IDEAS home Printed from
   My bibliography  Save this paper

A Markov Copula Model of Portfolio Credit Risk with Stochastic Intensities and Random Recoveries


  • Bielecki, T.R.

    (Illinois Institute of Technology)

  • Cousin, A.

    (Université de Lyon)

  • Crépey, S.

    (Université d’Évry Val d’Essonne)

  • Herbertsson, Alexander

    () (Department of Economics, School of Business, Economics and Law, Göteborg University)


In [4], the authors introduced a Markov copula model of portfolio credit risk. This model solves the top-down versus bottom-up puzzle in achieving efficient joint calibration to single-name CDS and to multi-name CDO tranches data. In [4], we studied a general model, that allows for stochastic default intensities and for random recoveries, and we conducted empirical study of our model using both deterministic and stochastic default intensities, as well as deterministic and random recoveries only. Since, in case of some “badly behaved” data sets a satisfactory calibration accuracy can only be achieved through the use of random recoveries, and, since for important applications, such as CVA computations for credit derivatives, the use of stochastic intensities is advocated by practitioners, efficient implementation of our model that would account for these two issues is very important. However, the details behind the implementation of the loss distribution in the case with random recoveries were not provided in [4]. Neither were the details on the stochastic default intensities given there. This paper is thus a complement to [4], with a focus on a detailed description of the methodology that we used so to implement these two model features: random recoveries and stochastic intensities.

Suggested Citation

  • Bielecki, T.R. & Cousin, A. & Crépey, S. & Herbertsson, Alexander, 2012. "A Markov Copula Model of Portfolio Credit Risk with Stochastic Intensities and Random Recoveries," Working Papers in Economics 545, University of Gothenburg, Department of Economics.
  • Handle: RePEc:hhs:gunwpe:0545
    Note: Contact information:

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Shanaka J Peiris & Magnus Saxegaard, 2007. "An Estimated DSGE Model for Monetary Policy Analysis in Low-Income Countries," IMF Working Papers 07/282, International Monetary Fund.
    2. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    3. Francis Vitek, 2009. "An Assessment of External Price Competitiveness for Mozambique," IMF Working Papers 09/165, International Monetary Fund.
    4. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    5. Mark R. Stone, 2003. "Inflation Targeting Lite," IMF Working Papers 03/12, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Portfolio Credit Risk; Markov Copula Model; Common Shocks; Stochastic Spreads; Random Recoveries;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:hhs:gunwpe:0545. 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: (Marie Andersson). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.