Portfolio Selection Based on Mean-Generalized Variance Analysis: Evidence from the G20 Stock Markets

Zongxin Li (), Yongchang Hui, Wing-Keung Wong and Ruiyue Lin ()
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Zongxin Li: School of Economics & Management, Northwest University, Xi’an, Shaanxi 710127, P. R. China
Yongchang Hui: School of Economics and Finance, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, P. R. China
Wing-Keung Wong: Department of Finance, Fintech & Blockchain Research Center, and Big Data Research Center, Asia University, Wufeng, Taichung 41354, Taiwan4Department of Medical Research, China Medical University Hospital, Wufeng, Taichung 41354, Taiwan5Business, Economic and Public Policy Research Centre, Hong Kong Shue Yan University, Hong Kong
Ruiyue Lin: School of Mathematics and Physics, Wenzhou University, Wenzhou, Zhejiang 325035, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2025, vol. 42, issue 03, 1-24

Abstract: Modern finance theories have been increasingly paying attention to nonlinear and asymmetric features of stock returns. In this paper, we extend the concept of covariance to generalized covariance by using Generalized Measure of Correlation (GMC). Based on the generalized covariance which is capable of catching the nonlinearity and asymmetry in stock (index) returns, we propose a mean-generalized variance portfolio selection model which considers the gross-exposure constraint. Furthermore, we propose the corresponding nonparametric estimation approach and the global optimization algorithm to enhance the applicability of our new model. Empirical studies on G20 stock markets support that a portfolio considering nonlinear and asymmetric features among the international markets would outperform traditional ones based on mean-variance optimization and equal weighting strategy in terms of return and flexibility.

Keywords: Generalized measures of correlation; generalized covariance; risk measure; portfolio optimization; G20 stock markets (search for similar items in EconPapers)
JEL-codes: C51 C53 G11 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0217595924500167

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