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Operations Research Transactions >

2024 , Vol. 28 >Issue 1: 77 - 88

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2024.01.006

The study of distributionally robust reward-risk optimization models with moment-based ambiguity set

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  • 1. School of Mathematics and Statistics, Hunan Normal University, Changsha 410081, Hunan, China
    2. School of Mathematics and Statistics, Hunan First Normal University, Changsha 410205, Hunan, China
    3. School of Mathematics and Computational Science, Xiangtan University, Xiangtan 411105, Hunan, China

Received date: 2021-09-08

  Online published: 2024-03-16

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Abstract

This article studies the reward-risk optimization model under the uncertain distribution of random variables. In view of the three typical problems of traditional reward-risk and the background of uncertainty of distributions, a new model of distributionally robust reward-risk optimization is proposed under more general conditions. Based on moment ambiguity set and optimal duality theory, the complex new optimization model is simplified to a nonlinear optimization problem of conventional structure. The equivalence of efficient frontier of three types of distributionally robust reward-risk optimization models is proved theoretically. Numerical example verifies the effectiveness of the theoretical analysis.

Key words： reward-risk optimization problems; distributionally robust optimization; efficient frontier; robust counterpart

Cite this article

Yinghan LI, Xiaojiao TONG, Liu YANG . The study of distributionally robust reward-risk optimization models with moment-based ambiguity set[J]. Operations Research Transactions, 2024 , 28(1) : 77 -88 . DOI: 10.15960/j.cnki.issn.1007-6093.2024.01.006

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