We apply four machine learning methods to cross-sectional return prediction for hedge fund selection. We equip the forecast model with a set of idiosyncratic features, which are derived from historical returns of a hedge fund and capture a variety of fund-specific information. Evaluating the...

We show that fund-specific return skewness is associated with managerial skill and future hedge fund performance. Specifically, skewness in fund returns reflects managerial skill in avoiding large drawdowns. Using a new measure of investment skill that accounts for this managerial ability, we...

Cette thèse est composée de trois articles qui étudient les fonds alternatifs selon trois vue différentes: au niveau des fonds eux-mêmes, au niveau de la construction de portefeuilles et finalement au niveau du marché. 1. Au niveau des fonds alternatifs: Le premier article se concentre sur...

While the majority of the predictability literature has been devoted to the predictability of traditional asset classes, the literature on the predictability of hedge fund returns is quite scanty. We focus on assessing the out-of-sample predictability of hedge fund strategies by employing an...

This paper develops a unified approach to comprehensively analyze individual hedge fund return predictability, both in- and out-of-sample. In-sample, we find that variation in hedge fund performance across changing market conditions is widespread and economically significant. The predictability...

This article analyzes the effect of liquidity risk on the performance of equity hedge fund portfolios. Similarly to Avramov, Kosowski, Naik, and Teo, we observe that, before accounting for the effect of liquidity risk, hedge fund portfolios that incorporate predictability in managerial skills...