TY - JOUR ID - 81728 TI - Portfolio Selection Optimization Problem Under Systemic Risks JO - Advances in Industrial Engineering JA - AIE LA - en SN - AU - Dehghan Dehnavi, Mohammad Ali AU - Bahrololoum, Mohammad Mahdi AU - Peymany Foroushany, Moslem AU - Raeiszadeh, Sayyed Ali AD - Department of Finance and Banking, Faculty of Accounting and Management Allameh Tabataba`i University, Tehran, Iran Y1 - 2020 PY - 2020 VL - 54 IS - 2 SP - 121 EP - 140 KW - Portfolio Selection KW - Systemic Risks KW - Genetic Algorithm KW - Imperialist competitive algorithm DO - 10.22059/jieng.2021.321882.1759 N2 - 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. UR - https://aie.ut.ac.ir/article_81728.html L1 - https://aie.ut.ac.ir/article_81728_cab0fdd2da76993b72c911d1aaaff114.pdf ER -