Forecasting the Performance of Hedge Fund Styles

Abstract

This article predicts the relative performance of hedge fund investment styles one period ahead using time-varying conditional stochastic dominance tests. These tests allow the construction of dynamic trading strategies based on nonparametric density forecasts of hedge fund returns. During the recent financial turmoil, our tests predict a superior performance of the Global Macro investment style compared to the other `Directional Traders' strategies. The Dedicated Short Bias investment style is, on the other hand, stochastically dominated by the other directional styles. These results are confirmed by simple nonparametric tests constructed from the realized excess returns. Further, by exploiting the cross-validation method for optimal bandwidth parameter selection, we find out which factors have predictive power for the density of hedge fund returns. We observe that different factors have forecasting power for different regions of the returns distribution and, more importantly, Fung and Hsieh factors have power not only for describing the risk premium but also for density forecasting if appropriately exploited.