Optimal Hedge Fund Allocation with Improved Estimates for Coskewness and Cokurtosis Parameters

Since hedge fund returns are not normally distributed, mean-variance optimisation techniques, which would lead to substantial welfare losses from the investor’s perspective, need to be replaced by optimisation procedures incorporating higher-order moments and comoments.

Author(s):

Asmerilda Hitaj

Junior researcher at the University of Milano - Bicocca (Italy).

Lionel Martellini

Professor of finance at EDHEC Business School and scientific director of EDHEC-Risk Institute.

Giovanni Zambruno

Holds the chair of Mathematical Finance at the University of Milano - Bicocca.

In this context, optimal portfolio decisions involving hedge fund style allocation require not only estimates for covariance parameters but also estimates for coskewness and cokurtosis parameters. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This paper presents an application of the improved estimators for higherorder co-moment parameters, recently introduced by Martellini and Ziemann (2010), in the context of hedge fund portfolio optimisation. We find that the use of these enhanced estimates generates a significant improvement for investors in hedge funds. We also find that it is only when improved estimators are used that portfolio selection with higherorder moments consistently dominates mean-variance analysis from an out-ofsample perspective. Our results have important potential implications for hedge fund investors and hedge fund of funds managers who routinely use portfolio optimisation procedures incorporating higher moments.
Pdf
Optimal Hedge Fund Allocation with Improved Estimates for Coskewness and Cokurto...
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Type: EDHEC Publication
Date: le 28/09/2010
Extra information : For more information, please contact Joanne Finlay, EDHEC Research and Development Department [ joanne.finlay@edhec.edu ] The contents of this paper do not necessarily reflect the opinions of EDHEC Business School.
Research Cluster : Finance

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