We find economically and statistically significant gains when using machine learning for portfolio allocation between the market index and risk-free asset. Optimal portfolio rules for time-varying expected returns and volatility are implemented with two Random Forest models. One model is...

This paper shows that portfolio constraints have important implications for management compensation and performance evaluation. In particular, in the presence of portfolio constraints, allowing for benchmarking can be beneficial. Benchmark design arises as an alternative effort inducement...