We apply machine learning techniques and use stock characteristics to predict the cross-section of stock returns in 33 international markets. We conduct a stringent out-of-sample test to examine concerns about overfitting: the models are trained with past U.S. data and used to predict...

We study capital allocations to managers with two mutual funds, and show that investors learn about managers from their performance records. Flows into a fund are predicted by the manager's performance in his other fund, especially when he outperforms and when signals from the other fund are...