IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

What Jump Process to use to Model S&P500 Returns?

Listed author(s):
  • Maria Semenova

    (University of Lausanne and FAME)

Registered author(s):

    This article estimates stochastic volatility jump-diffusion processes using the continuous empirical characteristic function method based on the Joint characteristic function and the Marginal characteristic function. The emphasis is on the specification of jumps in the asset log-price. Out of the models considered, stochastic volatility with normal jumps in the asset log-price fits the best the S&P500 index for the period from January 1980 to December 1999. Empirical characteristic unction estimation procedure based on the Marginal unconditional characteristic function is found to be more efficient when applied to the stochastic volatility models with jumps in the asset log-price. Joint unconditional characteristic function estimation is preferred in case of stochastic volatility model and stochastic volatility with jumps in both the asset log-prices and variance process.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: no

    Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 06-06.

    in new window

    Length: 42 pages
    Date of creation: Mar 2006
    Handle: RePEc:chf:rpseri:rp0606
    Contact details of provider: Web page:

    More information through EDIRC

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:chf:rpseri:rp0606. 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: (Marilyn Barja)

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.