IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v338y2004i1p292-295.html
   My bibliography  Save this article

A variance reduction technique for American option pricing

Author

Listed:
  • Moreni, Nicola

Abstract

In this paper we are interested in Monte Carlo pricing of American options via the Longstaff–Schwartz algorithm. In particular, we show that it is possible to obtain a variance reduction technique based on importance sampling by means of Girsanov theorem. The almost sure convergence of the modified algorithm and a central limit theorem were proved. Here, we summarise the theoretical results and some numerical outcomes.

Suggested Citation

  • Moreni, Nicola, 2004. "A variance reduction technique for American option pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 292-295.
    • Handle: RePEc:eee:phsmap:v:338:y:2004:i:1:p:292-295
    DOI: 10.1016/j.physa.2004.02.055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843710400250X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2004.02.055?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. Francois-Michel Boire & R. Mark Reesor & Lars Stentoft, 2021. "American Option Pricing with Importance Sampling and Shifted Regressions," JRFM, MDPI, vol. 14(8), pages 1-21, July.

    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:eee:phsmap:v:338:y:2004:i:1:p:292-295. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.