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The optimal structure of PD buckets

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  • Krink, Thiemo
  • Paterlini, Sandra
  • Resti, Andrea

Abstract

In designing credit rating systems under the new Basel Accord, considerable effort has been devoted to rating assignment and quantification, while the choice of the optimal bucket structure has received less attention. To fill this gap, we propose two "bucketing" strategies based on constrained optimisation, paying attention to the implications of rating buckets for loan-pricing and adverse selection phenomena. We compare them with some more naïve approaches, based on a sample of about 100,000 European companies. We also analyse the persistence of our performance measures over time, as well as the effect of large exposures being associated with low-PD obligors.

Suggested Citation

  • Krink, Thiemo & Paterlini, Sandra & Resti, Andrea, 2008. "The optimal structure of PD buckets," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2275-2286, October.
  • Handle: RePEc:eee:jbfina:v:32:y:2008:i:10:p:2275-2286
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    References listed on IDEAS

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    7. Paterlini, Sandra & Krink, Thiemo, 2006. "Differential evolution and particle swarm optimisation in partitional clustering," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1220-1247, March.
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    Cited by:

    1. Marianna Lyra & Akwum Onwunta & Peter Winker, 2015. "Threshold accepting for credit risk assessment and validation," Journal of Banking Regulation, Palgrave Macmillan, vol. 16(2), pages 130-145, April.
    2. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    3. Thiemo Krink & Sandra Paterlini, 2011. "Multiobjective optimization using differential evolution for real-world portfolio optimization," Computational Management Science, Springer, vol. 8(1), pages 157-179, April.
    4. Lyra, M. & Paha, J. & Paterlini, S. & Winker, P., 2010. "Optimization heuristics for determining internal rating grading scales," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2693-2706, November.
    5. Nana Chai & Baofeng Shi & Bin Meng & Yizhe Dong, 2023. "Default Feature Selection in Credit Risk Modeling: Evidence From Chinese Small Enterprises," SAGE Open, , vol. 13(2), pages 21582440231, April.
    6. Arne Risa Hole & Hong Il Yoo, 2017. "The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 997-1013, November.
    7. Emilia ?I?AN & Adela Ioana TUDOR, 2011. "Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 2(1), pages 13-22, March.

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