IDEAS home Printed from
   My bibliography  Save this article

Calibration strategies of stochastic volatility models for option pricing


  • Mauri Larikka
  • Juho Kanniainen


This study examines how calibrated stochastic volatility models maintain their option pricing performance over subsequent days. Specifically, using a number of sets of single and multi-day data, different loss functions, and regularization techniques, we examine the dynamics of the pricing errors of two well-recognized stochastic volatility models. We find that, depending on the loss function, the use of multi-day data in calibration can slow down the increase in the pricing error for long-maturity options. On the other hand, the calibration with 1 day of data tends to give the smallest in-sample error diminishing the benefit of larger multi-day datasets. Differences between different sizes of datasets are more noticeable with the discrete-time volatility model than a continuous time one but in both cases 1 day of data would be the optimal choice and in most cases daily calibration is needed.

Suggested Citation

  • Mauri Larikka & Juho Kanniainen, 2012. "Calibration strategies of stochastic volatility models for option pricing," Applied Financial Economics, Taylor & Francis Journals, vol. 22(23), pages 1979-1992, January.
  • Handle: RePEc:taf:apfiec:v:22:y:2012:i:23:p:1979-1992
    DOI: 10.1080/09603107.2012.681026

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item


    Access and download statistics


    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:apfiec:v:22:y:2012:i:23:p:1979-1992. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.