In this paper we investigate the claim that hedge funds offer investors a superior riskreturn trade-off. We do so using a continuous time version of Dybvig's (1988a, 1988b) payoff distribution pricing model. The evaluation model, which does not require any assumptions with regard to the return distribution of the funds in question, is applied to the monthly returns of 77 hedge funds and 13 hedge fund indices over the period May 1990-April 2000. The results show that as a stand-alone investment hedge funds do not offer a superior risk-return profile. We find 12 indices and 72 individual funds to be inefficient, with the average efficiency loss amounting to 2.76% per annum for indices and 6.42% for individual funds. Part of the inefficiency cost of individual funds can be diversified away. Funds of funds, however, are not the preferred vehicle for this as their performance appears to suffer badly from their double fee structure. Looking at hedge funds in a portfolio context results in a marked improvement in the evaluation outcomes. Seven of the 12 hedge fund indices and 58 of the 72 individual funds classified as inefficient on a stand-alone basis are capable of producing an efficient payoff profile when mixed with the S&P 500. The best results are obtained when 10-20% of the portfolio value is invested in hedge funds. .

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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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