January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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Fact 3
Autocorrelation (also known as serial correlation) measures how similar is a given time series to the lagged version of itself, over successive time intervals.
To investigate whether there is significant autocorrelation in returns, we created the autocorrelation plot using plot_acf from the statsmodels library. We inspected 50 lags and used the default alpha=0.05, which means that we also plotted the 95% confidence interval. Values outside of this interval can be considered statistically significant.
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