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 relative abnormal return, alpha. Whilst different factor models provide quite different estimates of a hedge fund’s alpha, we find that ranking funds according to their alpha is an efficient 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 the simplest factor model. Of the four factor models considered in this analysis the best out-of-sample performance is obtained using the statistical factor model.
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