IDEAS home Printed from https://ideas.repec.org/p/chf/rpseri/rp1634.html
   My bibliography  Save this paper

Linear Credit Risk Models

Author

Listed:
  • Damien Ackerer

    (Ecole Polytechnique Fédérale de Lausanne; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute)

  • Damir Filipović

    (Ecole Polytechnique Fédérale de Lausanne; Ecole Polytechnique Fédérale de Lausanne - Swiss Finance Institute)

Abstract

We introduce a novel class of credit risk models in which the drift of the survival process of a firm is a linear function of the factors. These models outperform the standard affine default intensity models in terms of analytical tractability. The prices of defaultable bonds and credit default swaps (CDS) are linear in the factors. The price of a CDS option can be uniformly approximated by polynomials in the factors. An empirical study illustrates the versatility of these models by fitting CDS spread time series.

Suggested Citation

  • Damien Ackerer & Damir Filipović, 2016. "Linear Credit Risk Models," Swiss Finance Institute Research Paper Series 16-34, Swiss Finance Institute, revised Jun 2016.
    • Handle: RePEc:chf:rpseri:rp1634
    as

    Download full text from publisher

    File URL: http://ssrn.com/abstract=2782455
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Damir Filipovi'c & Martin Larsson & Sergio Pulido, 2017. "Markov cubature rules for polynomial processes," Papers 1707.06849, arXiv.org, revised Jun 2019.

    More about this item

    Keywords

    Credit Default Swap; Credit Default Swap Option; Credit Risk; Credit Valuation Adjustment; Survival Process;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:chf:rpseri:rp1634. 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: Ridima Mittal (email available below). General contact details of provider: https://edirc.repec.org/data/fameech.html .

    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.