The Art of Investing in Hedge Funds: Fund Selection and Optimal Allocations

Abstract

With institutional investors increasingly involved in alternative investments, portfolio optimisation within a large universe of hedge funds has become a key area for research. This paper develops a portfolio construction model that is specifically designed for funds of hedge funds, incorporating specific controls for operational limitations, data biases and incompleteness. Absolute performance is targeted by selecting funds according to their alpha estimated with factor models. Whilst different factor models provide quite different estimates of a hedge fund's alpha, we can still use the ranking produced by them in the fund selection process. In an extensive out-of-sample historical analysis, funds of funds that are selected in this way and then allocated using constrained minimum variance optimisation are shown to perform much better than the equally weighted portfolio of all funds, or minimum variance portfolios of randomly selected funds. This is true even when hedge funds are selected according to their alphas produced by simple factor models. The best out-of-sample performance is obtained, out of the four factor models considered in this analysis, with the statistical factor model.