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Modeling The Recovery Rate In A Reduced Form Model

Author

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  • Xin Guo
  • Robert A. Jarrow
  • Yan Zeng

Abstract

This paper provides a model for the recovery rate process in a reduced form model. After default, a firm continues to operate, and the recovery rate is determined by the value of the firm's assets relative to its liabilities. The debt recovers a different magnitude depending upon whether or not the firm enters insolvency and bankruptcy. Although this recovery rate process is similar to that used in a structural model, the reduced form approach is maintained by utilizing information reduction in the sense of Guo, Jarrow, and Zeng. Our model is able to provide analytic expressions for a firm's default intensity, bankruptcy intensity, and zero‐coupon bond prices both before and after default.

Suggested Citation

  • Xin Guo & Robert A. Jarrow & Yan Zeng, 2009. "Modeling The Recovery Rate In A Reduced Form Model," Mathematical Finance, Wiley Blackwell, vol. 19(1), pages 73-97, January.
  • Handle: RePEc:bla:mathfi:v:19:y:2009:i:1:p:73-97
    DOI: 10.1111/j.1467-9965.2008.00358.x
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    Citations

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    Cited by:

    1. Yuki Itoh, 2008. "Recovery Process Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(3), pages 307-347, December.
    2. Khieu, Hinh D. & Mullineaux, Donald J. & Yi, Ha-Chin, 2012. "The determinants of bank loan recovery rates," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 923-933.
    3. Xu, Ruxing, 2011. "A lattice approach for pricing convertible bond asset swaps with market risk and counterparty risk," Economic Modelling, Elsevier, vol. 28(5), pages 2143-2153, September.
    4. Kraft, Holger & Steffensen, Mogens, 2009. "Asset allocation with contagion and explicit bankruptcy procedures," Journal of Mathematical Economics, Elsevier, vol. 45(1-2), pages 147-167, January.
    5. Xin Guo & Robert Jarrow & Haizhi Lin, 2008. "Distressed debt prices and recovery rate estimation," Review of Derivatives Research, Springer, vol. 11(3), pages 171-204, October.
    6. Jose Giancarlo Gasha & Mr. Andre O Santos & Mr. Jorge A Chan-Lau & Mr. Carlos I. Medeiros & Mr. Marcos R Souto & Christian Capuano, 2009. "Recent Advances in Credit Risk Modeling," IMF Working Papers 2009/162, International Monetary Fund.
    7. Satoshi Yamashita & Toshinao Yoshiba, 2010. "Analytical Solution for Expected Loss of a Collateralized Loan: A Square-root Intensity Process Negatively Correlated with Collateral Value," IMES Discussion Paper Series 10-E-10, Institute for Monetary and Economic Studies, Bank of Japan.
    8. Xin Guo & Yan Zeng, 2008. "Intensity process and compensator: A new filtration expansion approach and the Jeulin--Yor theorem," Papers 0801.3191, arXiv.org.
    9. Cangemi, Robert R. & Mason, Joseph R. & Pagano, Michael S., 2012. "Options-based structural model estimation of bond recovery rates," Journal of Financial Intermediation, Elsevier, vol. 21(3), pages 473-506.
    10. Devjak Srečko, 2018. "Modeling of Cash Flows from Nonperforming Loans in a Commercial Bank," Naše gospodarstvo/Our economy, Sciendo, vol. 64(4), pages 3-9, December.
    11. Cosimo Munari & Stefan Weber & Lutz Wilhelmy, 2023. "Capital requirements and claims recovery: A new perspective on solvency regulation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(2), pages 329-380, June.
    12. Alain Monfort & Fulvio Pegoraro & Jean-Paul Renne & Guillaume Roussellet, 2021. "Affine Modeling of Credit Risk, Pricing of Credit Events, and Contagion," Management Science, INFORMS, vol. 67(6), pages 3674-3693, June.
    13. Ying Jiao & Idris Kharroubi, 2016. "Information uncertainty related to marked random times and optimal investment," Papers 1607.02743, arXiv.org, revised Mar 2017.

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