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Bivariate Semi-Markov Process for Counterparty Credit Risk

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  • Guglielmo D'Amico
  • Raimondo Manca
  • Giovanni Salvi
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    Abstract

    We consider the problem of constructing an appropriate multivariate model for the study of the counterparty credit risk in credit rating migration problem. For this financial problem different multivariate Markov chain models were proposed. However the markovian assumption may be inappropriate for the study of the dynamic of credit ratings which typically show non markovian like behaviour. In this paper we develop a semi-Markov approach to the study of the counterparty credit risk by defining a new multivariate semi-Markov chain model. Methods are given for computing the transition probabilities, reliability functions and the price of a risky Credit Default Swap.

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    File URL: http://arxiv.org/pdf/1112.0226
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1112.0226.

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    Date of creation: Dec 2011
    Date of revision: Oct 2012
    Handle: RePEc:arx:papers:1112.0226

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    Web page: http://arxiv.org/

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    1. Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2007. "Valuing credit default swap in a non-homogeneous semi-Markovian rating based model," Computational Economics, Society for Computational Economics, vol. 29(2), pages 119-138, March.
    2. Guglielmo D'Amico & Jacques Janssen & Raimondo Manca, 2011. "A Non-Homogeneous Semi-Markov Reward Model For The Credit Spread Computation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(02), pages 221-238.
    3. Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2011. "Discrete Time Non-Homogeneous Semi-Markov Reliability Transition Credit Risk Models and the Default Distribution Functions," Computational Economics, Society for Computational Economics, vol. 38(4), pages 465-481, November.
    4. Damiano Brigo & Agostino Capponi, 2008. "Bilateral counterparty risk valuation with stochastic dynamical models and application to Credit Default Swaps," Papers 0812.3705, arXiv.org, revised Nov 2009.
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