We propose a new approach for estimating expected returns on individual stocks from a large number of firm characteristics. We treat expected returns as latent variables and apply the partial least squares (PLS) estimator that filters them out from the characteristics under an assumption that...

This paper studies the interplay between information aggregation and p-hacking in the context of predicting stock returns. The standard information aggregation techniques exacerbate p-hacking by increasing the probability of the type I error. We propose an aggregation technique, which is a...