Robust Portfolio Selection Using Vine Copulas

12 Pages Posted: 28 Nov 2020

See all articles by Yingwei Han

Yingwei Han

School of Economics and Management,China University of Geosciences, Beijing

Ping Li

Beihang University (BUAA) - School of Economic and Management Science

Date Written: October 14, 2020

Abstract

Portfolio optimization problems involving Conditional Value-at-Risk (CVaR) are often computationally intractable and require complete information about the distribution of returns, which is rarely available in practice. These difficulties are compounded when the portfolio contains a lot of assets. In this paper, we consider the worst-case CVaR (WCVaR) under mixture of vine copulas distribution uncertainty, which can capture complex and hidden dependence patterns in multivariate data.We compare the out-of-sample performance of the robust strategies based on the mixture of R-vine copulas, mixture of C-vine copulas, mixture of D-vine copulas and nominal CVaR method. The experimental study shows that the robust models based on mixture of R-Vine copulas and mixture of C-Vine copulas perform the best in terms of average returns, Sharpe ratio and cumulative returns. The performance of robust mixture of D-Vine copulas model might be advantageous when the correlation between assets is low.

Keywords: Robust optimization,Conditional Value at Risk, Dependence structures,Vine copulas

JEL Classification: G11

Suggested Citation

Han, Yingwei and Li, Ping, Robust Portfolio Selection Using Vine Copulas (October 14, 2020). Available at SSRN: https://ssrn.com/abstract=3711266 or http://dx.doi.org/10.2139/ssrn.3711266

Yingwei Han (Contact Author)

School of Economics and Management,China University of Geosciences, Beijing ( email )

NO. 29, Xueyuan Road, Haidian District
Beijing, 100083
China

Ping Li

Beihang University (BUAA) - School of Economic and Management Science ( email )

37 Xue Yuan Road
Beijing 100083
China

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