IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v96y2024ipas1057521924004976.html
   My bibliography  Save this article

Dynamic portfolio optimization with the MARCOS approach under uncertainty

Author

Listed:
  • Yu, Pengrui
  • Ge, Zhipeng
  • Gong, Xiaomin
  • Cao, Xiao

Abstract

This paper introduces a dynamic portfolio selection approach that integrates the robustness of interval type-2 fuzzy sets (IT2FSs) with the flexibility of the MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method, offering a novel framework for asset evaluation amidst uncertainty. The IT2FSs enhance the adaptability of asset criteria representation, while the innovative application of MARCOS within the IT2FS environment refines the asset selection process. The weighted semi-absolute deviation metric is embraced to capture portfolio risk characteristic, which ingeniously harnesses the utility function values derived from the IT2F-MARCOS framework to delineate the anticipated return profile. On this basis, a dynamic bi-objective portfolio allocation model with realistic constraints and dynamic risk preference is formulated to rebalance portfolio periodically. Empirical evidence demonstrates the robustness and effectiveness of this approach compared to benchmark indexes, different allocation strategies, and the TOPSIS-based selection method, offering significant advancements in portfolio optimization for investors navigating uncertain markets. This study endeavors to contribute to the field of portfolio management, providing a thoughtful approach that enhances both theoretical understanding and practical application.

Suggested Citation

  • Yu, Pengrui & Ge, Zhipeng & Gong, Xiaomin & Cao, Xiao, 2024. "Dynamic portfolio optimization with the MARCOS approach under uncertainty," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    • Handle: RePEc:eee:finana:v:96:y:2024:i:pa:s1057521924004976
    DOI: 10.1016/j.irfa.2024.103565
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521924004976
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2024.103565?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. Jean-Philippe Bouchaud & Marc Potters & Jean-Pierre Aguilar, 1997. "Missing information and asset allocation," Science & Finance (CFM) working paper archive 500045, Science & Finance, Capital Fund Management.
    2. Lim, Sungmook & Oh, Kwang Wuk & Zhu, Joe, 2014. "Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market," European Journal of Operational Research, Elsevier, vol. 236(1), pages 361-368.
    3. Jin, Xiu & Chen, Na & Yuan, Ying, 2019. "Multi-period and tri-objective uncertain portfolio selection model: A behavioral approach," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 492-504.
    4. Jeng, Don Jyh-Fu & Huang, Kuo-Hsin, 2015. "Strategic project portfolio selection for national research institutes," Journal of Business Research, Elsevier, vol. 68(11), pages 2305-2311.
    5. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    6. Büyüközkan, Gülçin & Havle, Celal Alpay & Feyzioğlu, Orhan, 2021. "An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry," Journal of Air Transport Management, Elsevier, vol. 97(C).
    7. 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.
    8. Pätäri, Eero & Karell, Ville & Luukka, Pasi & Yeomans, Julian S, 2018. "Comparison of the multicriteria decision-making methods for equity portfolio selection: The U.S. evidence," European Journal of Operational Research, Elsevier, vol. 265(2), pages 655-672.
    9. Ying Fu & Kien Ng & Boray Huang & Huei Huang, 2015. "Portfolio optimization with transaction costs: a two-period mean-variance model," Annals of Operations Research, Springer, vol. 233(1), pages 135-156, October.
    10. Wu, Qun & Liu, Xinwang & Qin, Jindong & Zhou, Ligang & Mardani, Abbas & Deveci, Muhammet, 2022. "An integrated multi-criteria decision-making and multi-objective optimization model for socially responsible portfolio selection," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    11. Yang, Chih-Hao & Hsu, Wei & Wu, Yong-Lin, 2022. "A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    12. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    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. Zhang, Cheng & Gong, Xiaomin & Zhang, Jingshu & Chen, Zhiwei, 2023. "Dynamic portfolio allocation for financial markets: A perspective of competitive-cum-compensatory strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    2. Wu, Qun & Liu, Xinwang & Qin, Jindong & Zhou, Ligang & Mardani, Abbas & Deveci, Muhammet, 2022. "An integrated multi-criteria decision-making and multi-objective optimization model for socially responsible portfolio selection," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    3. Wang, Jianzhou & Lv, Mengzheng & Wang, Shuai & Gao, Jialu & Zhao, Yang & Wang, Qiangqiang, 2024. "Can multi-period auto-portfolio systems improve returns? Evidence from Chinese and U.S. stock markets," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    4. Juan F. Monge & Mercedes Landete & Jos'e L. Ruiz, 2016. "Sharpe portfolio using a cross-efficiency evaluation," Papers 1610.00937, arXiv.org, revised Oct 2016.
    5. Masoud Rahiminezhad Galankashi & Farimah Mokhatab Rafiei & Maryam Ghezelbash, 2020. "Portfolio selection: a fuzzy-ANP approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-34, December.
    6. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    7. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    8. Xidonas, Panos & Thomakos, Dimitris & Samitas, Aristeidis, 2025. "On the integration of multiple criteria decision aiding and forecasting: Does it create value in portfolio selection?," European Journal of Operational Research, Elsevier, vol. 321(2), pages 516-528.
    9. Liu, Yong-Jun & Yang, Guo-Sen & Zhang, Wei-Guo, 2024. "A novel regret-rejoice cross-efficiency approach for energy stock portfolio optimization," Omega, Elsevier, vol. 126(C).
    10. Jin, Xiu & Chen, Na & Yuan, Ying, 2019. "Multi-period and tri-objective uncertain portfolio selection model: A behavioral approach," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 492-504.
    11. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    12. 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.
    13. 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.
    14. 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.
    15. Animesh Debnath & Jagannath Roy & Samarjit Kar & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2017. "A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products," Sustainability, MDPI, vol. 9(8), pages 1-33, July.
    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. J. Francisco Rubio & Neal Maroney & M. Kabir Hassan, 2018. "Can Efficiency of Returns Be Considered as a Pricing Factor?," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 25-54, June.
    18. Lin Chen & Jin Peng & Bo Zhang & Isnaini Rosyida, 2017. "Diversified models for portfolio selection based on uncertain semivariance," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(3), pages 637-648, February.
    19. Cui, Tianxiang & Du, Nanjiang & Yang, Xiaoying & Ding, Shusheng, 2024. "Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    20. Kamali, Rezvan & Mahmoodi, Safieh & Jahandideh, Mohammad-Taghi, 2019. "Optimization of multi-period portfolio model after fitting best distribution," Finance Research Letters, Elsevier, vol. 30(C), pages 44-50.

    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:finana:v:96:y:2024:i:pa:s1057521924004976. 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.elsevier.com/locate/inca/620166 .

    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.