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 …

Extending previous work on hedge fund pricing, this paper introduces the idea of modelling
the conditional quantiles of hedge fund returns using a set of risk factors. Quantile …

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 …

This paper advances the research on the predictability in hedge fund returns, using a broad
set of risk factors within a variety of different prediction models. Accounting for the fact that …

Extending previous work on hedge fund return predictability, this paper introduces the idea
of modelling the conditional distribution of hedge fund returns using Student's t full-factor …

This study examines the effects of systemic risk on global hedge fund returns. We consider
systemic risk as a conditional information variable to predict the underlying exposures to …

The academic literature has amassed overwhelming evidence indicating that investment
opportunities are hardly driven in a simplistic way by business cycle conditions, when …

Existe sólo dos teorías con un riguroso fundamento para calcular el equilibrio entre el riesgo
y la rentabilidad de los activos: el CAPM y el APT. Sin embargo, a diferencia del CAPM, el …

We report systematic, out-of-sample evidence on the benefits to an already well-diversified
investor that may derive from further diversification into various hedge fund strategies. We …

Hedge fund factor analysis is growing in popularity. While some investors simply use
traditional factor β s from the stock and bond markets, these factors do not fully explain …