{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Watch your tail!\n", "\n", "Allen Downey 2019\n", "\n", "[MIT License](https://en.wikipedia.org/wiki/MIT_License)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "from empiricaldist import Pmf\n", "\n", "from utils import decorate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Loading historical data from the S&P 500:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(17511, 6)" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# https://finance.yahoo.com/quote/%5EGSPC/history?period1=-630961200&period2=1565150400&interval=1d&filter=history&frequency=1d\n", "\n", "df = pd.read_csv('yahoo/yahoo_sp500.csv', index_col=0, parse_dates=True)\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Open | \n", "High | \n", "Low | \n", "Close | \n", "Adj Close | \n", "Volume | \n", "
---|---|---|---|---|---|---|
Date | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
1950-01-03 | \n", "16.66 | \n", "16.66 | \n", "16.66 | \n", "16.66 | \n", "16.66 | \n", "1260000 | \n", "
1950-01-04 | \n", "16.85 | \n", "16.85 | \n", "16.85 | \n", "16.85 | \n", "16.85 | \n", "1890000 | \n", "
1950-01-05 | \n", "16.93 | \n", "16.93 | \n", "16.93 | \n", "16.93 | \n", "16.93 | \n", "2550000 | \n", "
1950-01-06 | \n", "16.98 | \n", "16.98 | \n", "16.98 | \n", "16.98 | \n", "16.98 | \n", "2010000 | \n", "
1950-01-09 | \n", "17.08 | \n", "17.08 | \n", "17.08 | \n", "17.08 | \n", "17.08 | \n", "2520000 | \n", "