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.
Professor of Finance, EDHEC Business School
French Ministry of Economy, Industry and Employment
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. We find that the use of these enhanced estimates generates a significant improvement in investors' welfare. We also find that it is only when improved estimators are used that portfolio selection with higher-order moments dominates mean-variance analysis from an out-of-sample perspective.
|Research Cluster :||Finance|