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

Modeling multivariate parametric densities of financial returns (in Russian)

Listed author(s):
  • Alexey Balaev

    (Higher School of Economics, Moscow, Russia)

Registered author(s):

    This paper compares several bivariate conditional density parameterizations for stock market returns in terms of in-sample fit and out-of-sample predictive ability for the whole conditional density. We consider Skew-Normal, Skew-Student, Skew-GED and Gram-Charlier densities. We focus on the ability of these density specifications to capture asymmetry and so called 'multivariate tails'. Using a test based on Kullback-Leibler information criterion we conduct pairwise comparisons of estimated conditional density models in sample and out of sample. The models are ranked according to their quality of fit and predictive ability. We discuss the causes behind superiority of this or that density specification.

    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

    Article provided by Quantile in its journal Quantile.

    Volume (Year): (2011)
    Issue (Month): 9 (July)
    Pages: 39-60

    in new window

    Handle: RePEc:qnt:quantl:y:2011:i:9:p:39-60
    Contact details of provider: Web page:

    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:qnt:quantl:y:2011:i:9:p:39-60. 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: (Stanislav Anatolyev)

    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.