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Default correlation: an analytical result

Author

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  • Chunsheng Zhou
Abstract
Evaluating default correlations and the probabilities of multiple defaults is an important task in credit analysis and risk management, but it has never been an easy one because default correlations cannot be measured directly. This paper provides, for the first time, an analytical formula for calculating default correlations based on a first-passage-time model that can be easily implemented and conveniently used in a variety of financial applications. This paper also provides a theoretical justification for many empirical results found in the literature and increases our understanding of the important features of default correlations.

Suggested Citation

  • Chunsheng Zhou, 1997. "Default correlation: an analytical result," Finance and Economics Discussion Series 1997-27, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:1997-27
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    Citations

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    Cited by:

    1. Xin Gao & Binlin Wu & Tobias Schäfer, 2017. "Introducing an analytical solution and an improved one-factor gaussian copula model for the pricing of heterogeneous CDOs," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(02n03), pages 1-17, June.
    2. Carey, Mark & Hrycay, Mark, 2001. "Parameterizing credit risk models with rating data," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 197-270, January.
    3. Lucas, Andre & Klaassen, Pieter & Spreij, Peter & Straetmans, Stefan, 2001. "An analytic approach to credit risk of large corporate bond and loan portfolios," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1635-1664, September.
    4. Carey, Mark, 2002. "A guide to choosing absolute bank capital requirements," Journal of Banking & Finance, Elsevier, vol. 26(5), pages 929-951, May.
    5. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    6. Jones, David & Mingo, John, 1999. "Credit risk modeling and internal capital allocation processes: implications for a models-based regulatory bank capital standard," Journal of Economics and Business, Elsevier, vol. 51(2), pages 79-108, March.
    7. Dermine, Jean & Lajeri, Fatma, 2001. "Credit risk and the deposit insurance premium: a note," Journal of Economics and Business, Elsevier, vol. 53(5), pages 497-508.
    8. Bandyopadhyay, Arindam, 2010. "Understanding the Effect of Concentration Risk in the Banks’ Credit Portfolio: Indian Cases," MPRA Paper 24822, University Library of Munich, Germany.
    9. Mark Carey, 2001. "Dimensions of Credit Risk and Their Relationship to Economic Capital Requirements," NBER Chapters, in: Prudential Supervision: What Works and What Doesn't, pages 197-232, National Bureau of Economic Research, Inc.
    10. Richa Verma Bajaj, 2018. "Credit Risk Capital Estimation Under IRB Approach for Banks in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 475-500, June.
    11. Palombini, Edgardo, 2009. "Factor models and the credit risk of a loan portfolio," MPRA Paper 20107, University Library of Munich, Germany.
    12. Cowan, Adrian M. & Cowan, Charles D., 2004. "Default correlation: An empirical investigation of a subprime lender," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 753-771, April.
    13. Qian, Qian & Yang, Yang & Gu, Jing & Feng, Hairong, 2019. "Information authenticity, spreading willingness and credit risk contagion – A dual-layer network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Dariusz Gatarek & Juliusz Jabłecki, 2013. "A model for dependent defaults and pricing contingent claims with counterparty risk," NBP Working Papers 150, Narodowy Bank Polski.

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    Keywords

    Credit; Debt; Risk;
    All these keywords.

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