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Volumn 15, Issue 2, 2009, Pages 91-115

Fund of hedge funds portfolio selection: A multiple-objective approach

Author keywords

Asset allocation; Diversification; Hedge funds; Kurtosis; Optimisation; Skewness

Indexed keywords


EID: 68349128465     PISSN: 17539641     EISSN: 1753965X     Source Type: Journal    
DOI: 10.1057/jdhf.2009.1     Document Type: Article
Times cited : (54)

References (37)
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    • Of course, this implicitly assumes that investors' utility functions are of higher order than quadratic. For details, see Jean, W.H, 1971) The extension of portfolio analysis to three or more parameters. Journal of Financial and Quantitative Analysis 6: 505-515; and Scott, R.C. and Horvath, P.A, 1980) On the direction of preference for moments of higher order than the variance. Journal of Finance 354, 915-919
    • Of course, this implicitly assumes that investors' utility functions are of higher order than quadratic. For details, see Jean, W.H. (1971) The extension of portfolio analysis to three or more parameters. Journal of Financial and Quantitative Analysis 6: 505-515; and Scott, R.C. and Horvath, P.A. (1980) On the direction of preference for moments of higher order than the variance. Journal of Finance 35(4), 915-919.
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    • Examples in the context of hedge funds include Hagelin and Pramborg (Hagelin, N. and Pramborg, B, 2004) Evaluating gains from diversifying into hedge funds using dynamic investment strategies. In: B. Schachter (ed, Intelligent Hedge Fund Investing. London: Risk Waters Group, pp. 423-445, who develop a discrete-time dynamic investment model based on an investor with a power utility function, and Barés et al (Barés, P.-A, Gibson, R. and Gyger, S, 2002) Hedge Fund Allocation with Survival Uncertainty and Investment Constraints. Working paper, Swiss Federal Institute of Technology Lausanne EPEL, who examine the impact of hedge fund survival uncertainty on optimal allocations in an expected utility framework. In a more general asset return context, Harvey et al (Harvey, C.R, Liechty, J.C, Liechty, M.W. and Müller, P, 2004) Portfolio Selection with Higher Moments. Working paper, Duke University, consider utility- based portfolio optimisation
    • Examples in the context of hedge funds include Hagelin and Pramborg (Hagelin, N. and Pramborg, B. (2004) Evaluating gains from diversifying into hedge funds using dynamic investment strategies. In: B. Schachter (ed.) Intelligent Hedge Fund Investing. London: Risk Waters Group, pp. 423-445.) who develop a discrete-time dynamic investment model based on an investor with a power utility function, and Barés et al (Barés, P.-A., Gibson, R. and Gyger, S. (2002) Hedge Fund Allocation with Survival Uncertainty and Investment Constraints. Working paper, Swiss Federal Institute of Technology Lausanne EPEL.) who examine the impact of hedge fund survival uncertainty on optimal allocations in an expected utility framework. In a more general asset return context, Harvey et al (Harvey, C.R., Liechty, J.C., Liechty, M.W. and Müller, P. (2004) Portfolio Selection with Higher Moments. Working paper, Duke University.) consider utility- based portfolio optimisation using a new Bayesian decision theoretic framework, which incorporates higher moments and estimation error.
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    • Common choices are logarithmic, power and negative exponential utility functions. These functions satisfy the desirable properties: (a) non-satiety with respect to wealth, (b) risk aversion and (c) risk assets are not inferior goods. For more details, see Grauer, R.R. (2004) Are the Effects of Estimation Risk on Asset Allocation Problems Overstated? Working paper, Simon Fraser University.
    • Common choices are logarithmic, power and negative exponential utility functions. These functions satisfy the desirable properties: (a) non-satiety with respect to wealth, (b) risk aversion and (c) risk assets are not inferior goods. For more details, see Grauer, R.R. (2004) Are the Effects of Estimation Risk on Asset Allocation Problems Overstated? Working paper, Simon Fraser University.
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    • It is worth noting, however, that some of these utility-based approaches do not guarantee the existence of an optimal solution
    • It is worth noting, however, that some of these utility-based approaches do not guarantee the existence of an optimal solution.
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    • The optimal number of funds (within a strategy group) is an interesting area which will be dealt with in a subsequent paper. In part, the number of funds reflects a trade-off between possible diversification benefits and the cost of finding and monitoring high-quality funds
    • The optimal number of funds (within a strategy group) is an interesting area which will be dealt with in a subsequent paper. In part, the number of funds reflects a trade-off between possible diversification benefits and the cost of finding and monitoring high-quality funds.
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    • Note that this also implies a strong negative co-skewness between hedge funds and the stock market
    • Note that this also implies a strong negative co-skewness between hedge funds and the stock market.
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    • With more and more convertible arbitrage funds competing for the same trades, some funds may decide to no longer hedge their credit risk exposure to compensate for the loss of margin. Those funds can be expected to exhibit a more aggressive risk profile, especially lower co-skewness with other funds and equity
    • With more and more convertible arbitrage funds competing for the same trades, some funds may decide to no longer hedge their credit risk exposure to compensate for the loss of margin. Those funds can be expected to exhibit a more aggressive risk profile, especially lower co-skewness with other funds and equity.
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    • See also
    • See also: Black, F. and Litterman, R. (1992) Global portfolio optimization. Financial Analysts Journal 48(5): 28-43.
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    • In practice, these constraints could reflect the real or perceived need for fund managers, particularly new ones, to match closely the risk profile of the fund's peer group. They could also reflect constraints explicitly imposed by the fund's investors.
    • In practice, these constraints could reflect the real or perceived need for fund managers, particularly new ones, to match closely the risk profile of the fund's peer group. They could also reflect constraints explicitly imposed by the fund's investors.
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