@fawce: Interesting post, thanks for sharing.
One might ask what is the difference between correlation and cointegration. While two stocks must be correlated in order for them to be cointegrated, the reverse must not be true. Critically, for stock prices X and Y to be cointegrated, there must exist a beta so that eps = Y - beta * X with eps being stationary (i.e. the resulting line does not trail off into infinity but hovers around the same value).
What I'm a little puzzled by is that I've seen the regression (OLS) to be estimated sometimes with and other times without a Y-intercept. To my mind, estimating with an intercept should do a better job, but when I add an intercept to your code it does not work as well. Anyone has an explanation for this?
P.S.: I also included an adf test which tests whether the resulting spread is stationary but it takes too long to compute and the backtest fails. I think it would be nice if some calls (every couple of days when I run the regression and more advanced test) the algo would be allowed to run for a longer time.
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