A novel MOPSO-SODE algorithm for solving three-objective SR-ES-TR portfolio optimization problem

被引：9

作者：

Chen, Yinnan ^{[1
,2
]}

Zhao, Xinchao ^{[1
,2
]}

Hao, Junling ^{[3
]}

机构：

[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China

[2] Beijing Univ Posts & Telecommun, Key Lab Math & Informat Networks, Minist Educ, Beijing, Peoples R China

[3] Univ Int Business & Econ, Sch Stat, Beijing 100029, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2023年 / 233卷

基金：

北京市自然科学基金;

关键词：

Portfolio optimization; Sortino ratio; Expected shortfall; Turnover rate; Multi-objective swarm intelligence algorithm; PARTICLE SWARM OPTIMIZATION; MULTIOBJECTIVE EVOLUTIONARY ALGORITHM; SELECTION; INTELLIGENCE; MODEL; SKEWNESS;

D O I：

10.1016/j.eswa.2023.120742

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the development of financial market, people invest their savings into different financial products to increase return. However, financial market is an extremely complex system, where investment opportunities and risk often coexist. For investors, it is necessary to take effective measures to avoid risk while obtaining considerable return. In recent decades, actively managing investment in the form of a portfolio is widely accepted by investors. In this paper, we propose a new three-objective Sortino ratio-expected shortfall-turnover rate (SR-ES-TR) portfolio optimization (PO) model. The Sortino ratio is used to measure the risk-adjusted rate of return. The expected shortfall is used to measure the tail risk of a portfolio. Portfolio liquidity risk is characterized by turnover rate. We constructed a portfolio of ten stocks and solved the SR-ES-TR model by the novel MOPSO-SODE algorithm. Compared with other four multi-objective algorithms, the better performance and validity in solving SR-ES-TR model by MOPSO-SODE algorithm have been verified.

引用

页数：10

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