Advanced Search
MyIDEAS: Login

Return and Value at Risk using the Dirichlet Process

Contents:

Author Info

  • Mahmoud Zarepour
  • Thierry Bedard
  • Andre Dabrowski
Registered author(s):

    Abstract

    There exists a wide variety of models for return, and the chosen model determines the tool required to calculate the value at risk (VaR). This paper introduces an alternative methodology to model-based simulation by using a Monte Carlo simulation of the Dirichlet process. The model is constructed in a Bayesian framework, using properties initially described by Ferguson. A notable advantage of this model is that, on average, the random draws are sampled from a mixed distribution that consists of a prior guess by an expert and the empirical process based on a random sample of historical asset returns. The method is relatively automatic and similar to machine learning tools, e.g. the estimate is updated as new data arrive.

    Download Info

    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: http://www.tandfonline.com/doi/abs/10.1080/13504860701718448
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Mathematical Finance.

    Volume (Year): 15 (2008)
    Issue (Month): 3 ()
    Pages: 205-218

    as in new window
    Handle: RePEc:taf:apmtfi:v:15:y:2008:i:3:p:205-218

    Contact details of provider:
    Web page: http://www.tandfonline.com/RAMF20

    Order Information:
    Web: http://www.tandfonline.com/pricing/journal/RAMF20

    Related research

    Keywords: Dirichlet process; quantiles; Bayes estimates; value at risk;

    References

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Zarepour, Mahmoud & Labadi, Luai Al, 2012. "On a rapid simulation of the Dirichlet process," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 916-924.
    2. Han, Yufeng, 2012. "State uncertainty in stock markets: How big is the impact on the cost of equity?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2575-2592.

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:taf:apmtfi:v:15:y:2008:i:3:p:205-218. 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: (Michael McNulty).

    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.