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Measuring portfolio credit risk correctly: Why parameter uncertainty matters

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  • Tarashev, Nikola

Abstract

Why should risk management systems account for parameter uncertainty? In addressing this question, the paper lets an investor in a credit portfolio face non-diversifiable uncertainty about two risk parameters - probability of default and asset-return correlation - and calibrates this uncertainty to a lower bound on estimation noise. In this context, a Bayesian inference procedure is essential for deriving and analyzing the main result, i.e. that parameter uncertainty raises substantially the tail risk perceived by the investor. Since a measure of tail risk that incorporates parameter uncertainty is computationally demanding, the paper also derives a closed-form approximation to such a measure.

Suggested Citation

  • Tarashev, Nikola, 2010. "Measuring portfolio credit risk correctly: Why parameter uncertainty matters," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2065-2076, September.
  • Handle: RePEc:eee:jbfina:v:34:y:2010:i:9:p:2065-2076
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    References listed on IDEAS

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    1. Kerkhof, Jeroen & Melenberg, Bertrand & Schumacher, Hans, 2010. "Model risk and capital reserves," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 267-279, January.
    2. Bongaerts, Dion & Charlier, Erwin, 2009. "Private equity and regulatory capital," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1211-1220, July.
    3. Zhu, Haibin & Tarashev, Nikola A., 2008. "The pricing of correlated default risk: evidence from the credit derivatives market," Discussion Paper Series 2: Banking and Financial Studies 2008,09, Deutsche Bundesbank.
    4. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    5. Forte, Santiago & Peña, Juan Ignacio, 2009. "Credit spreads: An empirical analysis on the informational content of stocks, bonds, and CDS," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2013-2025, November.
    6. Hanson, Samuel & Schuermann, Til, 2006. "Confidence intervals for probabilities of default," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2281-2301, August.
    7. Liao, Hsien-Hsing & Chen, Tsung-Kang & Lu, Chia-Wu, 2009. "Bank credit risk and structural credit models: Agency and information asymmetry perspectives," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1520-1530, August.
    8. Lütkebohmert, Eva & Gordy, Michael B., 2007. "Granularity adjustment for Basel II," Discussion Paper Series 2: Banking and Financial Studies 2007,01, Deutsche Bundesbank.
    9. Borio, Claudio & Tsatsaronis, Kostas, 2004. "Accounting and prudential regulation: from uncomfortable bedfellows to perfect partners?," Journal of Financial Stability, Elsevier, vol. 1(1), pages 111-135, September.
    10. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    11. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
    12. Nikola Tarashev & Haibin Zhu, 2008. "Specification and Calibration Errors in Measures of Portfolio Credit Risk: The Case of the ASRF Model," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 129-173, June.
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    Cited by:

    1. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    2. Adonis Antoniades & Nikola Tarashev, 2014. "Securitisations: tranching concentrates uncertainty," BIS Quarterly Review, Bank for International Settlements, December.
    3. Aussenegg, Wolfgang & Resch, Florian & Winkler, Gerhard, 2011. "Pitfalls and remedies in testing the calibration quality of rating systems," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 698-708, March.
    4. Pflug, Georg Ch. & Pichler, Alois & Wozabal, David, 2012. "The 1/N investment strategy is optimal under high model ambiguity," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 410-417.
    5. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 403-417, February.
    6. Tirupam Goel & Ulf Lewrick & Agnė Nikola Tarashev, 2017. "Bank capital allocation under multiple constraints," BIS Working Papers 666, Bank for International Settlements.
    7. repec:eee:finana:v:53:y:2017:i:c:p:80-93 is not listed on IDEAS

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