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Information Journal Paper

Title

Portfolio Selection Optimization Problem Under Systemic Risks

Pages

  121-140

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.

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    APA: Copy

    DEHGHAN DEHNAVI, MOHAMMAD ALI, BAHROLOLOUM, MOHAMMAD MAHDI, peymani foroushani, moslem, & Raeiszadeh, Sayed Ali. (2020). Portfolio Selection Optimization Problem Under Systemic Risks. ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING), 54(2), 121-140. SID. https://sid.ir/paper/993965/en

    Vancouver: Copy

    DEHGHAN DEHNAVI MOHAMMAD ALI, BAHROLOLOUM MOHAMMAD MAHDI, peymani foroushani moslem, Raeiszadeh Sayed Ali. Portfolio Selection Optimization Problem Under Systemic Risks. ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING)[Internet]. 2020;54(2):121-140. Available from: https://sid.ir/paper/993965/en

    IEEE: Copy

    MOHAMMAD ALI DEHGHAN DEHNAVI, MOHAMMAD MAHDI BAHROLOLOUM, moslem peymani foroushani, and Sayed Ali Raeiszadeh, “Portfolio Selection Optimization Problem Under Systemic Risks,” ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING), vol. 54, no. 2, pp. 121–140, 2020, [Online]. Available: https://sid.ir/paper/993965/en

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