IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v61y2005i2p219-237.html
   My bibliography  Save this article

Optimal consumption and investment problems under GARCH with transaction costs

Author

Listed:
  • Zhiping Chen
  • K. C. Yuen

Abstract

General multiperiod optimal consumption and investment problems with proportional transaction costs are investigated in this paper, a GARCH-type process is used to model the risky asset’s return series so that its time-varying moments and conditional heteroskedasticity can be properly described. We model this kind of consumption and investment problems as dynamic stochastic optimization problems, which can easily cope with different utility functions and any number of time periods. The procedure to efficiently solve the resulting nonlinear stochastic optimization problem is discussed in detail and a parallelizable decomposition algorithm is devised. Numerical results show the suitability and promise of our methodology. Copyright Springer-Verlag 2005

Suggested Citation

  • Zhiping Chen & K. C. Yuen, 2005. "Optimal consumption and investment problems under GARCH with transaction costs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 61(2), pages 219-237, June.
  • Handle: RePEc:spr:mathme:v:61:y:2005:i:2:p:219-237
    DOI: 10.1007/s001860400396
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s001860400396
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s001860400396?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. Lee, Zu-Hsu & Deng, Shiming & Lin, Beixin & Yang, James G.S., 2010. "Decision model and analysis for investment interest expense deduction and allocation," European Journal of Operational Research, Elsevier, vol. 200(1), pages 268-280, January.
    2. Davari-Ardakani, Hamed & Aminnayeri, Majid & Seifi, Abbas, 2014. "A study on modeling the dynamics of statistically dependent returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 35-51.

    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:spr:mathme:v:61:y:2005:i:2:p:219-237. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.