A Hybrid Model of Stochastic Dynamic Programming and Genetic Algorithm for Multistage Portfolio Optimization with GlueVaR Risk Measurement

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Ghandehari Maryam; AZAR ADEL; YAZDANIAN AHMAD REZA; Golarzi Gholamhossein

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Journal: Industrial Management Journal Year:2019 | Volume:11 | Issue:3 Page(s): 517-542

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Title

A Hybrid Model of Stochastic Dynamic Programming and Genetic Algorithm for Multistage Portfolio Optimization with GlueVaR Risk Measurement

Author(s)

Ghandehari Maryam | AZAR ADEL | YAZDANIAN AHMAD REZA | Golarzi Gholamhossein | Issue Writer Certificate

Keywords

Portfolio optimizationQ1

Stochastic dynamic programmingQ1

GlueVaR risk measurementQ1

Genetic algorithmQ2

Scenario constructiomQ1

Abstract

Objective: The selection of an optimal investment portfolio for a long-term period does not seem logical. So the investors should update their investment portfolios over specific time periods if needed. Since the problem dimensions significantly increase after the periods, a definitive solution to the problem is not achievable. Methods: In this regard, the Multistage Approximate Stochastic dynamic programming has been used to make the best portfolio over each period by using a stochastic return rate. The Monte Carlo was used for scenario development, and GlueVar was selected as a risk measurement criterion. The approximation technique was used to resolve for large dimensions; however, some optimized solutions may be eliminated so we used the Genetic algorithm for the rapid search around the optimal solution to obtain a better one, if possible. Results: Top 100 companies listed in the Tehran Stock Exchange between 2011 and 2017 were investigated. This study investigated and compared the return and risk of investment portfolios based on the proposed method, Genetic algorithm, and stock portfolio with equal weights. The modeling was done with MATLAB and tests were carried out with SPSS. Conclusion: The results indicated a higher performance of the proposed method in comparison with the other mentioned methods.

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APA: Copy

Ghandehari, Maryam, AZAR, ADEL, YAZDANIAN, AHMAD REZA, & Golarzi, Gholamhossein. (2019). A Hybrid Model of Stochastic Dynamic Programming and Genetic Algorithm for Multistage Portfolio Optimization with GlueVaR Risk Measurement. JOURNAL OF INDUSTRIAL MANAGEMENT, 11(3 ), 517-542. SID. https://sid.ir/paper/139999/en

Vancouver: Copy

Ghandehari Maryam, AZAR ADEL, YAZDANIAN AHMAD REZA, Golarzi Gholamhossein. A Hybrid Model of Stochastic Dynamic Programming and Genetic Algorithm for Multistage Portfolio Optimization with GlueVaR Risk Measurement. JOURNAL OF INDUSTRIAL MANAGEMENT[Internet]. 2019;11(3 ):517-542. Available from: https://sid.ir/paper/139999/en

IEEE: Copy

Maryam Ghandehari, ADEL AZAR, AHMAD REZA YAZDANIAN, and Gholamhossein Golarzi, “A Hybrid Model of Stochastic Dynamic Programming and Genetic Algorithm for Multistage Portfolio Optimization with GlueVaR Risk Measurement,” JOURNAL OF INDUSTRIAL MANAGEMENT, vol. 11, no. 3 , pp. 517–542, 2019, [Online]. Available: https://sid.ir/paper/139999/en

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