The classic mean-reversion strategy is to calculate an "expected return" (alpha) by computing the raw return for each security and then remove the part which you think is market driven. Statistically you just do a PCA and remove the projection of the return over the sum of eigenspaces. Then you will trade the residuals as a reversion signal.

Today I looked at cross sectional correlation (every stock every day in the same vector) of stock return against the forward returns (return of the stock in the future) and realized that the correlation was better than the correlation between residuals and forward returns.

My question is then: is this fact well known, is that the case all day or just around particular moments? I have a personal explanation but I am curious to see what you think of it.

  • $\begingroup$ What time horizon is used for calculating the returns (daily, monthly,...) and what time lag is considered for the cross sectional correlation? Furthermore, did you use raw returns or excess returns, i.e. over the risk-free rate? $\endgroup$ Aug 30, 2018 at 13:29


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