January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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We present another method of investigating the leverage effect (fact 5). To do so, we use the VIX (CBOE Volatility Index), which is a popular metric of the stock market's expectation regarding volatility. The measure is implied by option prices on the S&P 500 index. We take the following steps:
- Download and preprocess the prices of the S&P 500 and VIX:
df = yf.download(['^GSPC', '^VIX'], start='1985-01-01', end='2018-12-31', progress=False)df = df[['Adj Close']]df.columns = df.columns.droplevel(0)df = df.rename(columns={'^GSPC': 'sp500', '^VIX': 'vix'})
- Calculate the log returns (we can just as well use percentage change-simple returns):
df['log_rtn'] = np.log(df.sp500 / df.sp500.shift(1))df['vol_rtn'] = np.log(df.vix ...
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