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The Cross Section of Recovery Rates and Default Probabilities Implied by Credit Default Swap Spreads

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  • Elkamhi, Redouane
  • Jacobs, Kris
  • Pan, Xuhui

Abstract

Rather than assuming a fixed recovery rate in estimation, we estimate recovery rates from credit default swap spreads, using 3 years of daily data on 152 corporations. We use a quadratic pricing model, which ensures nonnegative default probabilities and recovery rates. The estimated cross section of recovery rates is plausible, with an average recovery rate of 54% and substantial cross-sectional variation. Estimated 5-year default probabilities are on average 67% higher than default probabilities obtained using the standard 40% recovery assumption. This finding critically impacts the valuation of structured credit products. Larger firms and firms with more tangible assets have higher recovery rates.

Suggested Citation

  • Elkamhi, Redouane & Jacobs, Kris & Pan, Xuhui, 2014. "The Cross Section of Recovery Rates and Default Probabilities Implied by Credit Default Swap Spreads," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(1), pages 193-220, February.
    • Handle: RePEc:cup:jfinqa:v:49:y:2014:i:01:p:193-220_00
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    Cited by:

    1. Jean‐François Bégin & Mathieu Boudreault & Mathieu Thériault, 2024. "Leveraging prices from credit and equity option markets for portfolio risk management," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 122-147, January.
    2. Murphy, Austin & Headley, Adrian, 2022. "An empirical evaluation of alternative fundamental models of credit spreads," International Review of Financial Analysis, Elsevier, vol. 81(C).
    3. Abudy, Menachem Meni & Raviv, Alon, 2016. "How much can illiquidity affect corporate debt yield spread?," Journal of Financial Stability, Elsevier, vol. 25(C), pages 58-69.
    4. Jansen, Jeroen & Das, Sanjiv R. & Fabozzi, Frank J., 2018. "Local volatility and the recovery rate of credit default swaps," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 1-29.
    5. Florent Kanga GBONGUE & Lambert N’Galadjo BAMBA, 2023. "Le modèle hybride de la structure par terme des primes souveraines de crédit et de liquidité dans la zone UEMOA," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 57, pages 101-145.
    6. Chernov, Mikhail & Augustin, Patrick & Song, Dongho, 2018. "Sovereign credit risk and exchange rates: Evidence from CDS quanto spreads," CEPR Discussion Papers 12857, C.E.P.R. Discussion Papers.
    7. Ferriani, Fabrizio & Gazzani, Andrea, 2023. "The impact of the war in Ukraine on energy prices: Consequences for firms’ financial performance," International Economics, Elsevier, vol. 174(C), pages 221-230.
    8. Chengzhu Sun & Shujing Wang & Chu Zhang, 2021. "Corporate Payout Policy and Credit Risk: Evidence from Credit Default Swap Markets," Management Science, INFORMS, vol. 67(9), pages 5755-5775, September.
    9. Mili, Medhi & Sahut, Jean-Michel & Teulon, Frédéric, 2018. "Modeling recovery rates of corporate defaulted bonds in developed and developing countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 28-44.
    10. Ye, Xiaoxia & Yu, Fan & Zhao, Ran, 2022. "Credit derivatives and corporate default prediction," Journal of Banking & Finance, Elsevier, vol. 138(C).
    11. Clark, Brian & Donato, James & Francis, Bill B & Shohfi, Thomas D, 2023. "Bank loan renegotiation and credit default swaps," Journal of Banking & Finance, Elsevier, vol. 151(C).
    12. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.

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