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

delete2023-12-01
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PRE
AI
Y
Yinnan Chen
DOI:10.1016/j.eswa.2023.120742delete
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摘要

摘要

En 中文
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.
Keyword:
Portfolio optimization
Sortino ratio
Expected shortfall
Turnover rate
Multi-objective swarm intelligence algorithm

期刊

Expert Systems with Applications 封面图
Expert Systems with Applications
IF:
7.5
论文数:
2.9W
被引数:
10.2W

机构

B
beijing university of posts & telecommunications
学者数:
1.4W
论文数: 1.2W
被引数: 9
U
university of international business & economics
学者数:
1.6K
论文数: 2.1K
被引数: 5
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引用论文

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