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The Role of Market-Implied Severity Modeling for Credit VaR

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  • J. Samuel Baixauli

    (Department of Management and Finance, University of Murcia)

  • Susana Alvarez

    (Department of Quantitative Methods for the Economy and Business, University of Murcia)

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    Abstract

    In this paper a beta-component mixture is proposed to model the market-implied severity. Recovery rates are extracted and identified from credit default swaps instead of using defaulted bonds instead using defaulted bonds because it allows us to identify recovery rates of low probability of default companies. An empirical analysis is carried out and the results show that a single beta distribution is rejected as a correct specification for implied severity while a beta-component mixture is accepted. Furthermore, the importance of this modeling approach is highlighted by focusing on its role for credit VaR.

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    Bibliographic Info

    Article provided by Society for AEF in its journal Annals of Economics and Finance.

    Volume (Year): 11 (2010)
    Issue (Month): 2 (November)
    Pages: 337-353

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    Handle: RePEc:cuf:journl:y:2010:v:11:i:2:p:337-353

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    Related research

    Keywords: Implied severity; Credit default swaps; Beta-component mixture; Credit VaR;

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    References

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    1. Das, Sanjiv R. & Hanouna, Paul, 2009. "Implied recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1837-1857, November.
    2. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    3. Jarrow, Robert A & Lando, David & Turnbull, Stuart M, 1997. "A Markov Model for the Term Structure of Credit Risk Spreads," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 481-523.
    4. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    5. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    6. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign "CDS" Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    7. Renault, Olivier & Scaillet, Olivier, 2004. "On the way to recovery: A nonparametric bias free estimation of recovery rate densities," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 2915-2931, December.
    8. Klaus Düllmann & Agnieszka Sosinska, 2007. "Credit default swap prices as risk indicators of listed German banks," Financial Markets and Portfolio Management, Springer, vol. 21(3), pages 269-292, September.
    9. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-89, October.
    10. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
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    Cited by:
    1. Yashkir, Olga & Yashkir, Yuriy, 2013. "Loss Given Default Modelling: Comparative Analysis," MPRA Paper 46147, University Library of Munich, Germany.

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