A Parsimonious Approach for Higher-Order Moments in Portfolio Selection

44 Pages Posted: 13 Feb 2020 Last revised: 13 Apr 2020

See all articles by Khaldoun Khashanah

Khaldoun Khashanah

Stevens Institute of Technology

Majeed Simaan

Stevens Institute of Technology - School of Business

Yusif Simaan

Fordham University - Graduate School of Business

Date Written: April 10, 2020

Abstract

This paper investigates the economic value of higher moments in portfolio selection under estimation risk. It deploys a non-elliptical distribution for the asset returns. Such distribution decomposes the asset returns into two independent stochastic components: a Gaussian and a Bernoulli jump process. Given the adverse effects of estimation risk on portfolio selection, the distribution imposes a parsimonious structure to identify the higher-order moments. The moments can be easily calibrated using the expected maximization algorithm for maximum likelihood estimation. We find that the corresponding portfolio outperforms the conventional mean-variance portfolio as well as the equally weighted (naive) portfolio. Nonetheless, the evidence is more statistically significant when one considers a larger number of assets and a higher level of risk aversion. While this outperformance comes at the cost of a larger turnover, we show that the performance prevails after taking into consideration a transaction cost of 5% per traded dollar.

Keywords: Downside Risk, Statistical Learning, Non-Elliptical Distributions, Multivariate Analysis

JEL Classification: C13, C44, C46, G11

Suggested Citation

Khashanah, Khaldoun and Simaan, Majeed and Simaan, Yusif, A Parsimonious Approach for Higher-Order Moments in Portfolio Selection (April 10, 2020). Available at SSRN: https://ssrn.com/abstract=3523379 or http://dx.doi.org/10.2139/ssrn.3523379

Khaldoun Khashanah

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

Majeed Simaan (Contact Author)

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Yusif Simaan

Fordham University - Graduate School of Business ( email )

113 West 60th Street
Bronx, NY 10458
United States
6462200652 (Phone)

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