We know that the stock market fell dramatically in October, 1987. We could choose a stock to test the volatility before and after October, 1987. For instance, we could use Ford Motor Corp, with a ticker of F, to illustrate how to test the equality of variance before and after the market crash in 1987. In the following Python program, we define a function called ret_f() to retrieve daily price data from Yahoo! Finance and estimate its daily returns:
import scipy as sp from matplotlib.finance import quotes_historical_yahoo import numpy as np # input area ticker='F' # stock begdate1=(1982,9,1) # starting date for period #1 enddate1=(1987,9,1) # ending date for period #1 begdate2=(1987,12,1) # starting date for period #2 enddate2=(1992,12,1) # ending date for period #2 # define a function def ret_f(ticker,begdate,enddate): p = quotes_historical_yahoo(ticker, begdate, enddate,asobject=True, adjusted...