IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v202y2022icp59-78.html
   My bibliography  Save this article

Non-dominated sorting genetic algorithm-II for possibilistic mean-semiabsolute deviation-Yager entropy portfolio model with complex real-world constraints

Author

Listed:
  • Deng, Xue
  • Chen, Jiaxing
  • Wang, Xu
  • Geng, Fengting

Abstract

The purpose of our paper is to address the multi-objective portfolio model with complex real-world constraints under the assumption that the returns of risky assets are fuzzy variables. Firstly, a new possibilistic mean-semiabsolute deviation-Yager entropy portfolio model is proposed with transaction costs, cardinality and quantity constraints Secondly, to solve the proposed model efficiently, a non-dominated sorting genetic algorithm-II (NSGA-II) is presented, which can not only reduce the computational complexity but also enhance the solution accuracy. Then, a numerical example is provided to verify the feasibility and effectiveness of our proposed model and algorithm. Based on these results, we analyze the efficient frontiers with different quantity constraints and transaction costs, and illustrate the portfolio distributions with different transaction costs by using the boxplot figures. Finally, these solutions solved by NSGA-II and four traditional computation methods are compared. Our proposed algorithm outperforms the minimax method (Polakabb, 2010), two-stage method (Masson, 2016), extended two-stage method (Li, 2012) and compromise approach-based genetic algorithm (Li, 2013) in the efficient frontier, accuracy and number of solutions.

Suggested Citation

  • Deng, Xue & Chen, Jiaxing & Wang, Xu & Geng, Fengting, 2022. "Non-dominated sorting genetic algorithm-II for possibilistic mean-semiabsolute deviation-Yager entropy portfolio model with complex real-world constraints," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 59-78.
    • Handle: RePEc:eee:matcom:v:202:y:2022:i:c:p:59-78
    DOI: 10.1016/j.matcom.2022.05.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475422002099
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2022.05.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, Chang-Chun & Liu, Yi-Ting, 2008. "Genetic algorithms for portfolio selection problems with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 185(1), pages 393-404, February.
    2. Ehrgott, Matthias & Klamroth, Kathrin & Schwehm, Christian, 2004. "An MCDM approach to portfolio optimization," European Journal of Operational Research, Elsevier, vol. 155(3), pages 752-770, June.
    3. Chen, Wei & Zhang, Wei-Guo, 2010. "The admissible portfolio selection problem with transaction costs and an improved PSO algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2070-2076.
    4. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    5. Yue, Wei & Wang, Yuping, 2017. "A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 124-140.
    6. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    7. Anil Bera & Sung Park, 2008. "Optimal Portfolio Diversification Using the Maximum Entropy Principle," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 484-512.
    8. Grootveld, Henk & Hallerbach, Winfried, 1999. "Variance vs downside risk: Is there really that much difference?," European Journal of Operational Research, Elsevier, vol. 114(2), pages 304-319, April.
    9. Masson, Renaud & Lahrichi, Nadia & Rousseau, Louis-Martin, 2016. "A two-stage solution method for the annual dairy transportation problem," European Journal of Operational Research, Elsevier, vol. 251(1), pages 36-43.
    10. Tanaka, Hideo & Guo, Peijun, 1999. "Portfolio selection based on upper and lower exponential possibility distributions," European Journal of Operational Research, Elsevier, vol. 114(1), pages 115-126, April.
    11. Li, Yongjun & Chen, Yao & Liang, Liang & Xie, Jianhui, 2012. "DEA models for extended two-stage network structures," Omega, Elsevier, vol. 40(5), pages 611-618.
    12. Chen, Wei, 2015. "Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 125-139.
    13. Polak, George G. & Rogers, David F. & Sweeney, Dennis J., 2010. "Risk management strategies via minimax portfolio optimization," European Journal of Operational Research, Elsevier, vol. 207(1), pages 409-419, November.
    14. Wei Chen & Yiping Yang & Hui Ma, 2011. "Fuzzy Portfolio Selection Problem with Different Borrowing and Lending Rates," Mathematical Problems in Engineering, Hindawi, vol. 2011, pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Wei, 2015. "Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 125-139.
    2. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    3. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    4. Akhter Mohiuddin Rather & V. N. Sastry & Arun Agarwal, 2017. "Stock market prediction and Portfolio selection models: a survey," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 558-579, September.
    5. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    6. Jing-Rung Yu & Wan-Jiun Paul Chiou & Jian-Hong Yang, 2017. "Diversification benefits of risk portfolio models: a case of Taiwan’s stock market," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 467-502, February.
    7. Schuhmacher, Frank & Auer, Benjamin R., 2014. "Sufficient conditions under which SSD- and MR-efficient sets are identical," European Journal of Operational Research, Elsevier, vol. 239(3), pages 756-763.
    8. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 2001. "A fuzzy goal programming approach to portfolio selection," European Journal of Operational Research, Elsevier, vol. 133(2), pages 287-297, January.
    9. Huang, Xiaoxia & Ying, Haiyao, 2013. "Risk index based models for portfolio adjusting problem with returns subject to experts' evaluations," Economic Modelling, Elsevier, vol. 30(C), pages 61-66.
    10. Massol, Olivier & Banal-Estañol, Albert, 2014. "Export diversification through resource-based industrialization: The case of natural gas," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1067-1082.
    11. Buckley, Winston S. & Brown, Garfield O. & Marshall, Mario, 2012. "A mispricing model of stocks under asymmetric information," European Journal of Operational Research, Elsevier, vol. 221(3), pages 584-592.
    12. Wei Chen & Yun Wang & Mukesh Kumar Mehlawat, 2018. "A hybrid FA–SA algorithm for fuzzy portfolio selection with transaction costs," Annals of Operations Research, Springer, vol. 269(1), pages 129-147, October.
    13. Wei Chen & Yuxi Gai & Pankaj Gupta, 2018. "Efficiency evaluation of fuzzy portfolio in different risk measures via DEA," Annals of Operations Research, Springer, vol. 269(1), pages 103-127, October.
    14. Akhilesh KUMAR & Mohammad SHAHID, 2021. "Portfolio selection problem: Issues, challenges and future prospectus," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(629), W), pages 71-90, Winter.
    15. Guo, Sini & Yu, Lean & Li, Xiang & Kar, Samarjit, 2016. "Fuzzy multi-period portfolio selection with different investment horizons," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1026-1035.
    16. Chen, Wei & Zhang, Haoyu & Jia, Lifen, 2022. "A novel two-stage method for well-diversified portfolio construction based on stock return prediction using machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    17. Pankaj Gupta & Mukesh Mehlawat & Garima Mittal, 2012. "Asset portfolio optimization using support vector machines and real-coded genetic algorithm," Journal of Global Optimization, Springer, vol. 53(2), pages 297-315, June.
    18. Hirschberger, Markus & Qi, Yue & Steuer, Ralph E., 2010. "Large-scale MV efficient frontier computation via a procedure of parametric quadratic programming," European Journal of Operational Research, Elsevier, vol. 204(3), pages 581-588, August.
    19. Xidonas, Panagiotis & Mavrotas, George & Zopounidis, Constantin & Psarras, John, 2011. "IPSSIS: An integrated multicriteria decision support system for equity portfolio construction and selection," European Journal of Operational Research, Elsevier, vol. 210(2), pages 398-409, April.
    20. Hsin-Hung Chen & Hsien-Tang Tsai & Dennis Lin, 2011. "Optimal mean-variance portfolio selection using Cauchy-Schwarz maximization," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2795-2801.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:202:y:2022:i:c:p:59-78. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.