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Extending Multi-Period Pluto and Tasche PD Calibration Model Using Mode LRDF Approach

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DOI: 10.4236/jmf.2014.44026    3,995 Downloads   5,174 Views   Citations
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ABSTRACT

The intention of this paper is to propose extension to the Pluto and Tasche PD calibration model for low default portfolios that could produce more stable LRDF estimates and eliminate the necessity of quartile choice, while preserving adequate level of conservatism. Multi-period Pluto and Tasche model allows us to fulfill Basel committee requirements regarding long-term LRDF calibration even for portfolios with no observable defaults. The main drawback of that approach is a very strict requirement for the sample: only borrowers that are observable to the bank within each point on long-term horizon could be used as observations. Information regarding rating migrations, borrowers that arrived in the portfolio after sample cutoff date and borrowers that left the portfolio before the end of long-term calibration horizon should be excluded from the sample. Proposed Mode approach pairs Pluto and Tasche model with mode LRDF estimator (proposed by Canadian OSFI), as the results, it eliminates drawbacks of the original Pluto and Tasche model.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Surzhko, D. (2014) Extending Multi-Period Pluto and Tasche PD Calibration Model Using Mode LRDF Approach. Journal of Mathematical Finance, 4, 297-303. doi: 10.4236/jmf.2014.44026.

References

[1] Tasche, D. (2009) Estimating Discriminatory Power and PD Curves When the Number of Defaults Is Small. Working Paper
[2] Pluto, K. and Tasche, D. (2005) Thinking Positively. Risk, August, 72-78.
[3] Basel Committee on Banking Supervision (BCBS) (2004) Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework.
http://www.bis.org/publ/bcbs107.htm
[4] Vasicek, O.A. (1997) The Loan Loss Distribution. Technical Report, KMV Corporation, San Francisco.
[5] Bluhm, C., Overbeck, L. and Wagner, C. (2003) An Introduction to Credit Risk Modeling. Chapman & Hall/CRC, Boca Raton
[6] Office of the Superintendent of Financial Institutions (OSFI) of Canada (2004) Risk Quantification of IRB Systems at IRB Banks: Appendix—A Conservative Estimate of a Long-Term Average PD by a Hypothetical Bank. December 2004.
[7] Miu, P. and Ozdemir, B. (2008) Estimating and Validating Long-Run Probability of Default with Respect to Basel II Requirements. Journal of Risk Model Validation, 2, 1-39.

  
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