IDEAS home Printed from https://ideas.repec.org/a/aza/rmfi00/y2011v4i4p392-412.html
   My bibliography  Save this article

The Crash-NIG copula model: Risk measurement and management of credit portfolios

Author

Listed:
  • Schlösser, Anna
  • Zagst, Rudi

Abstract

The one-factor copula models became very popular for modelling dependence in credit portfolios and collateralised debt obligation (CDO) valuation owing to their simplicity. Still, it is also well known that they are too simple for an exact pricing. Nevertheless, it is possible to extend the model in various ways so that it is possible to describe historical correlation behaviour realistically. Such an extension of the one-factor copula model, called the Crash-NIG copula model, is proposed by the authors with the following characteristics: (i) more tail dependence than in the Gaussian case, (ii) consistent term structure dimension, (iii) different rating buckets, relaxing the assumption of a large homogeneous portfolio, and (iv) different correlation regimes. Here the authors demonstrate how to apply this model for generating rating transition and default scenarios of a credit portfolio together with the other relevant risk factors. Repricing of instruments on the simulated scenario paths, that is the most difficult problem for such complex instruments as CDO tranches, can also be done efficiently fast using the same model. Finally, portfolio optimisation can be performed on the derived profit and loss distributions that are shown to be very different from normal.

Suggested Citation

  • Schlösser, Anna & Zagst, Rudi, 2011. "The Crash-NIG copula model: Risk measurement and management of credit portfolios," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 4(4), pages 392-412, September.
  • Handle: RePEc:aza:rmfi00:y:2011:v:4:i:4:p:392-412
    as

    Download full text from publisher

    File URL: https://hstalks.com/article/5049/download/
    Download Restriction: Requires a paid subscription for full access.

    File URL: https://hstalks.com/article/5049/
    Download Restriction: Requires a paid subscription for full access.
    ---><---

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

    More about this item

    Keywords

    economic scenario generation; CDO; copula; factor model; correlation; default probability; portfolio loss; regime-switching; Hidden Markov Model; portfolio optimisation; mean variance; CVaR;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

    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:aza:rmfi00:y:2011:v:4:i:4:p:392-412. 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: Henry Stewart Talks (email available below). General contact details of provider: .

    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.