IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v8y2008i3p299-312.html
   My bibliography  Save this article

Dynamic hedging of single and multi-dimensional options with transaction costs: a generalized utility maximization approach

Author

Listed:
  • Peter Meindl
  • James Primbs

Abstract

We propose a new methodology for discrete time dynamic hedging with transaction costs that has three key performance features. First, the methodology can accommodate the use of a wide range of objective functions, from the use of many types of utility functions to the more traditional objectives of hedging error minimization. Second, our methodology can significantly outperform traditional dynamic hedging methodologies across a range of objective functions. Third, our methodology can be applied to both single and multi-dimensional options while analytical methods typically can only be applied to single dimensional options.

Suggested Citation

  • Peter Meindl & James Primbs, 2008. "Dynamic hedging of single and multi-dimensional options with transaction costs: a generalized utility maximization approach," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 299-312.
    • Handle: RePEc:taf:quantf:v:8:y:2008:i:3:p:299-312
    DOI: 10.1080/14697680701381210
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/14697680701381210
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697680701381210?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. Yuji Yamada & James A. Primbs, 2018. "Model Predictive Control for Optimal Pairs Trading Portfolio with Gross Exposure and Transaction Cost Constraints," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(1), pages 1-21, March.
    2. James Primbs & Chang Sung, 2008. "A Stochastic Receding Horizon Control Approach to Constrained Index Tracking," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(1), pages 3-24, March.
    3. Peter Nystrup & Stephen Boyd & Erik Lindström & Henrik Madsen, 2019. "Multi-period portfolio selection with drawdown control," Annals of Operations Research, Springer, vol. 282(1), pages 245-271, November.

    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:taf:quantf:v:8:y:2008:i:3:p:299-312. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.