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I'm trying to detect return predictability by regressing stock returns on the first couple of principal components of a set of macroeconomic variables. I'm doing this for different stock styles such as small, value and momentum stocks. Since I don't know at which lag I should insert these principal components, I'm hoping to find someone who can help me out.

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Later on I would use these principal components in another regression that looks like this:

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  • $\begingroup$ Maybe you should first implement an automatic selection algorithm which starts with a lot of possible lags then gradually removes them by performing new regressions. It stops as soon as all your coefficients are statistically significant. Let data talk. $\endgroup$ – Lisa Ann May 1 at 16:07

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