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On Correlation and Default Clustering in Credit Markets

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  • Antje Berndt
  • Peter Ritchken
  • Zhiqiang Sun

Abstract

We establish Markovian models in the Heath, Jarrow, and Morton (1992) paradigm that permit an exponential affine representation of riskless and risky bond prices while offering significant flexibility in the choice of volatility structures. Estimating models in our family is typically no more difficult than in the workhorse affine family. Besides diffusive and jump-induced default correlations, defaults can impact the credit spreads of surviving firms, allowing for a greater clustering of defaults. Numerical implementations highlight the importance of incorporating interest rate--credit spread correlations, credit spread impact factors, and the full credit spread curve when building a unified framework for pricing credit derivatives. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

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  • Antje Berndt & Peter Ritchken & Zhiqiang Sun, 2010. "On Correlation and Default Clustering in Credit Markets," The Review of Financial Studies, Society for Financial Studies, vol. 23(7), pages 2680-2729, July.
  • Handle: RePEc:oup:rfinst:v:23:y:2010:i:7:p:2680-2729
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    Cited by:

    1. 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.
    2. Wolff, Christian & Bams, Dennis & Pisa, Magdalena, 2015. "Ripple effects from industry defaults," CEPR Discussion Papers 10891, C.E.P.R. Discussion Papers.
    3. Günter Franke, 2013. "Known Unknowns in Verbriefungen," Schmalenbach Journal of Business Research, Springer, vol. 65(67), pages 1-34, January.
    4. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    5. Wolff, Christian & Bams, Dennis & Pisa, Magdalena, 2015. "Credit risk characteristics of US small business portfolios," CEPR Discussion Papers 10889, C.E.P.R. Discussion Papers.
    6. Arismendi-Zambrano, Juan & Belitsky, Vladimir & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2022. "The implications of dependence, tail dependence, and bounds’ measures for counterparty credit risk pricing," Journal of Financial Stability, Elsevier, vol. 58(C).
    7. J. C. Arismendi-Zambrano & Vladimir Belitsky & Vinicius Amorim Sobreiro & Herbert Kimura, 2020. "The Implications of Tail Dependency Measures for Counterparty Credit Risk Pricing," Economics Department Working Paper Series n306-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    8. Bai, Jennie & Goldstein, Robert S. & Yang, Fan, 2020. "Is the credit spread puzzle a myth?," Journal of Financial Economics, Elsevier, vol. 137(2), pages 297-319.
    9. Samuel Chege Maina, 2011. "Credit Risk Modelling in Markovian HJM Term Structure Class of Models with Stochastic Volatility," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2011.
    10. Batten, Jonathan A. & Jacoby, Gady & Liao, Rose C., 2014. "Corporate yield spreads and real interest rates," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 89-100.
    11. Xiaolu Hu & Haoyi Luo & Zijin Xu & Jiang Li, 2021. "Intra‐industry spill‐over effect of default: Evidence from the Chinese bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4703-4740, September.
    12. Liu, Jinyu & Zhong, Rui, 2017. "Political uncertainty and a firm's credit risk: Evidence from the international CDS market," Journal of Financial Stability, Elsevier, vol. 30(C), pages 53-66.
    13. Jarrow, Robert A., 2011. "Credit market equilibrium theory and evidence: Revisiting the structural versus reduced form credit risk model debate," Finance Research Letters, Elsevier, vol. 8(1), pages 2-7, March.
    14. Samuel Chege Maina, 2011. "Credit Risk Modelling in Markovian HJM Term Structure Class of Models with Stochastic Volatility," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5, July-Dece.

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