IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v12y2012i9p1381-1394.html
   My bibliography  Save this article

Z -Transform and preconditioning techniques for option pricing

Author

Listed:
  • Gianluca Fusai
  • Daniele Marazzina
  • Marina Marena
  • Michael Ng

Abstract

In the present paper, we convert the usual n -step backward recursion that arises in option pricing into a set of independent integral equations by using a z -transform approach. In order to solve these equations, we consider different quadrature procedures that transform the integral equation into a linear system that we solve by iterative algorithms and we study the benefits of suitable preconditioning techniques. We show the relevance of our procedure in pricing options (such as plain vanilla, lookback, single and double barrier options) when the underlying evolves according to an exponential L�vy process.

Suggested Citation

  • Gianluca Fusai & Daniele Marazzina & Marina Marena & Michael Ng, 2012. "Z -Transform and preconditioning techniques for option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1381-1394, November.
  • Handle: RePEc:taf:quantf:v:12:y:2012:i:9:p:1381-1394
    DOI: 10.1080/14697688.2010.538074
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2010.538074
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/14697688.2010.538074?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. S. Corsaro & D. Marazzina & Z. Marino, 2015. "A parallel wavelet-based pricing procedure for Asian options," Quantitative Finance, Taylor & Francis Journals, vol. 15(1), pages 101-113, January.
    2. Fusai, Gianluca & Germano, Guido & Marazzina, Daniele, 2016. "Spitzer identity, Wiener-Hopf factorization and pricing of discretely monitored exotic options," European Journal of Operational Research, Elsevier, vol. 251(1), pages 124-134.
    3. Sesana, Debora & Marazzina, Daniele & Fusai, Gianluca, 2014. "Pricing exotic derivatives exploiting structure," European Journal of Operational Research, Elsevier, vol. 236(1), pages 369-381.

    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:quantf:v:12:y:2012:i:9:p:1381-1394. 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.