IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1302.0134.html
   My bibliography  Save this paper

Maximization of Non-Concave Utility Functions in Discrete-Time Financial Market Models

Author

Listed:
  • Laurence Carassus
  • Miklos Rasonyi

Abstract

This paper investigates the problem of maximizing expected terminal utility in a (generically incomplete) discrete-time financial market model with finite time horizon. In contrast to the standard setting, a possibly non-concave utility function $U$ is considered, with domain of definition $\mathbb{R}$. Simple conditions are presented which guarantee the existence of an optimal strategy for the problem. In particular, the asymptotic elasticity of $U$ plays a decisive role: existence can be shown when it is strictly greater at $-\infty$ than at $+\infty$.

Suggested Citation

  • Laurence Carassus & Miklos Rasonyi, 2013. "Maximization of Non-Concave Utility Functions in Discrete-Time Financial Market Models," Papers 1302.0134, arXiv.org, revised Sep 2014.
    • Handle: RePEc:arx:papers:1302.0134
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1302.0134
    File Function: Latest version
    Download Restriction: no
    ---><---

    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. repec:dau:papers:123456789/2317 is not listed on IDEAS
    3. Bernard, Carole & Ghossoub, Mario, 2009. "Static Portfolio Choice under Cumulative Prospect Theory," MPRA Paper 15446, University Library of Munich, Germany.
    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. Laurence Carassus & Mikl'os R'asonyi & Andrea M. Rodrigues, 2015. "Non-concave utility maximisation on the positive real axis in discrete time," Papers 1501.03123, arXiv.org, revised Apr 2015.
    2. Miklos Rasonyi, 2014. "Optimal investment with bounded above utilities in discrete time markets," Papers 1409.2023, arXiv.org.

    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. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    2. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    3. Jaroslava Hlouskova & Jana Mikocziova & Rudolf Sivak & Peter Tsigaris, 2014. "Capital Income Taxation and Risk-Taking under Prospect Theory: The Continuous Distribution Case," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 374-391, November.
    4. Yun Shi & Xiangyu Cui & Jing Yao & Duan Li, 2015. "Dynamic Trading with Reference Point Adaptation and Loss Aversion," Operations Research, INFORMS, vol. 63(4), pages 789-806, August.
    5. Laurence Carassus & Mikl'os R'asonyi & Andrea M. Rodrigues, 2015. "Non-concave utility maximisation on the positive real axis in discrete time," Papers 1501.03123, arXiv.org, revised Apr 2015.
    6. Jaroslava Hlouskova & Panagiotis Tsigaris, 2012. "Capital income taxation and risk taking under prospect theory," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(4), pages 554-573, August.
    7. De Giorgi, Enrico G. & Legg, Shane, 2012. "Dynamic portfolio choice and asset pricing with narrow framing and probability weighting," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 951-972.
    8. 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.
    9. Hou, Yanxi & Wang, Xing, 2019. "Nonparametric inference for distortion risk measures on tail regions," Insurance: Mathematics and Economics, Elsevier, vol. 89(C), pages 92-110.
    10. 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.
    11. Miklos Rasonyi & Andrea M. Rodrigues, 2012. "Optimal Portfolio Choice for a Behavioural Investor in Continuous-Time Markets," Papers 1202.0628, arXiv.org, revised Apr 2013.
    12. Alain Bensoussan & Abel Cadenillas & Hyeng Keun Koo, 2015. "Entrepreneurial Decisions on Effort and Project with a Nonconcave Objective Function," Mathematics of Operations Research, INFORMS, vol. 40(4), pages 902-914, October.
    13. Fortin, Ines & Hlouskova, Jaroslava & Tsigaris, Panagiotis, 2016. "The Consumption-Investment Decision of a Prospect Theory Household," Economics Series 322, Institute for Advanced Studies.
    14. Xue Dong He & Xun Yu Zhou, 2011. "Portfolio Choice Under Cumulative Prospect Theory: An Analytical Treatment," Management Science, INFORMS, vol. 57(2), pages 315-331, February.
    15. Miklos Rasonyi, 2014. "Optimal investment with bounded above utilities in discrete time markets," Papers 1409.2023, arXiv.org.
    16. Miklós Rásonyi & Andrea Rodrigues, 2013. "Optimal portfolio choice for a behavioural investor in continuous-time markets," Annals of Finance, Springer, vol. 9(2), pages 291-318, May.
    17. Laurence Carassus & Miklos Rasonyi, 2011. "On optimal investment for a behavioural investor in multiperiod incomplete market models," Papers 1107.1617, arXiv.org, revised Oct 2012.
    18. An Chen & Thai Nguyen & Thorsten Sehner, 2022. "Unit-Linked Tontine: Utility-Based Design, Pricing and Performance," Risks, MDPI, vol. 10(4), pages 1-27, April.
    19. Dong, Yinghui & Zheng, Harry, 2019. "Optimal investment of DC pension plan under short-selling constraints and portfolio insurance," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 47-59.
    20. Marcos Escobar-Anel & Michel Kschonnek & Rudi Zagst, 2022. "Portfolio optimization: not necessarily concave utility and constraints on wealth and allocation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(1), pages 101-140, February.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1302.0134. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.