Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO
Despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. In this paper, MOEAs ha...
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| Format: | Article |
| Language: | fas |
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University of Tehran
2014-09-01
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| Series: | تحقیقات مالی |
| Subjects: | |
| Online Access: | https://jfr.ut.ac.ir/article_50715_585cb96acf8f5ee88526fdd187a14bd5.pdf |
| _version_ | 1828394388399587328 |
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| author | Mahsa Rajabi Hamid Khaloozadeh |
| author_facet | Mahsa Rajabi Hamid Khaloozadeh |
| author_sort | Mahsa Rajabi |
| collection | DOAJ |
| description | Despite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. In this paper, MOEAs have been used for solving multi-objective portfolio optimization problem in Tehran stock market. For this purpose, Non-dominated Sorting Genetic Algorithm (NSGA_II) and Multi-objective Particle Swarm Optimization (MOPSO), as two common approaches, were compared with each other. Using pareto front, investors can choose optimal portfolio based on different risks and returns. Two objectives of the problem are return and risk of portfolio and CVaR is the risk metric. In order to solve the problem, three real-world constraints were considered. The results indicate that these approaches have a high performance in constraint portfolio optimization. |
| first_indexed | 2024-12-10T07:55:12Z |
| format | Article |
| id | doaj.art-79f5e6a5a86d4d6e988b7f19e66bca04 |
| institution | Directory Open Access Journal |
| issn | 1024-8153 2423-5377 |
| language | fas |
| last_indexed | 2024-12-10T07:55:12Z |
| publishDate | 2014-09-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | تحقیقات مالی |
| spelling | doaj.art-79f5e6a5a86d4d6e988b7f19e66bca042022-12-22T01:56:56ZfasUniversity of Tehranتحقیقات مالی1024-81532423-53772014-09-0116225327010.22059/jfr.2014.5071550715Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSOMahsa Rajabi0Hamid Khaloozadeh1PhD., Electrical and Control Engineering, K. N. Toosi University of TechnologyProf. , K. N. Toosi University of TechnologyDespite the growing use of evolutionary multi-objective optimization algorithms in different categories of science, these algorithms as a powerful tool in portfolio optimization and specially solving multi-objective portfolio optimization problem is still in its early stages. In this paper, MOEAs have been used for solving multi-objective portfolio optimization problem in Tehran stock market. For this purpose, Non-dominated Sorting Genetic Algorithm (NSGA_II) and Multi-objective Particle Swarm Optimization (MOPSO), as two common approaches, were compared with each other. Using pareto front, investors can choose optimal portfolio based on different risks and returns. Two objectives of the problem are return and risk of portfolio and CVaR is the risk metric. In order to solve the problem, three real-world constraints were considered. The results indicate that these approaches have a high performance in constraint portfolio optimization.https://jfr.ut.ac.ir/article_50715_585cb96acf8f5ee88526fdd187a14bd5.pdfoptimal portfolio predictionmulti-objective evolutionary algorithmsconditional value at risknsga-iimopso |
| spellingShingle | Mahsa Rajabi Hamid Khaloozadeh Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO تحقیقات مالی optimal portfolio prediction multi-objective evolutionary algorithms conditional value at risk nsga-ii mopso |
| title | Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO |
| title_full | Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO |
| title_fullStr | Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO |
| title_full_unstemmed | Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO |
| title_short | Optimal Portfolio Prediction in Tehran Stock Market using Multi-Objective Evolutionary Algorithms, NSGA-II and MOPSO |
| title_sort | optimal portfolio prediction in tehran stock market using multi objective evolutionary algorithms nsga ii and mopso |
| topic | optimal portfolio prediction multi-objective evolutionary algorithms conditional value at risk nsga-ii mopso |
| url | https://jfr.ut.ac.ir/article_50715_585cb96acf8f5ee88526fdd187a14bd5.pdf |
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