0x7A4DS2Hw4Hnn38e//zP/wyfz4dbbrkF8+fPNzuWJfGqW0RERBbHYXAiIiKLY1kTERFZHMuaiIjI4ljWREREFseyJiIisjiWNRERkcWxrImIiCyOZU1ERGRx/x+gOh+c6XkKkwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(amzn_return, bins = 25, edgecolor='w', density= True)\n",
    "data = np.linspace(mini, maxi, 100)\n",
    "plt.plot(data, norm.pdf(data, mean, std));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 12. Compare normally distributed sample with same attributes as amzn price change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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G59Y/A5oK89j53P3tB/qeaTCkZMK9dz2UihOi4xD5BMuaqAN5jxdBObsPptt/DDnaJjpOyDKl3w/J2gnOze9xdziFBJY1UQdRHbVwFi6DnJAEw4AJouOENMloadwdfvkC3Ps3io5DdNNY1kQdxLX9Q8DjgjnzIUgy//T8Td8zFfpeQ+HelQ+1vkZ0HKKbwm8Mog7gKdsF78mdMA67B7pOXPqyo5hG3w9oClw7PxIdheimsKyJ/EzzuuEqWg65Uw8Yh0wTHSesyNHxMKZOgfdYIZTy46LjELUby5rIz9wHCqDZq2DKmAtJ1ouOE3aMQ++GZI2Fs3AZNE0VHYeoXVjWRH6kNlyGe/c66HsNhb77ANFxwpJkMMOUfh/UylPwHtkmOg5Ru7CsifzIXbwaUDwwpd8nOkpY0/dNhy7hNriKP4bmbhAdh6jNWNZEfqJUnYbnyFYYBk2CHJMoOk5YkyQJpjsegOaww1XKhT4o+LCsifxA0zS4ipZDMkfCNDRbdBwCoOvSG4aUTHgObIJy+bzoOERtwrIm8gNvWSmUC0dgHDETkilCdBz6jnHkjwCDEa7C5dA0TXQcolZjWRP5mKZ44NqxAnKnHjCkjBMdh/6BbImGafgMKN8egHJmj+g4RK3GsibyMff+z6DZK2EaPQeSrBMdh37AMHAC5NhucBb9lfOGU9BgWRP5kNpwBe7da6G7ZQj0PQaJjkPXIMl6mDLmQqut4LzhFDRY1kQ+5C5ZDXg9MKfPER2FbkDfYxDnDaegwrIm8hGl6jQ8h7+CYdBEyLE8VSvQcd5wCiYsayIfaDxV66+QTBEwDbtHdBxqBc4bTsGEZU3kA97Tu6BcOMxTtYKMcejdkCwxcH29kqdyUUDjqgJE7RAVbYHZ1Pjno3k9OPvRRzB06YFumdk8AjyISAYzjMNz4Nr2Fyhn90F/y2DRkYiuiWVN1A5mkx7ZTzZOWznefBAzrBfxVu1EHHl6XbufM39xjq/iURsYUjLh3rcBrp0fQ9czFZLEHY4UePipJLoJVsmFyeZ9OOjujiPebqLjUDtIsh6mEbOgVp+F98TXouMQXRPLmugmTDAfgFnyIN8xTHQUugn6vrdDjusJV/FqaIpXdByiq7CsidopWmpApvkwdrlvxQWlk+g4dBMkSYZp5I+h2SvhObxFdByiq7CsidppkmU/dFCx3jFEdBTyAV3PVOi6JsO9Kw+axyU6DlEzPMCMqB08l8uRYTqGItdtuKRGiY4TUtweBTab77ep0+WFvdZx3dslSYJp5Gw0rH0F7gMFXNqUAgrLmqgdarauhAoJBY400VFCjtGgazrS3pfyF+fA3sJ9dIm3NU5Dumc9jP3HQzJH+jwHUXtwNzhRGyk151C3/ytsdSbjimYVHYd8zDjyR4DHCdeeT0RHIWrCsiZqI3fxakgGEz53clWtUKTr3AP6fhnwHNwEta5adBwiACxrojZRKk7CW1aK2FH3oF4zi45DfmIaPgPQNLh3+X53PFF7sKyJ2sBVshqSKRIxo+4WHYX8SI6ywTBgPDxHtkK9fEF0HCKWNVFrec9/A+XbAzAOvRuyib9Vhzrj0GxAb4SrZLXoKEQsa6LW0DQNruJVkCI6wTDgLtFxqAPIlmgYU7PgPVkMpfKU6DgU5ljWRK2gnNkLtfw4jMNyIOmNouNQBzGmTYFkjoJr58eio1CYY1kTtUDT1MZRdXQ8DMljRMehDiQZLTAOvRvKuYPwnjskOg6FMZY1UQu8J3ZCrT4L04iZkGTOIxRuDP3HQ4qMg2vnx9A0TXQcClMsa6Ib0FQvXCW5kDv3gL7vKNFxSABJb4RxaDbUypNQzu4XHYfCFMua6AY8R7dDqy2HaeSPIEn8cwlXhn5jIEV1gas0l6NrEoLfPkTXoXndcJfmQY7vC90tQ0THIYEknf670fUpKGf3io5DYYhlTXQdnsNboNVXfzeqlkTHIcEM/e6AFGWDqzSPo2vqcCxromvQvG6493wCXddk6Lr1Fx2HAoAk62H6fnR9hqNr6lgsa6Jr8Bz+ClrDZRiHz+Compro+2V8N7pew9E1dSiWNdEPNI6q1zWOqrumiI5DAUSS9TANuwdqVRmUM3tEx6EwwrIm+oGmUfWwHI6q6Sr62zIgRcdzdE0dqlVlnZ+fj2nTpmHy5MlYtmzZde/3zDPPYPXqv096n5ubizFjxiAnJwc5OTlYsmTJzScm8qOmUXViP/5WTdckybrG366rTsN7erfoOBQmWpyOqby8HEuWLMHq1athNBoxZ84cjBo1CklJSc3u88ILL6CoqAjp6elN1x84cACLFi3C3XdzOUEKDp4j342qx/8zR9V0XfrbMiDtXgd36Rroew3lZ4X8rsWRdWFhIdLT0xEbGwur1YqsrCxs2LCh2X3y8/MxYcIETJ06tdn1+/fvR25uLrKzs/HUU0/hypUrvk1P5ENNR4BzVE0tkGRd42/Xl87Ae3qX6DgUBlocWVdUVMBmszVdjo+Px759+5rd55FHHgEAlJaWNrveZrPhoYcewrBhw/CHP/wBL7/8MhYvXuyL3EStEhVtgdnUuvm8r5R8irr6GsTnPAFLfLSfk1Gw0yelQ9q99h9G1zwEiPynxW8xVVWb7eLRNK3Vu3zefPPNpv9+5JFHMGnSpDaFi4uLbNP9A4HNFiU6Qshr6zbOfjKvxfvooOBXsbm4pMTjX984CeDG6xfnL85pUwYKDL7++7SPuxeVa/+IiOpvEJGS3vID/JyHrhYq27jFsk5MTERJSUnT5crKSsTHx7f4xHa7HatWrcL8+fMBNJa8TqdrU7hLl+qgqsFztKXNFoXKSrvoGCGtrdu4tX+oo03HECs3YFndHQD4+2Oo8vXfpxY/BFJMIiq//BvqO/dv0+ia3xf+F2zbWJal6w5SW/xkZWRkoKioCNXV1XA4HCgoKEBmZmaLL2q1WvHee+9h797GmX4+/PDDNo+siTqCDgommg/gpMeGo95E0XEoiDT9dl19Ft5TpS0/gKidWizrhIQELFy4EPPmzcOMGTNw9913Iy0tDQsWLMD+/ddfLk6n0+H111/Hiy++iKlTp+LgwYN4+umnfRqeyBfSTcfRSdeATx2DwVE1tZW+bzrkmES4S/OgaaroOBSiWnXkTXZ2NrKzs5tdt3Tp0qvu9+qrrza7PGLECOTm5t5EPCL/0kHBJPP+70bVXUXHoSAkyTKMw3Pg/OIdeE+VwtBnpOhIFIJ4+CKFNY6qyRf0fUZBju0Kd+kajq7JL1jWFLY4qiZfkWQZxmE5UGvO8bdr8guWNYWt70fVGziqJh/Q97kdUkwi3LvWcnRNPseyprD0j6PqIxxVkw9Istw4Z3j1WXhP7xEdh0IMy5rCEkfV5A/6pHRIUbbvRtfBM0cEBT6WNYWd78+rPuXtwlE1+dTfV+Qqg3J2X8sPIGolljWFnZHGk+isq8dGjqrJD/T9MiBFxsG1K4+ja/IZljWFFRkqJln244w3Dt94uomOQyFIkvUwDrkbasVJKOcOio5DIYJlTWFluPEUuujqsNGRBo6qyV8MyWMgRXTmb9fkMyxrChvSd6Pqb72dcMDTQ3QcCmGSzgDjkGlQLh6FcuGw6DgUAljWFDaGGk8jQVeLAo6qqQMYkjMhWWPh3rVWdBQKAa2aG5wo2EnQMNm8Dxe8sdjnuUV0HBLA7VH8srax0+WFvdZx1fWS3gjj4KlwFf0V3otHoU/s5/PXpvDBsqawkGY4g676K3i/biw0jqrDktGgQ/aTeT5/3vzFObjeismG/nfCvecTuHethX7aUz5/bQof3A1OIU+ChizLPpQr0djj7iU6DoURSW+CMW0KlG8PQCk/LjoOBTGWNYW8gYaz6K6vQYEjFRo/8tTBDAPugmSKhIu/XdNN4DcXhTRN0zDFsg+VShR2uW8VHYfCkGQww5A2BcrZfVAqy0THoSDFsqaQ5jixCz311fjMMQgqP+4kiHHgBMAUAfcu3/9mTuGB314UsjRNQ83Wj3BJiUCxu6/oOBTGJKMFxkGT4T29G8qlM6LjUBBiWVPIUs4dhOv8MWxypnJUTcIZB00EDBaed03twm8wCkmapsG9ay10UXH42sVRNYknmSJgHDQR3lMlUKrPiY5DQYZlTSFJuXAYysWjiB09Awp0ouMQAQCMqVmAwQz3bo6uqW1Y1hSS3LvWQrLEIGrIBNFRiJpI5kgYB06A98ROuKu+FR2HggjLmkKO9+JRKOe/gXHwNMgGk+g4RM0YUrMAvQGXt68SHYWCCMuaQo5711pI5igYBtwpOgrRVWRLNAwD7kLdwW1Qr1wUHYeCBMuaQopSfhzKtwdgSJsCSc9RNQUmY9pUSDo9XLvXiY5CQYJlTSHFtWstJFPj74JEgUq2xiBq2GR4jxVCra0QHYeCAMuaQoZScRLK2X2No2qDWXQcohuKTc8BZBnuPRxdU8tY1hQyXLvyAFMER9UUFPRRnWFIGQfPke1Q7VWi41CAY1lTSFCqyqCc2QtjahYko0V0HKJWMQ6eDkgS3Hs+ER2FApxedAAiAIiKtsBsat3H0WaLuuq6i5s/gWyOQLdxMyCbI3wdj+i63B7lmp/J1ki4tRcqh9wF+54v0HXiHOijuzTd5nR5Ya91+ComBTmWNQUEs0mP7CfbtyJRd101nokpxqcNg7HhuU3NbstfnOOLeETXZTTo2v3ZBYBOciT+PUbBh7/7A1Y1jGq6Pn9xDuy+CEghgWVNQS/Lsg8O1YAtrv6ioxC1WY0aia9dfZFhOoZNjlRc0awAbm7EfiMcsQcnljUFtW66Ggw2nsEGRxocmlF0HKJ22eRMxSjTCdxlOYjchpEAbn7Efj0csQcnHmBGQW2yeR+cmgFbnBxVU/C6pEahxN0HGaajiJI46qWrsawpaCXqLmOw8TS+cqagQeNsZRTcChyp0EPFXeaDoqNQAGJZU9CabN4HD/T4kqNqCgFVajRK3LfiDvNRRHJ0TT/AsqaglCBfxlBjGbY6k9GgcbYyCg2fOVJhgBfjzYdER6EAw7KmoDTZsh8e6PGFc6DoKEQ+U6HGYLe7N8aaj0BpqBUdhwIIy5qCjk2uxTBjGbY5+6Geo2oKMQXONBjgxZWv80VHoQDCsqagM9myD17I+JKjagpBF5VY7HX3wpWS9YiQnKLjUIBgWVNQ6SLXYrjxFLY7k2HXOAc4haYNzsHQ3C7+dk1NWNYUVCZZ9kOBjM85qqYQdlGJRcSADGSaD3N0TQBY1hRE4mQ7RhpPotDVj6NqCnmdxt4LAxRM4HnXBJY1BZEsy77GUbWDo2oKfcYuPbDL3RtjzYc5qxmxrCk42ORajDSexHZXP9R+t9ABUajb4BgMPVSOrollTcFhimUvPNBhk2OQ6ChEHaZSjUaxuw/uMB9BtNQgOg4JxLKmgJeou4xhxlPY6kxGHX+rpjCz0ZEGHVRMsHB0Hc5Y1hTwppj3ws3ZyihMXVKjUOzuiztMRxDD0XXYYllTQOumq8ZQ02lscfbnbGUUtjY6UiFDw0TLftFRSBCWNQW0qZa9aFAN+NI5QHQUImGq1Sh87UpChukYYuV60XFIAJY1BaweuktIM57FZucAOLheNYW5AmcqAGCSmaPrcMSypoA1zbIH9aoRm7leNRFq1EjscCUh3XQcneQ60XGog7GsKSD11ldioPEcvnAOhAtG0XGIAsJn342uJ3N0HXZY1hSQplr2wK6a8ZUzRXQUooBxWY1Aoes2jDIdR2fZLjoOdaBWlXV+fj6mTZuGyZMnY9myZde93zPPPIPVq1c3XT5//jweeOABTJkyBY899hjq63lgBLWsj74cKYYL+Nw5EG4YRMchCiibHKlQISGLR4aHlRbLury8HEuWLMHy5cuxZs0arFixAsePH7/qPo8++ig2btzY7PqXXnoJc+fOxYYNGzBo0CC89dZbvk1PIUjDNMseXFEt2OZMFh2GKOBc0awodPXDSOMJxHF0HTZaLOvCwkKkp6cjNjYWVqsVWVlZ2LBhQ7P75OfnY8KECZg6dWrTdR6PB8XFxcjKygIAzJo166rHEf3QbfqLuM1Qjk2OQfBALzoOUUDa5BgEBTKyLPtER6EO0mJZV1RUwGazNV2Oj49HeXl5s/s88sgj+PGPf9zsupqaGkRGRkKvb/zCtdlsVz2OqLnGUXWN0jhyIKJrq9Ws2O5MxkjjSSTIl0XHoQ7Q4tBFVVVIktR0WdO0Zpev51r3a83j/lFcXGSb7h8IbLYo0RGCVorhPPoYKrGyfhS80ImOQxTQPnMOwmjzMUy37sH/1N3ZpseG0/dUqLzXFss6MTERJSUlTZcrKysRHx/f4hN37twZdrsdiqJAp9O1+nH/6NKlOqiq1qbHiGSzRaGykr8htUeXLpGYZtmDS0oEdriSRMchCnj1mhlfOAZgmnUvbtFV4YzSpdWPDZfvqWD7TpZl6bqD1BZ3g2dkZKCoqAjV1dVwOBwoKChAZmZmiy9qMBgwYsQIrF+/HgCwZs2aVj2OwlPDsRL00l9CgSMNCkfVRK2y2TkAdtWMbOsuAMEzsKG2a7GsExISsHDhQsybNw8zZszA3XffjbS0NCxYsAD799/41IEXXngBK1euxLRp01BSUoJf/vKXvspNIURTVVRvXo5KJQo73X1FxyEKGi4YUOBIRT/DRSTrL4iOQ37UqsNts7OzkZ2d3ey6pUuXXnW/V199tdnl7t2744MPPriJeBQOvMcL4ak8g3UNmVA5Tw9Rm2x39cOd5kPItu7C0dqu0NC2Y4MoOPCbkYTSvG64ilfD1DUJezy9RMchCjoKdPjUMQQ99dUYbDwtOg75CcuahPIc+hxafTU63/VPAEcERO1S4r4V572xmG7ZDRmq6DjkByxrEkZz1cO1ex10PVNh6Z0qOg5R0NIgY51jKOJ1dowyHW/5ARR0WNYkjHvvesDVANPtP275zkR0Qwc9PXDSY8NUy14Y4BUdh3yMZU1CqPU1cO8vgD4pHbq4W0THIQoBEvIdwxAjO5BpPiw6DPkYy5qEcJfmApoG08hZoqMQhYyT3gQcdHfHRPMBWCSX6DjkQyxr6nBKzXl4jmyFYcB4yFG2lh9ARK22zjEMZsmNCeaDoqOQD7GsqcO5iz8G9CYYh2a3fGciapPzSifsct+KceZvEC01iI5DPsKypg6lXDwGb9kuGAdPg2yJFh2HKCStdwyBDiqmcAnNkMGypg6jaRpcOz+CZImGMTVLdByikHVJjcJ2Vz+km47BJteKjkM+wLKmDqOc2Qvl4lEYh8+AZDCJjkMU0gocafBCh2mWPaKjkA+wrKlDaKraOKqOSYAhhauvEfmbXbNgs7M/hpnK0FNXJToO3SSWNXUI77HtUGvOwTRyNiS5VevHENFN+sI5EHbVjBnWEnAJzeDGsia/07xuuEpyIdv6QH/rCNFxiMKGUzPiE8cQJBkqMMTART6CGcua/M5zsHGxDtOoH0OSuFgHUUfa4UrCOW8n3GMthR6K6DjUTixr8ivVUQvX7rXQ9UyDvlt/0XGIwo4GGbkNIxCnq8ed5kOi41A7sazJr9zFqwGPG6b0OaKjEIWtY96u2OfuiUmW/fDaa0THoXZgWZPfKFWn4Tm8BYaBE6Dr1E10HKKwltcwHHqoqNmyXHQUageWNfmFpmlwFS6DZI6EaXiO6DhEYa9KjcYWZwrse7+EUlUmOg61Ecua/MJ7cmfjBCgjfwTJFCE6DhEBKHCmQbZGwVW4HJrGU7mCCcuafE7zuuDasQJyXC8YkjkBClGgcGpGdB53P5SLR+E9VSI6DrUBy5p8zr1nfeOpWhlzIcn8iBEFkqghEyB37gHX1yuged2i41Ar8ZuUfEq1V8G9dz30fUdB3zVZdBwi+gFJ1sE0ei40exXcBwpEx6FWYlmTT7m+XgFAgmnUvaKjENF16LsPgL7XULh3r4PacFl0HGoFljX5jPf8N/CeLIZxyHTIkXGi4xDRDZjS7wMUD9zFq0RHoVZgWZNPaKoCV+FySJFxMA6eKjoOEbVAjkmEYdAkeI5s46lcQYBlTT7hObwFavVZmNLnQNIbRccholYwDc2GZI6Eq+ivPJUrwLGs6aZprnq4i1dD1zWZq2oRBRHJFAHjiJlQLhzhqVwBjmVNN81VkgvNXQ9Txj9xVS2iIGNIGQe5c8/G0bXbIToOXYdedAAKLlHRFphNf//YuCvOwH7oC0QPnYwuKQMEJiOi9pBkHcxjH0RD3itwleTCnDFXdCS6BpY1tYnZpEf2k3nfXdLweNQm9NTp8eznMajflHfDx95I/mLOH04kii4hCYYB4+E5+BkMt2VAZ+stOhL9AHeDU7sNNZYh2XAB6x2DUa+ZRcchoptgGvkjSOZoOLf+LzRVER2HfoBlTe1ilZz4kbUYp71x2ObiTGVEwU4yRcCU8QDUqtPwHPxcdBz6AZY1tcsMaymskgt/qx8NjR8jopCg7zMSup5pcJWshlpXLToO/QN+y1Kb9dNfwCjTCXzhHIjzSmfRcYjIRyRJgvmOnwCqClfhMtFx6B+wrKlNVI8L90bsQKUShY2ONNFxiMjH5GgbjMNnwFtWCk/ZLtFx6Dssa2qTmq0rYdPZ8bf60fDwZAKikGRMm9y4jOb2D3nudYBgWVOrKVWncWXHWuxwJeG4N1F0HCLyE0nWwzx2PrT6GrhK14iOQ+B51iHrh5OX3CxNVXBu7V+gs0Yjr3q4z56XiAJT07nXBwpguG00dF163/D+vv7O+Z7T5YW9lqN7lnWIaj55yc0bbz6IGdYTiJ/5b2j4U5XPnpeIApdp5I/gPVUK51fvwzrjV5Dk6++M9fV3zvfyF+fA7vNnDT7cDU4t6izbMdWyFwfcPRDRP0N0HCLqIH8/97oMnkM891okljW1QMO9ETugAfioYRQX6iAKM03nXhev4rnXArGs6YZGGE+iv+EC1jUMw2U1QnQcIupgzc693v4B170WhGVN1xUhOTHTWoJT3i7Y5uonOg4RCSJH22AaMRPe07vhPVYoOk5Y4gFmdF0zrSUwSx78rT6DU4oShQi3R4HNFtXmx2l3/QgXzu+Dq2gZbIOGwRAT74d0dD0sa7qm/oZzGGk6iQ2ONFxUYkXHISIfMRp07T5qu7PcH/8n5ji+XPIi3rBPavaPeC5z618cLtFVIiUH5kZsxwVvLD5zpIqOQ0QBolqNxMf1tyPJUI7x5kOi44QVljX9gIb7I4pgkdz4S/1YeKETHYiIAkixuw/2um/BdMsedNPx6PCOwrKmZsaYjmCQ8VvkNwzHeaWT6DhEFHAkrKhPR71mwk8itkEPRXSgsMCypiaJusvIsZbikLsbtrhSRMchogBVr5nx1/oMdNNfxnTLbtFxwgLLmgAAeiiYF7EVLs2A5fV3AODkJ0R0fd94umObsx/uNB9Ckv6i6Dghj2VNAIBs6y5019dgeX0G7JpFdBwiCgJ5DcNRqUbjnyK2QXHWi44T0ljWhBTDOdxp/gZfOZNxyNNDdBwiChJuGPBh3RhEyw5c2vie6DghjWUd5iIkJ+ZGFOKCNxZrG7j0JRG1zRmlCwocaag78BWGGMtExwlZrSrr/Px8TJs2DZMnT8ayZcuuuv2bb77BrFmzkJWVheeeew5erxcAkJubizFjxiAnJwc5OTlYsmSJb9PTTdIwN6IQVsmFv9SPhYdz5BBROxQ4U2Hqdhvute5AjNQgOk5IarGsy8vLsWTJEixfvhxr1qzBihUrcPz48Wb3efrpp/GrX/0KGzduhKZpWLlyJQDgwIEDWLRoEfLy8pCXl4eFCxf6511Qu/A0LSLyBRUybPc8Ab2kYm7kdkjgYh++1mJZFxYWIj09HbGxsbBarcjKysKGDRuabj937hycTieGDBkCAJg1a1bT7fv370dubi6ys7Px1FNP4cqVK/55F9RmPE2LiHzJGNcNeQ3DkWK4gAnmA6LjhJwWy7qiogI2m63pcnx8PMrLy697u81ma7rdZrPh8ccfx9q1a9G1a1e8/PLLvsxO7aTjaVpE5AfbXf1Q6uqN6ZbdSNafFx0npLT4I6WqqpCkv3+Za5rW7PKNbn/zzTebrn/kkUcwadKkNoWLi4ts0/0DQXtWs+loOdZSdNfX4B37XTxNi4h8SMLf6kejq+4yHoz8Cr+vnY5q9ea/E2/mezUYvpNbo8WyTkxMRElJSdPlyspKxMfHN7u9srKy6XJVVRXi4+Nht9uxatUqzJ8/H0Bjiet0bZtn+tKlOqhq8Pz2YbNFobLSLjoGgOt/QEcaT2Cc+TA2O/vzNC0i8jk3DHivbjyeiv4ED0duxuu1U2/64NX2fq8G0ndya8iydN1Baou7wTMyMlBUVITq6mo4HA4UFBQgMzOz6fbu3bvDZDKhtLQUAJCXl4fMzExYrVa899572Lt3LwDgww8/bPPImnzrFl0V7osowlFPIvJ4mhYR+cklNQof1I9BN10N7o3YAfCAs5vW4j93EhISsHDhQsybNw8ejwezZ89GWloaFixYgCeeeAKpqan4/e9/j+effx51dXUYOHAg5s2bB51Oh9dffx0vvvginE4nevfujddee60j3hNdQ7TUgIejvsQV1Yr/rcuEylPsiciPDnl64FPHEEy37sEZbxy2uvqLjhTUWrVvIjs7G9nZ2c2uW7p0adN/p6Sk4OOPP77qcSNGjEBubu5NRqSbpYeCh6I2wyJ5sMQ+EQ2aWXQkIgoDnzlTcYu+CjOtJTindMZJb4LoSEGLw6uQp+HeiB24VV+FZXV34ALPpyaiDqJBwof1Y3BJjcRPI7dwwpSbwLIOcZmmwxhlOoENjjTs9fQSHYeIwoxTM+JPdeNhkrz4adRm6Lj+dbuwrENYP/0FzLCWYJ+7JzY4BouOQ0Rh6qISi+V1GbhVX4VZ1mLRcYISyzpEeWouYn7kFlQoMfiwbgw0TnxCRALt8fTGJsdAjDEfxSjjMdFxgg7LOgRpbgcufvQqAGBp3Xi4YBCciIgI+MQxFEc8ifhxxNe4RVclOk5QYVmHGE1T4dz8HjxV5/B+XSYu+WD2ICIiX1Ah4891mahVrfjnqC9gk2tFRwoaLOsQ4y7Ng7esFHETH8RRbzfRcYiImqnXzPhv+wRI0PBY1CZE8wjxVmFZhxD34S1w78qDvt8YRI+cLjoOEdE1VagxeMc+AZGyE49FbYJFcouOFPBY1iHCc2InXF+9D13PVJjHzm+2uAoRUaA5o3TBn+x3Il5Xi0civ4ABXtGRAhrLOgR4z+yF84t3oEu8DZZJv4Cku7lJ84mIOsIRbzd8UD8GffQVeDDyK8hQRUcKWCzrIOc9fxiOz96AHNcDlim/hKQ3iY5ERNRqe9y9sarhdqQav8V9EUXgoh/XxiFYEFMqTsKx8XXIUTZYpj0FyWgVHYmIqM22uVIQKTsx1bIPdaoZ+Q6uCvhDLOsgpVR/i4ZPF0MyR8Ey/WnIZp6iRUTBa4NjMKIkJyZaDsKuWbDZOUB0pIDCsg5Cam0FHJ/8DpLOAOv0pyFHcHEOIgp2Ej5uuB0RsgszrSWoU00ocfcVHSpgsKyDjFpXjYZPXgNUBZZ7/i/k6HjRkYiIfEKDjA/qxiAiyoW5EYVo0HgMzvd4gFkQUR21cKz/HTRnHSzTnoKuU3fRkYiIfEqBDu/Zx+Oc0hkPRW5G/ZGdoiMFBJZ1kNBc9XCsXwzVXgXLlIXQ2XqLjkRE5BcuGPC2fSLOKZ1Rvup38BzdLjqScCzrIKDW16Ah/7dQa76FZdK/QN81WXQkIiK/atBMeLN2Eiy9BsK5eSncBz4THUkolnWAUy6fR0Peb74bUf8b9LekiY5ERNQh3DAg8b7noO89HK7CZXCVroGmhed52CzrAKaUH0dD3iuA4oE1exH0PQaKjkRE1KEkvQHmiY9D328M3KVr4CpaDk0Lv5nOeDR4gPKe2QPHZ29BiugE67QnedQ3EYUtSdbBPO4huIxWeA4UQHM3wJz5ECRZJzpah2FZByDPka1wfvW/kONugWXqv0G2RIuOREQklCTJMI2+H5I5Au6SXDjdDpjvehSS3ig6WofgbvAAomkaXLvz4dzyJ+i6D4A1exGLmojoO5IkwTQsB6aMB+At2wXHhiXQ3A7RsToEyzpAaKoK1/YP4S5eBX3SaFiyfgnJYBYdi4go4BgHTYL5zgVQLhxBwye/g9pwWXQkv2NZBwDN64bz87fgOfQ5DGlTYB6/gMtcEhHdgKHfHbBM+heo1d+iYfWL8F48JjqSX7GsBVPrLqHhk9fgPVUCU/ocmNPnQJL4v4WIqCX63kNhnfHvgN4IR/6rcB/4LGRP7eLwTSDvmb1wbl4KqF7Ez3oSkf0zREciIgoqurieiJj5AhxfLoWrcBmUipMwj50PyRBa84qzrAXQVC/cxavh3rsexvje+NXRIah8rxJAns9eI39xjs+ei4gokEmmCFiynoB79zq4S3LRcOksLJN/AdhCZ+lg7m/tYGpdNRz5/wH33vUwpNyJbvP/HypVHvFNRHQzJEmGadg9sEx7EmpDDepXv4T6o8WiY/kMy7oDec/sQ8OqX0G5dAbmu34Gc+Z8yCG2q4aISCR9j0GImPUS5JgElH/0KlzFq6CpwT/jGXeDdwBNVeAuyYV7zzrInXvAOvHnkGO7io5FRBSS5KgusN7zLKRdK2Hfnd/4O/ZdPwvqeStY1n6m1tfA+fnbUC4ehSElE6aMfwqbGXeIiESR9EbYpj8Gd3RPuLZ/gIaVz8KUMRf6pNGQJEl0vDZjWfuJpmnwHt0G144V0BQ3zOP/GYbbeLQ3EVFHMqaMgy4+Cc6v/gTnl+9Cd3wHzGMfhBwZJzpam7Cs/UCpOQfXtr9AuXAEckISLOMegi62m+hYRERhSde5O6z3PA/PwU1wFX+M+o+eg2nkbBgG3hU081qwrH1I9bjg2vkx3Hs/BYxmmDJ/CkPy2KD5MBARhSpJlmFMnQx976Fwbv0zXIUfwnNiB8yZP4WuU3fR8VrEsvYR75l9+Hblh/BeroC+3x0wjbovqA9mICIKRXKUDZapT8J7rBDOouVoWPUCjMOyYRw8PaCneQ7cZO0UFW2B2eT7t+V0eWGvvXp1F7W+Bq7CZfCeKoEhrjssd/8f6Lv19/nrExGFI7dHge0mJje53mOdMRNxpWcqXIXL4C7JhfdEMcyZ86FLSGr3a/lTyJW12aRH9pO+mwnse/mLc2D/h8uaqsBz6Au4ilcBqgLjiFnoPvFeVFU7ff7aREThymjQ+e873RINy4TH4E0aDee2P6Mh7zfQ9x4G44hZ0HXu4fPXvBkhV9b+pqkKvMcK4dqdD622Aroeg2AeMw9ydDwknQEAy5qIKNA1G7HbxkJNHYErxZ/g8o48NHz874gcNBadMu+DoVNim573enthbxbLupU0VYHnyNamkpa79IY565fQ3TI4KM/ZIyIKZ9cesRtglbIxwXwAmfu348r+rdjhug0bHWm4ollb9bw/3AvrKyzrFshQMcJ4Emf/+wl4ay6ypImIQliDZkK+Yzi2OPtjkmU/MkzHMNJ0AtucydjkHIR6zSwkF8v6Or4v6cmW/bDp7JBNfWFhSRMRhYVazYpVDaPwpXMAplj24U7zN8gwH8Vm5wBscybDrlk6NA/L+gfMkhvDjacw3nwINp0dZ72d8a59PF56+lGYjC1vrps5apGIiAJLtRqF5fV34HPHQEy17sUUyz5MNB/AHncvbHUlo8xrA+D/ARzLGgCgoZeuChnmYxhqLINJ8uKMNw7v2sfjoKcHAAkmo/+OMiciosBWrsbi/bpxWC9fwRjzEdxuPIERplP41tsJW10pKHXdCo8fKzWsy9oiuTHceBIZpmPorq+BS9Oj1NUbRa5+OKPEoSP+tURERMGjQo3B6obbsa5hKEaYTmGs6TDujyhCjqUUX7v7wlM9EoDv97CGYVl/P4o+imHGMhglBWe9nbGiPh2lrt5wgStiERHRjblhQKGrHwpdt6GPvgJjTUeQaTqMs2//C3Q9BsHQbwz0twyGZPTNb9thUtYaeuiqkWY8gzTDGXTVX4FT06PY1QeFrn74Vgmu1VeIiChQSDjpTcBJbwKiGxrwRo4Ol0sL4PzivwGdHvoeqdD3GQl9ryGQjK07/etaQrasZahI0pcj1XgGqYaz6KRrgKpJOOGNx9/q+2OX61a4YBAdk4iIQkStZkWnsTnwJGdBKT8B78lieE+VwHt6NyDroesxEIY+I6HvNRSSKaJNzx1SZa15nKg7fAD/FLENAw3fwiq74dZ0OOzphk8cQ3HI013YOXJERBQeJEmGPvE26BNvgzZ6DtSKk/CcKoH3ZDGcZ/YCkg66HgOg7zUU+m4DIMUktHhKcFCXteZxQik/DuXCESgXj0KpOIE6xYv+BhP2e3pin7snjni6+fUIPSIiouuRJBm6hCToEpKgjboPauUpeE+VwHOyGK6zf4ELgGSNha5bf5huHQbE3XXN5wmqFtOcdVDKj8F74QiUC0ehVpUBmgpIMuQuvWAYOBFd0jIw57+OQgXXkCYiosAhSRJ08X2gi+8D4+0/hlZbAe/5b6Cc/wbKuYNwVR4Hbg/CslYqTsJz8QTU6jNQKk5Crf628QZZ3/hmh0yHrmsydPF9m464s9iioOK4wNREREQ3JkkSpJgEGGMSgP53QtM0SHWV171/QJe18/O34L1SCckUCblLLxhH3N5YzrZbIel5ihUREYUGSZIgxyRc9/aALmvzuIehRSVAssZyPm4iIgpbrSrr/Px8vP322/B6vXjwwQfxwAMPNLv9m2++wXPPPYf6+nqMGDECL730EvR6Pc6fP4+nn34aly5dwq233orf//73iIho/eHq8akj2/ZuiIiIBGq2TrYPtVjW5eXlWLJkCVavXg2j0Yg5c+Zg1KhRSEpKarrP008/jd/85jcYMmQInn32WaxcuRJz587FSy+9hLlz52L69Ol488038dZbb+Hpp59udbiHf1OAipq2LeLNubaJiEiUa6+T3TrxnSz40/OTr3lbi4dMFxYWIj09HbGxsbBarcjKysKGDRuabj937hycTieGDBkCAJg1axY2bNgAj8eD4uJiZGVlNbueiIiI2qbFkXVFRQVsNlvT5fj4eOzbt++6t9tsNpSXl6OmpgaRkZHQ6/XNrm+LuJj2TWAS38k/64zyefm8/n7eYMrK5+Xz8nl9+7w36jxJ0zTtRg9+++234XK58Mtf/hIAsHLlShw4cAAvv/wyAKC0tBSLFy/G8uXLAQBlZWV49NFH8ec//xn33nsvtmzZAgDwer0YOnQo9u/f3643QUREFK5a3A2emJiIysq/n/tVWVmJ+Pj4695eVVWF+Ph4dO7cGXa7HYqiXPNxRERE1DotlnVGRgaKiopQXV0Nh8OBgoICZGZmNt3evXt3mEwmlJaWAgDy8vKQmZkJg8GAESNGYP369QCANWvWNHscERERtU6Lu8GBxlO33nnnHXg8HsyePRsLFizAggUL8MQTTyA1NRWHDx/G888/j7q6OgwcOBC//e1vYTQace7cOSxatAiXLl1C165d8Yc//AExMTEd8b6IiIhCRqvKmoiIiMThahdEREQBjmVNREQU4FjWREREAY5lTUREFOBY1kRERAGOZe0Hhw4dwqBBg0THCEmlpaWYPXs2cnJy8OCDD+LcuXOiI4WU/Px8TJs2DZMnT8ayZctExwlJb7zxBqZPn47p06fjtddeEx0npP3Hf/wHFi1aJDqGT7CsfczhcODXv/41PB6P6Cgh6fsV3vLy8pCdnY3f/OY3oiOFjO9X2Fu+fDnWrFmDFStW4Pjx46JjhZTCwkJs27YNubm5WLNmDQ4ePIjPPvtMdKyQVFRUhNzcXNExfIZl7WOvvvoqHnzwQdExQpLb7ca//uu/IiUlBQCQnJyMCxcuCE4VOlpaYY9uns1mw6JFi2A0GmEwGNC3b1+cP39edKyQc/nyZSxZsgSPPvqo6Cg+w7L2oc8//xxOpxNTpkwRHSUkGY1G5OQ0rleuqireeOMNTJw4UXCq0HGtFfbaulIe3dhtt93WtJxwWVkZPv30U4wbN05sqBD0q1/9CgsXLkR0dLToKD7T4hKZdLVPP/0Uv/3tb5td16dPH9TV1eH9998XEyrEXG8bv//++3C73Vi0aBG8Xi9+9rOfCUoYelRVhSRJTZc1TWt2mXzn2LFj+NnPfoZnnnkGvXv3Fh0npHz00Ufo2rUrRo8ejdWrV4uO4zOcbtRHPvroI7zzzjuIiIgAABw+fBgpKSlYtmwZIiMjBacLHfX19XjssccQGxuL3//+9zAajaIjhYzc3FyUlJTglVdeAQC8+eab0DQNv/jFLwQnCy2lpaV44okn8Oyzz2L69Omi44Scn/70p6isrIROp8OVK1fQ0NCAGTNm4NlnnxUd7aawrP0kOTkZR44cER0j5Dz++OOIi4vDSy+9BFnmrzi+VF5ejvvvvx8ff/wxLBYL5syZg1//+tdIS0sTHS1kXLhwATNnzsSSJUswevRo0XFC3urVq7Fz5068+uqroqPcNO4Gp6Bx6NAhfP7550hKSsLMmTMBNP6uunTpUsHJQkNCQgIWLlyIefPmNa2wx6L2rT/96U9wuVzNymPOnDm4//77BaaiYMCRNRERUYDjfkQiIqIAx7ImIiIKcCxrIiKiAMeyJiIiCnAsayIiogDHsiYiIgpwLGsiIqIAx7ImIiIKcP8fFv7XpT2lQjcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(x, bins =25, density = True)\n",
    "b = np.linspace(mini, maxi, 100)\n",
    "plt.plot(b,stats.norm.pdf(b, mean, std))\n",
    "plt.xlim(-5,5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Is daily price change significantly different from zero?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 13. Conduct simple hypothesis test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_1sampResult(statistic=1.4743142468193604, pvalue=0.14165011186612425)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.ttest_1samp(amzn_return.sample(252), 0, alternative='two-sided')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Can price movement be described as a random walk?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 14. Create price lags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "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>Close</th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_2</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>2016-06-07</th>\n",
       "      <td>723.739990</td>\n",
       "      <td>726.729980</td>\n",
       "      <td>725.539978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>726.640015</td>\n",
       "      <td>723.739990</td>\n",
       "      <td>726.729980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>727.650024</td>\n",
       "      <td>726.640015</td>\n",
       "      <td>723.739990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-10</th>\n",
       "      <td>717.909973</td>\n",
       "      <td>727.650024</td>\n",
       "      <td>726.640015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-13</th>\n",
       "      <td>715.239990</td>\n",
       "      <td>717.909973</td>\n",
       "      <td>727.650024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Close       lag_1       lag_2\n",
       "Date                                          \n",
       "2016-06-07  723.739990  726.729980  725.539978\n",
       "2016-06-08  726.640015  723.739990  726.729980\n",
       "2016-06-09  727.650024  726.640015  723.739990\n",
       "2016-06-10  717.909973  727.650024  726.640015\n",
       "2016-06-13  715.239990  717.909973  727.650024"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn_close = pd.DataFrame(amzn.Close, columns= ['Close'])\n",
    "amzn_close['lag_1'] = amzn_close.Close.shift(1)\n",
    "amzn_close['lag_2'] = amzn_close.Close.shift(2)\n",
    "amzn_close.dropna(inplace = True)\n",
    "amzn_close.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 15. Fit linear model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "lr = np.linalg.lstsq(amzn_close[['lag_1', 'lag_2']], amzn_close.Close, rcond=None)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "amzn_close['predict'] = np.dot(amzn_close[['lag_1', 'lag_2']], lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Close</th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_2</th>\n",
       "      <th>predict</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-06-07</th>\n",
       "      <td>723.739990</td>\n",
       "      <td>726.729980</td>\n",
       "      <td>725.539978</td>\n",
       "      <td>727.325283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-08</th>\n",
       "      <td>726.640015</td>\n",
       "      <td>723.739990</td>\n",
       "      <td>726.729980</td>\n",
       "      <td>724.580125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-09</th>\n",
       "      <td>727.650024</td>\n",
       "      <td>726.640015</td>\n",
       "      <td>723.739990</td>\n",
       "      <td>727.133955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-10</th>\n",
       "      <td>717.909973</td>\n",
       "      <td>727.650024</td>\n",
       "      <td>726.640015</td>\n",
       "      <td>728.256831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-13</th>\n",
       "      <td>715.239990</td>\n",
       "      <td>717.909973</td>\n",
       "      <td>727.650024</td>\n",
       "      <td>719.144556</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Close       lag_1       lag_2     predict\n",
       "Date                                                      \n",
       "2016-06-07  723.739990  726.729980  725.539978  727.325283\n",
       "2016-06-08  726.640015  723.739990  726.729980  724.580125\n",
       "2016-06-09  727.650024  726.640015  723.739990  727.133955\n",
       "2016-06-10  717.909973  727.650024  726.640015  728.256831\n",
       "2016-06-13  715.239990  717.909973  727.650024  719.144556"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn_close.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "amzn_close.iloc[-252:][['Close', 'predict']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}