IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v218y2012i2p484-492.html
   My bibliography  Save this article

An expected regret minimization portfolio selection model

Author

Listed:
  • Li, Xiang
  • Shou, Biying
  • Qin, Zhongfeng

Abstract

Fuzzy portfolio selection has been widely studied within the framework of the credibility theory. However, all existing models provide only concentrated investment solutions, which contradicts the risk diversification concept in the classical portfolio selection theory. In this paper, we propose an expected regret minimization model, which minimizes the expected value of the distance between the maximum return and the obtained return associated with each portfolio. We prove that our model is advantageous for obtaining distributive investment and reducing investor regret. The effectiveness of the model is demonstrated by using an example of a portfolio selection problem comprising ten securities in the Shanghai Stock Exchange 180 Index.

Suggested Citation

  • Li, Xiang & Shou, Biying & Qin, Zhongfeng, 2012. "An expected regret minimization portfolio selection model," European Journal of Operational Research, Elsevier, vol. 218(2), pages 484-492.
  • Handle: RePEc:eee:ejores:v:218:y:2012:i:2:p:484-492
    DOI: 10.1016/j.ejor.2011.11.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171101006X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2011.11.015?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. Li Chen & Simai He & Shuzhong Zhang, 2011. "Tight Bounds for Some Risk Measures, with Applications to Robust Portfolio Selection," Operations Research, INFORMS, vol. 59(4), pages 847-865, August.
    2. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, vol. 92(368), pages 805-824, December.
    3. Yu, Mei & Takahashi, Satoru & Inoue, Hiroshi & Wang, Shouyang, 2010. "Dynamic portfolio optimization with risk control for absolute deviation model," European Journal of Operational Research, Elsevier, vol. 201(2), pages 349-364, March.
    4. Huang, Dashan & Zhu, Shushang & Fabozzi, Frank J. & Fukushima, Masao, 2010. "Portfolio selection under distributional uncertainty: A relative robust CVaR approach," European Journal of Operational Research, Elsevier, vol. 203(1), pages 185-194, May.
    5. Khwazbeen Saida Fatah & Peng Shi & Jamal R.M. Ameen & Ron Wiltshire, 2010. "Risk averse preference models for normalised lotteries based on simulation," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 8(2), pages 189-207.
    6. Zhang, Wei-Guo & Zhang, Xi-Li & Xiao, Wei-Lin, 2009. "Portfolio selection under possibilistic mean-variance utility and a SMO algorithm," European Journal of Operational Research, Elsevier, vol. 197(2), pages 693-700, September.
    7. David E. Bell, 1982. "Regret in Decision Making under Uncertainty," Operations Research, INFORMS, vol. 30(5), pages 961-981, October.
    8. Khwazbeen S. Fatah & Peng Shi & Jamal R.M. Ameen & Ronald J. Wiltshire, 2009. "A preference ranking model based on both mean-variance analysis and cumulative distribution function using simulation," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 5(3), pages 311-327.
    9. Gregory, Christine & Darby-Dowman, Ken & Mitra, Gautam, 2011. "Robust optimization and portfolio selection: The cost of robustness," European Journal of Operational Research, Elsevier, vol. 212(2), pages 417-428, July.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Cheng, Dong & Yuan, Yuxiang & Wu, Yong & Hao, Tiantian & Cheng, Faxin, 2022. "Maximum satisfaction consensus with budget constraints considering individual tolerance and compromise limit behaviors," European Journal of Operational Research, Elsevier, vol. 297(1), pages 221-238.
    3. Tsaur, Ruey-Chyn, 2013. "Fuzzy portfolio model with different investor risk attitudes," European Journal of Operational Research, Elsevier, vol. 227(2), pages 385-390.
    4. Kuen-Suan Chen & Ruey-Chyn Tsaur & Nei-Chih Lin, 2022. "Dimensions Analysis to Excess Investment in Fuzzy Portfolio Model from the Threshold of Guaranteed Return Rates," Mathematics, MDPI, vol. 11(1), pages 1-13, December.
    5. 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.
    6. Xingyu Yang & Jin’an He & Hong Lin & Yong Zhang, 2020. "Boosting Exponential Gradient Strategy for Online Portfolio Selection: An Aggregating Experts’ Advice Method," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 231-251, January.
    7. Benati, S. & Conde, E., 2022. "A relative robust approach on expected returns with bounded CVaR for portfolio selection," European Journal of Operational Research, Elsevier, vol. 296(1), pages 332-352.
    8. Yong-Jun Liu & Wei-Guo Zhang & Jun-Bo Wang, 2016. "Multi-period cardinality constrained portfolio selection models with interval coefficients," Annals of Operations Research, Springer, vol. 244(2), pages 545-569, September.
    9. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    10. Lioui, Abraham & Poncet, Patrice, 2013. "Optimal benchmarking for active portfolio managers," European Journal of Operational Research, Elsevier, vol. 226(2), pages 268-276.

    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. Andrea C. Hupman & Jay Simon, 2023. "The Legacy of Peter Fishburn: Foundational Work and Lasting Impact," Decision Analysis, INFORMS, vol. 20(1), pages 1-15, March.
    2. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    3. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    4. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    5. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    6. Georgia Perakis & Guillaume Roels, 2008. "Regret in the Newsvendor Model with Partial Information," Operations Research, INFORMS, vol. 56(1), pages 188-203, February.
    7. Jinyi Hu, 2023. "Linguistic Multiple-Attribute Decision Making Based on Regret Theory and Minimax-DEA," Mathematics, MDPI, vol. 11(20), pages 1-14, October.
    8. Martín Egozcue & Xu Guo & Wing-Keung Wong, 2015. "Optimal output for the regret-averse competitive firm under price uncertainty," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 5(2), pages 279-295, December.
    9. Jhunjhunwala, Tanushree, 2021. "Searching to avoid regret: An experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 298-319.
    10. van Dijk, Wilco W. & van der Pligt, Joop, 1997. "The Impact of Probability and Magnitude of Outcome on Disappointment and Elation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 69(3), pages 277-284, March.
    11. 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.
    12. Enrico G. De Giorgi & Thierry Post, 2011. "Loss Aversion with a State-Dependent Reference Point," Management Science, INFORMS, vol. 57(6), pages 1094-1110, June.
    13. van Dijk, W.W. & Zeelenberg, M. & van der Pligt, J., 1999. "Not having what you want versus having what you don't want : The impact of the type of negative outcome on the experience of disappointment and related emotions," Other publications TiSEM 5d1661b1-db82-4773-8ac4-5, Tilburg University, School of Economics and Management.
    14. Olivier Chanel & Graciela Chichilnisky, 2009. "The influence of fear in decisions: Experimental evidence," Journal of Risk and Uncertainty, Springer, vol. 39(3), pages 271-298, December.
    15. Soora Rasouli & Harry Timmermans, 2017. "Specification of regret-based models of choice behaviour: formal analyses and experimental design based evidence," Transportation, Springer, vol. 44(6), pages 1555-1576, November.
    16. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.
    17. Raquel M. Gaspar & Paulo M. Silva, 2023. "Investors’ perspective on portfolio insurance," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 22(1), pages 49-79, January.
    18. Yuval Rottenstreich & Alex Markle & Johannes Müller-Trede, 2023. "Risky Sure Things," Management Science, INFORMS, vol. 69(8), pages 4707-4720, August.
    19. Ulrich Schmidt & Stefan Traub, 2009. "An Experimental Investigation of the Disparity Between WTA and WTP for Lotteries," Theory and Decision, Springer, vol. 66(3), pages 229-262, March.
    20. Herweg, Fabian, 2013. "The expectation-based loss-averse newsvendor," Economics Letters, Elsevier, vol. 120(3), pages 429-432.

    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:ejores:v:218:y:2012:i:2:p:484-492. 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/eor .

    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.