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Estimating Implied Recovery Rates from the Term Structure of CDS Spreads

Author

Listed:
  • 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 reflect 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.

Suggested Citation

  • Marcin Jaskowski & Michael McAleer, 2012. "Estimating Implied Recovery Rates from the Term Structure of CDS Spreads," Documentos de Trabajo del ICAE 2012-28, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    • Handle: RePEc:ucm:doicae:1228
    Note: For financial 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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    References listed on IDEAS

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    1. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
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    Cited by:

    1. Pascal François, 2019. "The Determinants of Market-Implied Recovery Rates," Risks, MDPI, vol. 7(2), pages 1-15, May.
    2. Foroni, Claudia & Ravazzolo, Francesco & Sadaba, Barbara, 2018. "Assessing the predictive ability of sovereign default risk on exchange rate returns," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 242-264.
    3. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    4. Pascal François & Weiyu Jiang, 2019. "Credit Value Adjustment with Market-implied Recovery," Journal of Financial Services Research, Springer;Western Finance Association, vol. 56(2), pages 145-166, October.
    5. Anh Le, 2015. "Separating the Components of Default Risk: A Derivative-Based Approach," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-48.

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    More about this item

    Keywords

    Constant recovery; Stochastic recovery; Implied recovery rate; Term structure; CDS spreads.;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects

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