IDEAS home Printed from https://ideas.repec.org/a/wly/jnlaaa/v2014y2014i1n426036.html

The Optimal Portfolio Selection Model under g‐Expectation

Author

Listed:
  • Li Li

Abstract

This paper solves the optimal portfolio selection model under the framework of the prospect theory proposed by Kahneman and Tversky in the 1970s with decision rule replaced by the g‐expectation introduced by Peng. This model was established in the general continuous time setting and firstly adopted the g‐expectation to replace Choquet expectation adopted in the work of Jin and Zhou, 2008. Using different S‐shaped utility functions and g‐functions to represent the investors′ different uncertainty attitudes towards losses and gains makes the model not only more realistic but also more difficult to deal with. Although the models are mathematically complicated and sophisticated, the optimal solution turns out to be surprisingly simple, the payoff of a portfolio of two binary claims. Also I give the economic meaning of my model and the comparison with that one in the work of Jin and Zhou, 2008.

Suggested Citation

  • Li Li, 2014. "The Optimal Portfolio Selection Model under g‐Expectation," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:426036
    DOI: 10.1155/2014/426036
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2014/426036
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/426036?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
    ---><---

    References listed on IDEAS

    as
    1. Arjan B. Berkelaar & Roy Kouwenberg & Thierry Post, 2004. "Optimal Portfolio Choice under Loss Aversion," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 973-987, November.
    2. Hanqing Jin & Zuo Quan Xu & Xun Yu Zhou, 2008. "A Convex Stochastic Optimization Problem Arising From Portfolio Selection," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 171-183, January.
    3. Hanqing Jin & Xun Yu Zhou, 2008. "Behavioral Portfolio Selection In Continuous Time," Mathematical Finance, Wiley Blackwell, vol. 18(3), pages 385-426, July.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    6. Larry G. Epstein & Shaolin Ji, 2013. "Ambiguous Volatility and Asset Pricing in Continuous Time," The Review of Financial Studies, Society for Financial Studies, vol. 26(7), pages 1740-1786.
    7. N. El Karoui & S. Peng & M. C. Quenez, 1997. "Backward Stochastic Differential Equations in Finance," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 1-71, January.
    8. Harrison, J. Michael & Kreps, David M., 1979. "Martingales and arbitrage in multiperiod securities markets," Journal of Economic Theory, Elsevier, vol. 20(3), pages 381-408, June.
    9. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    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. Zongxia Liang & Yang Liu & Litian Zhang, 2021. "A Framework of State-dependent Utility Optimization with General Benchmarks," Papers 2101.06675, arXiv.org, revised Dec 2023.
    2. Jing Peng & Pengyu Wei & Zuo Quan Xu, 2022. "Relative growth rate optimization under behavioral criterion," Papers 2211.05402, arXiv.org.
    3. Servaas van Bilsen & Roger J. A. Laeven & Theo E. Nijman, 2020. "Consumption and Portfolio Choice Under Loss Aversion and Endogenous Updating of the Reference Level," Management Science, INFORMS, vol. 66(9), pages 3927-3955, September.
    4. Arindam Maity & Koushik Bera & N. Selvaraju, 2025. "Behavioral robust mean-variance portfolio selection with an intractable claim," Mathematics and Financial Economics, Springer, volume 19, number 5, June.
    5. Xun Li & Xiang Yu & Qinyi Zhang, 2021. "Optimal consumption with loss aversion and reference to past spending maximum," Papers 2108.02648, arXiv.org, revised Mar 2024.
    6. Curatola, Giuliano, 2016. "Optimal consumption and portfolio choice with loss aversion," SAFE Working Paper Series 130, Leibniz Institute for Financial Research SAFE.
    7. Laurence Carassus & Miklós Rásonyi, 2016. "Maximization of Nonconcave Utility Functions in Discrete-Time Financial Market Models," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 146-173, February.
    8. Fangyuan Zhang, 2023. "Non-concave portfolio optimization with average value-at-risk," Mathematics and Financial Economics, Springer, volume 17, number 3, June.
    9. van Bilsen, Servaas & Laeven, Roger J.A., 2020. "Dynamic consumption and portfolio choice under prospect theory," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 224-237.
    10. Hanqing Jin & Xun Yu Zhou, 2008. "Behavioral Portfolio Selection In Continuous Time," Mathematical Finance, Wiley Blackwell, vol. 18(3), pages 385-426, July.
    11. Song, Jingjing & Bi, Xiuchun & Li, Rong & Zhang, Shuguang, 2017. "Optimal consumption and portfolio selection problems under loss aversion with downside consumption constraints," Applied Mathematics and Computation, Elsevier, vol. 299(C), pages 80-94.
    12. Sigrid Källblad & Jan Obłój & Thaleia Zariphopoulou, 2018. "Dynamically consistent investment under model uncertainty: the robust forward criteria," Finance and Stochastics, Springer, vol. 22(4), pages 879-918, October.
    13. Chen, Zheng & Li, Zhongfei & Zeng, Yan & Shen, Yang, 2025. "Dynamic derivative-based pension investment with stochastic volatility: A behavioral perspective," Insurance: Mathematics and Economics, Elsevier, vol. 125(C).
    14. Guan, Guohui & Liang, Zongxia & Xia, Yi, 2023. "Optimal management of DC pension fund under the relative performance ratio and VaR constraint," European Journal of Operational Research, Elsevier, vol. 305(2), pages 868-886.
    15. Huy N. Chau & Mikl'os R'asonyi, 2016. "Skorohod's representation theorem and optimal strategies for markets with frictions," Papers 1606.07311, arXiv.org, revised Apr 2017.
    16. Vicky Henderson, 2012. "Prospect Theory, Liquidation, and the Disposition Effect," Management Science, INFORMS, vol. 58(2), pages 445-460, February.
    17. Marcos Escobar-Anel & Andreas Lichtenstern & Rudi Zagst, 2020. "Behavioral portfolio insurance strategies," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(4), pages 353-399, December.
    18. Moris S. Strub & Duan Li, 2020. "Failing to Foresee the Updating of the Reference Point Leads to Time-Inconsistent Investment," Operations Research, INFORMS, vol. 68(1), pages 199-213, January.
    19. Curatola, Giuliano, 2017. "Optimal portfolio choice with loss aversion over consumption," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 345-358.
    20. Bi, Xiuchun & Cui, Zhenyu & Fan, Jiacheng & Yuan, Lvning & Zhang, Shuguang, 2023. "Optimal investment problem under behavioral setting: A Lagrange duality perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).

    More about this item

    Statistics

    Access and download statistics

    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:wly:jnlaaa:v:2014:y:2014:i:1:n:426036. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/4058 .

    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.