Computational Economics

, Volume 40, Issue 2, pp 115–129 | Cite as

Implied Severity Density Estimation: An Extended Semiparametric Method to Compute Credit Value at Risk

  • J. Samuel Baixauli
  • Susana Alvarez


This paper focuses on estimating implied severity, which does not rely on historical data and can be used especially for low default companies. We perform an extended semiparametric estimation method based on a mixture start to estimate it. We carry out an empirical analysis and our results show that our method allows us to capture the observed multimodal behaviour of severity better than the commonly used single beta distribution assumption. Futhermore, we highlight the relevance of this modeling approach by focusing on its role for credit VaR.


Credit default swaps Implied severity Semiparametric estimation 


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  1. Acharya V., Bharath S., Srinivasan A. (2007) Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries. Journal of Financial Economics 85(3): 787–821CrossRefGoogle Scholar
  2. Altman E., Brady B., Sinori A. (2005) The link between default and recovery rates: theory, empirical evidence and implications. Journal of Business 78: 2203–2228CrossRefGoogle Scholar
  3. Araten M., Jacobs M. Jr., Varshney P. (2004) Measuring LGD on commercial loans: an 18-year study. The RMA Journal 86(8): 28–35Google Scholar
  4. Arvanitis A., Browne C., Gregory J., Martin R. (1998) A credit risk toolbox. Risk 12: 50–55Google Scholar
  5. Asarnow E., Edwards D. (1995) Measuring loss on defaulted bank loans: A 24-year study. Journal of Commercial Lending 77: 11–23Google Scholar
  6. Chava, S., Stefanescu, C., & Turnbull, S. M. Modeling expected loss with unobservable heterogeneity. Working paper series 2006. SSRN Website.
  7. Chen S. (1999) Beta kernel estimators for density functions. Computational Statistics and Data Analysis 31: 131–145CrossRefGoogle Scholar
  8. Christensen, J. (2005). Joint estimation of default and recovery risk: A simulation study.
  9. Das S.R., Hanouna P. (2009) Implied recovery. Journal of Economics Dynamics & Control 33: 1837–1857CrossRefGoogle Scholar
  10. Duffie D., Singleton K. (1999) Modeling term structures of defaultable bonds. Review of Financial Studies 12: 687–720CrossRefGoogle Scholar
  11. Düllmann K., Sosinska A. (2007) Credit default swap as risk indicators of listed German banks. Financial Markets and Portfolio Management 21: 269–292CrossRefGoogle Scholar
  12. Finger, C., Finkelstein, V., Lardy, J. P., Pan, G., Ta, T., & Tierney, J. (2002). CreditGrades technical document, RiskMetrics Group. A technical discussion of the CreditGrades model for quantitative credit assesment.
  13. Gourieroux, C., & Monfort, A. (2006). (Non) consistency of the beta kernel estimator for recovery rate distribution. Série des Documents de Travail du CREST (Centre de Recherche en Economie et Statistique), 2006-31.Google Scholar
  14. Hagmann M., Renault O., Scaillet O. et al (2005) Estimation of recovery rate densities: Non-parametric and semi-parametric approaches versus industry practice. In: Altman E. (eds) Recovery Risk: The next challenger in credit risk management. Risk Books, London, pp 323–346Google Scholar
  15. Jarrow R. (2001) Default parameter estimation using market prices. Financial Analysts Journal 57(5): 75–92CrossRefGoogle Scholar
  16. Jarrow R., Lando D., Turnbull S. M. (1997) A Markov model for the term structure of credit risk spreads. Review of Financial Studies 10: 481–523CrossRefGoogle Scholar
  17. Lando D. (2004) Credit risk modeling: Theory and applications. Princeton University Press, Princeton, NJGoogle Scholar
  18. Madan D., Guntay L., Unal H. (2003) Pricing the risk of recovery in default with APR violation. Journal of Banking and Finance 27(6): 1001–1218CrossRefGoogle Scholar
  19. Merton R. C. (1974) On the pricing of corporate debt: the risk structure of interest rates. The Journal of Finance 27(6): 1001–1218Google Scholar
  20. Nelson C. R., Siegel A. F. (1987) Parsimonious modeling of yield curves. Journal of Business 60: 473–489CrossRefGoogle Scholar
  21. Pan J., Singleton K. (2008) Default and recovery implicit in the term structure of sovereign CDS spreads. Journal of Finance 63(5): 2345–2384CrossRefGoogle Scholar
  22. Renault O., Scaillet O. (2004) On the way to recovery: A nonparametric bias free estimation of recovery rate densities. Journal of Banking and Finance 28(12): 2915–2931CrossRefGoogle Scholar
  23. Seidler J., Jakubik P. (2009) Implied market loss given default in the Czech Republic. Structural-model approach. Czech Journal of Economic and Finance 59: 20–40Google Scholar
  24. Schuermann T. et al (2005) What do we know about loss given default?. In: Altman E. (eds) Recovery Risk: The next challenger in credit risk management. Risk Books, London, pp 3–24Google Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  1. 1.Department of Management and FinanceUniversity of MurciaMurciaSpain
  2. 2.Department of Quantitative Methods for the Economy and BusinessUniversity of MurciaMurciaSpain

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