IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v24y2021i01ns0219024921500035.html
   My bibliography  Save this article

Time-Inconsistent Markovian Control Problems Under Model Uncertainty With Application To The Mean-Variance Portfolio Selection

Author

Listed:
  • TOMASZ R. BIELECKI

    (Department of Applied Mathematics, Illinois Institute of Technology, 10 W 32nd Street, Building RE, Room 220, Chicago, IL 60616, USA)

  • TAO CHEN

    (Department of Mathematics, University of Michigan, 530 Church Street, East Hall, Room 2859, Ann Arbor, MI 48109, USA)

  • IGOR CIALENCO

    (Department of Applied Mathematics, Illinois Institute of Technology, 10 W 32nd Street, Building RE, Room 220, Chicago, IL 60616, USA)

Abstract

In this paper, we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfect strategies with the adaptive robust stochastic control method to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results and by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

Suggested Citation

  • Tomasz R. Bielecki & Tao Chen & Igor Cialenco, 2021. "Time-Inconsistent Markovian Control Problems Under Model Uncertainty With Application To The Mean-Variance Portfolio Selection," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 24(01), pages 1-28, February.
    • Handle: RePEc:wsi:ijtafx:v:24:y:2021:i:01:n:s0219024921500035
    DOI: 10.1142/S0219024921500035
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024921500035
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219024921500035?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.

    Citations

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


    Cited by:

    1. Marcin Pitera & {L}ukasz Stettner, 2022. "Discrete-time risk sensitive portfolio optimization with proportional transaction costs," Papers 2201.02828, arXiv.org.

    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:wsi:ijtafx:v:24:y:2021:i:01:n:s0219024921500035. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijtaf/ijtaf.shtml .

    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.