Factor-based portfolio optimization

A parsimonious factor model mitigates idiosyncratic noise in historical data for portfolio optimization. We use market predictors and machine learning to incorporate forward-looking information into expected returns. The combination of the factor model and forward-looking returns improves out-of-sample performance, conforming to the theoretical assumption that the mean and variance correspond to future returns.