IDEAS home Printed from https://ideas.repec.org/a/cuf/journl/y2001v2i2p445-465.html
   My bibliography  Save this article

Martingale Measure Method for Expected Utility Maximization in Discrete-Time Incomplete Markets

Author

Listed:
  • Ping Li

    (Institute of Systems Science, Academy of Mathematics and Systems Science, The Chinese Academy of Sciences)

  • Jianming Xia

    (Institute of Applied Mathematics, Academy of Mathematics and Systems Science, The Chinese Academy of Sciences)

  • Jia-an Yan

    (Institute of Applied Mathematics, Academy of Mathematics and Systems Science, The Chinese Academy of Sciences)

Abstract

In this paper we study the expected utility maximization problem for discretetime incomplete financial markets. As shown by Xia and Yan (2000a, 2000b) in the continuous-time case, this problem can be solved by the martingale measure method. In a special discrete-time model, we explicitly work out the optimal trading strategies and the associated minimum relative entropy martingale measures and minimum Hellinger-Kakutani distance martingale measures.

Suggested Citation

  • Ping Li & Jianming Xia & Jia-an Yan, 2001. "Martingale Measure Method for Expected Utility Maximization in Discrete-Time Incomplete Markets," Annals of Economics and Finance, Society for AEF, vol. 2(2), pages 445-465, November.
    • Handle: RePEc:cuf:journl:y:2001:v:2:i:2:p:445-465
    as

    Download full text from publisher

    File URL: http://www.aeconf.net/Articles/Nov2001/aef020209.pdf
    Download Restriction: no
    File URL: http://down.aefweb.net/AefArticles/aef020209.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2015. "On the exact solution of the multi-period portfolio choice problem for an exponential utility under return predictability," European Journal of Operational Research, Elsevier, vol. 246(2), pages 528-542.
    2. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.

    More about this item

    Keywords

    Martingale measure; Incomplete market; Utility maximization; Optimal trading strategy; Relative entropy; Hellinger-Kakutani distance;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:cuf:journl:y:2001:v:2:i:2:p:445-465. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Qiang Gao (email available below). General contact details of provider: https://edirc.repec.org/data/emcufcn.html .

    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.