Portfolio Selection Optimization Problem Under Systemic Risks

Document Type : Research Paper

Authors

Department of Finance and Banking, Faculty of Accounting and Management Allameh Tabataba`i University, Tehran, Iran

Abstract

Abstract: Portfolio selection is of great importance among financiers, who seek to invest in a financial market by selecting a portfolio to minimize the risk of investment and maximize their profit. Since there is a covariant among portfolios, there are situations in which all portfolios go high or down simultaneously, known as systemic risks. In this study, we proposed three improved meta-heuristic algorithms namely, genetic, dragonfly, and imperialist competitive algorithms to study the portfolio selection problem in the presence of systemic risks. Results reveal that our Imperialist Competitive Algorithm are superior to Genetic algorithm method. After that, we implement our method on the Iran Stock Exchange market and show that considering systemic risks leads to more robust portfolio selection. . Results reveal that our Imperialist Competitive Algorithm are superior to Genetic algorithm method. After that, we implement our method on the Iran Stock Exchange market and show that considering systemic risks leads to more robust portfolio selection.

Keywords

References

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Advances in Industrial Engineering
Volume 54, Issue 2
April 2020
Pages 121-140

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