Research and publications

Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection

In the presence of non-normally distributed asset returns, optimal portfolio selection techniques require estimates for variance-covariance parameters, along with estimates for higher-order moments and comoments of the return distribution. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This paper extends the existing literature, which has mostly focused on the covariance matrix, by introducing improved estimators for the coskewness and cokurtosis parameters. A revisited version of this paper was published in the April 2010 issue of the Review of Financial Studies.

Author(s):

Lionel Martellini, Volker Ziemann

Summary:

In the presence of non-normally distributed asset returns, optimal portfolio selection techniques require estimates for variance-covariance parameters, along with estimates for higher-order moments and comoments of the return distribution. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This paper extends the existing literature, which has mostly focused on the covariance matrix, by introducing improved estimators for the coskewness and cokurtosis parameters. A revisited version of this paper was published in the April 2010 issue of the Review of Financial Studies.

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Type :	Working paper
Date :	19/02/2010
Keywords :	Alternative Investments

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