IDEAS home Printed from https://ideas.repec.org/h/spr/lnechp/978-3-642-15609-0_5.html
   My bibliography  Save this book chapter

Normal Inverse Gaussian Factor Copula Model

In: Pricing and Risk Management of Synthetic CDOs

Author

Listed:
  • Anna Schlösser

    (Hedging and Derivatives Strategies)

Abstract

We have seen in the previous section, that a heavy tailed distribution of factors in the one factor copula model may help solving the correlation smile problem of the Gaussian copula model. Thus, finding a different heavy tailed distribution that is similar to the Student-t but stable under convolution would help to decrease the computation time tremendously. As computation time is an important issue for a large range of applications such as the determination of an optimal portfolio asset allocation (including CDO tranches), where CDO tranches have to be repriced in each scenario path at each time step in the future, the usage of such a distribution is crucial.

Suggested Citation

  • Anna Schlösser, 2011. "Normal Inverse Gaussian Factor Copula Model," Lecture Notes in Economics and Mathematical Systems, in: Pricing and Risk Management of Synthetic CDOs, chapter 0, pages 129-163, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-15609-0_5
    DOI: 10.1007/978-3-642-15609-0_5
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnechp:978-3-642-15609-0_5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.