CVaR-based robust models for portfolio selection

Yufei Sun; Ee Ling Grace Aw; Bin Li; Kok Lay Teo; Jie Sun

doi:10.3934/jimo.2019032

Article Contents

2020, Volume 16, Issue 4: 1861-1871. Doi: 10.3934/jimo.2019032

This issue Previous Article Determining personnel promotion policies in HEI Next Article Higher-order symmetric duality for multiobjective programming with cone constraints

CVaR-based robust models for portfolio selection

1.
School of Mathematical Sciences, Chongqing Normal University, No. 12 Tianchen Road, Shapingba, Chongqing 400047, China
2.
Department of Mathematics and Statistics, Curtin University, GPO Box U1987 Perth, Western Australia 6845, Australia
3.
College of Electrical Engineering and Information Technology, Sichuan University, No. 24 Yihuan Road, Chengdu, Sichuan 610065, China
4.
School of Science, Hebei University of Technology, No. 5340 Xiping Road, Beichen, Tianjin 300130, China

^* Corresponding author: Bin Li
^* Corresponding author: Bin Li

The first and the third to fifth author were saddened by Grace's passing, and dedicate this joint paper to her memory

Received: March 31, 2018

Revised: September 30, 2018

Early access: May 2019

Published: May 2020

This work was partially supported by a grant from National Natural Science Foundation of China under number 61701124, a grant from Science and Technology on Space Intelligent Control Laboratory for National Defence, No. KGJZDSYS-2018-03, a grant from Sichuan Science and Technology Program under number 2019YJ0105, and a grant from Fundamental Research Funds for the Central Universities (China)

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Abstract

This study relaxes the distributional assumption of the return of the risky asset, to arrive at the optimal portfolio. Studies of portfolio selection models have typically assumed that stock returns conform to the normal distribution. The application of robust optimization techniques means that only the historical mean and variance of asset returns are required instead of distributional information. We show that the method results in an optimal portfolio that has comparable return and yet equivalent risk, to one that assumes normality of asset returns.

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Mathematics Subject Classification: Primary: 90C15.

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