IDEAS home Printed from https://ideas.repec.org/a/taf/apmtfi/v23y2016i2p158-173.html
   My bibliography  Save this article

On the Method of Optimal Portfolio Choice by Cost-Efficiency

Author

Listed:
  • Ludger Rüschendorf
  • Viktor Wolf

Abstract

We develop the method of optimal portfolio choice based on the concept of cost-efficiency in two directions. First, instead of specifying a payoff distribution in an unique way, we allow customer-defined constraints and preferences for the choice of a distributional form of the payoff distribution. This leads to a class of possible payoff distributions. We determine upper and lower bounds for the corresponding strategies in stochastic order and describe related upper and lower price bounds for the induced class of cost-efficient payoffs. While the results for the cost-efficient payoff given so far in the literature in the context of Lévy models are based on the Esscher pricing measure we use as alternative the method of empirical pricing measures. This method is well established in the literature and leads to more precise pricing of options and their cost-efficient counterparts. We show in some examples for real market data that this choice is numerically feasible and leads to more precise prices for the cost-efficient payoffs and for values of the efficiency loss.

Suggested Citation

  • Ludger Rüschendorf & Viktor Wolf, 2016. "On the Method of Optimal Portfolio Choice by Cost-Efficiency," Applied Mathematical Finance, Taylor & Francis Journals, vol. 23(2), pages 158-173, March.
    • Handle: RePEc:taf:apmtfi:v:23:y:2016:i:2:p:158-173
    DOI: 10.1080/1350486X.2016.1204238
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1350486X.2016.1204238
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1350486X.2016.1204238?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. Carole Bernard & Gero Junike & Thibaut Lux & Steven Vanduffel, 2024. "Cost-efficient payoffs under model ambiguity," Finance and Stochastics, Springer, vol. 28(4), pages 965-997, October.

    More about this item

    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:taf:apmtfi:v:23:y:2016:i:2:p:158-173. 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/RAMF20 .

    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.