A Coskewness Shrinkage Approach for Estimating the Skewness of Linear Combinations of Random Variables*

Kris Boudt, Dries Cornilly, Tim Verdonck

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Decision-making in finance often requires an accurate estimate of the coskewness matrix to optimize the allocation to random variables with asymmetric distributions. The classical sample estimator of the coskewness matrix performs poorly for small sample sizes. A solution is to use shrinkage estimators, defined as the convex combination between the sample coskewness matrix and a target matrix. We propose unbiased consistent estimators for the MSE loss function and include the possibility of having multiple target matrices. In a portfolio application, we find that the proposed shrinkage coskewness estimators are useful in mean–variance–skewness efficient portfolio allocation of funds of hedge funds.
Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalJournal of Financial Econometrics
Volume18
Issue number1
Early online date4 Oct 2018
DOIs
Publication statusPublished - 1 Jan 2021

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