is an Associate at UBS (London). She is a Structurer in the Fund Derivatives Structuring team. Her research is on the detailed characterisation of hedge fund portfolio returns and optimisation within a mean-variance-skewnesskurtosis framework.Correspondence: Ryan J. Davies, Finance Division, Babson College, 224 Tomasso Hall, Babson Park, MA 02457-0310, USA E-mail: rdavies@babson.edu PRACTICAL APPLICATIONS Hedge funds exhibit complex, non-normal return distributions. In this context, it is difficult for investors to determine how much capital to allocate across different hedge fund strategies. Standard mean-variance portfolio theory and performance measures based on it (for example, the Sharpe ratio) may be inappropriate. The paper proposes an alternative portfolio allocation technique based on polynomial goal programming (PGP) that is simple to implement and computationally robust.ABSTRACT This paper develops a technique for fund of hedge funds to allocate capital across different hedge fund strategies and traditional asset classes. Our adaptation of the polynomial goal programming optimisation method incorporates investor preferences for higher return moments, such as skewness and kurtosis, and provides computational advantages over rival methods. We show how optimal allocations depend on the interaction between strategies, as measured by covariance, co-skewness and co-kurtosis. We also demonstrate the importance of constructing 'like for like' representative portfolios that reflect the investment opportunities available to different-sized funds. Our empirical results www.palgrave-journals.com/jdhf/ reveal the importance of equity market neutral funds as volatility and kurtosis reducers and of global macro funds as portfolio skewness enhancers.

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