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Proposal of New Hybrid PD Estimation Models for the Low Default Portfolios (LDPs), Empirical Comparisons and Policy Implications

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  • Rungporn Roengpitya

    (Bank of Thailand)

Abstract

I proposed the new group of hybrid models to be used for the probability of default (PD) estimation on low default portfolios (LDPs). The construction of this hybrid model class was based upon the two existing estimation approaches–the most prudent estimation of Pluto and Tasche (2006) and Forrest (2005)’s maximum likelihood method. These new hybrid models possess the robust framework from the maximum likelihood concept but, unlike the original likelihood approach, the PD computation is much less intensive for rating models with many rating grades. Moreover, I found that the proposed hybrid models yield more conservative PDs than the existing LDP models, provided that the observed default rates satisfied specific conditions outlined in this paper. In addition to the theoretical construction of the models, this paper also gives the mathematical proofs of the necessary and sufficient conditions to ensure rank ordering of PD estimates from the hybrid models as well as the proofs of the conditions needed to guarantee the conservatism of the hybrid PDs when compared to other estimation method.

Suggested Citation

  • 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.
  • Handle: RePEc:bth:wpaper:2012-03
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    References listed on IDEAS

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    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. 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.
    Full references (including those not matched with items on IDEAS)

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