Rank Alpha Funds of Hedge Funds

Abstract

This article examines the performance of hedge fund portfolios when fund selection is based on the rank of a fund's alpha, rather than the estimated value of the alpha. Estimated alphas can vary significantly depending on the model used and hence induce a high degree of model risk in portfolio optimization. The authors find, even for the simplest factor models, that ranking funds according to their alpha estimates is an efficient selection process. In an extensive out-of-sample historical analysis, funds of funds that are selected in this manner are shown to outperform an equally weighted index of all funds, minimum variance portfolios of randomly selected funds and portfolios that are optimized using estimated alpha values. Of the four factor models considered here the best out-of-sample performance is obtained using the rank alphas from the principal components factor model.