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Estimating Implied Recovery Rates from the Term Structure of CDS Spreads

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Author Info

  • Marcin Jaskowski

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam.)

Abstract

Credit risk models should reect the observation that the relevant value of collateral is generally not the average value of the asset over all possible states of nature. In most cases, the relevant value of collateral for the lender is its secondary market value in bad states of nature, where marginal utilities are high. Although the negative correlation between recovery rates and default probabilities is well documented, the majority of pricing models does not allow for correlation between the two. In this paper, we propose a relatively parsimonious reduced-form continuous time model that estimates expected recovery rates and default probabilities from the term structure of CDS spreads. The parameters of the model and latent factors driving recovery risk and default risk are estimated using a Bayesian MCMC algorithm. We find that the Bayesian deviance information criterion (DIC) favors the model with stochastic recovery over constant recovery. We also observe that for companies with a good rating, implied constant recovery rates do not difier much from stochastic recovery. However, if a company is very risky, then forward stochastic recovery rates are significantly lower at longer maturities.

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Bibliographic Info

Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico in its series Documentos de Trabajo del ICAE with number 2012-28.

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Length: 31 pages
Date of creation: Dec 2012
Date of revision:
Handle: RePEc:ucm:doicae:1228

Note: For nancial support, the second author wishes to acknowledge the Australian Research Council, National Science Council, Taiwan, and the Japan Society for the Promotion of Science.
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Related research

Keywords: Constant recovery; stochastic recovery; implied recovery rate; term structure; CDS spreads.;

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References

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  1. Efraim Benmelech & Nittai K. Bergman, 2011. "Bankruptcy and the Collateral Channel," Journal of Finance, American Finance Association, vol. 66(2), pages 337-378, 04.
  2. Max Bruche & Carlos González Aguado, 2006. "Recovery Rates, Default Probabilities And The Credit Cycle," Working Papers wp2006_0612, CEMFI.
  3. John Y. Campbell & Stefano Giglio & Parag Pathak, 2009. "Forced Sales and House Prices," NBER Working Papers 14866, National Bureau of Economic Research, Inc.
  4. 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.
  5. Das, Sanjiv R. & Hanouna, Paul, 2009. "Implied recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1837-1857, November.
  6. 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.
  7. Schneider, Paul & Sögner, Leopold & Veža, Tanja, 2011. "The Economic Role of Jumps and Recovery Rates in the Market for Corporate Default Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(06), pages 1517-1547, January.
  8. Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "A Theory of the Term Structure of Interest Rates," Econometrica, Econometric Society, vol. 53(2), pages 385-407, March.
  9. 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.
  10. Duffie, Darrell, 2005. "Credit risk modeling with affine processes," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2751-2802, November.
  11. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
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