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Challenges on the Validation of PD Models for Low Default Portfolios (LDPs) and Regulatory Policy Implications

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  • Rungporn Roengpitya

    (Bank of Thailand)

  • Pratabjai Nilla-or

    (Bank of Thailand)

Abstract

This paper is the first of its kind to compare the probability of default (PD) estimates for low default portfolios (LDPs) from various methods–notably Pluto and Tasche (2006), Van Der Burgt (2007), Benjamin, Cathcart and Ryan (2006) and Roengpitya (2012)–using the historical data of sovereign borrowers from the years 1975-2009. The comparison results give insightful information to bank supervisors and banks regarding the PD model validation and possible underestimation of PD values. We found that the most conservative approaches tend to be that of Pluto and Tasche (2006) and Roengpitya (2012) while Van Der Burgt (2007) seemed to yield the least conservative estimates. Moreover, for prudent supervisory purposes, we suggested that the accuracy ratio (AR) in the Van Der Burgt (2007) CAP curve method should be restricted to be between 40% and 80% to prevent a possible underestimation of credit risk. Finally, we presented the necessary and sufficient conditions to ensure that the rank ordering of PD estimates from Pluto and Tasche (2006)’s most prudent approach is satisfied.

Suggested Citation

  • Rungporn Roengpitya & Pratabjai Nilla-or, 2012. "Challenges on the Validation of PD Models for Low Default Portfolios (LDPs) and Regulatory Policy Implications," Working Papers 2012-02, Monetary Policy Group, Bank of Thailand.
    • Handle: RePEc:bth:wpaper:2012-02
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    References listed on IDEAS

    as
    1. Katja Pluto & Dirk Tasche, 2006. "Estimating Probabilities of Default for Low Default Portfolios," Springer Books, in: Bernd Engelmann & Robert Rauhmeier (ed.), The Basel II Risk Parameters, chapter 0, pages 79-103, Springer.
    2. Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
    3. George A. Papanastasopoulos, 2007. "Using option theory and fundamentals to assess the default risk of listed firms," International Journal of Accounting, Auditing and Performance Evaluation, Inderscience Enterprises Ltd, vol. 4(3), pages 305-331.
    4. Roberto Savona & Marika Vezzoli, 2012. "Multidimensional Distance‐To‐Collapse Point And Sovereign Default Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(4), pages 205-228, October.
    5. Samuel Hanson & Til Schuermann, 2004. "Estimating probabilities of default," Staff Reports 190, Federal Reserve Bank of New York.
    6. Georg von Pföstl & Markus Ricke, 2007. "Quantitative Validation of Rating Models for Low Default Portfolios through Benchmarking," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 14, pages 117-125.
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    Cited by:

    1. Rungporn Roengpitya, 2012. "Proposal of New Hybrid PD Estimation Models for the Low Default Portfolios (LDPs), Empirical Comparisons and Policy Implications," Working Papers 2012-03, Monetary Policy Group, Bank of Thailand.

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