IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-540-33087-5_5.html
   My bibliography  Save this book chapter

Estimating Probabilities of Default for Low Default Portfolios

In: The Basel II Risk Parameters

Author

Listed:
  • Katja Pluto

    (Department of Deutsche Bundesbank)

  • Dirk Tasche

    (Department of Deutsche Bundesbank)

Abstract

For credit risk management purposes in general, and for allocation of regulatory capital by banks in particular (Basel II), numerical assessments of the credit-worthiness of borrowers are indispensable. These assessments are expressed in terms of probabilities of default (PD) that should incorporate a certain degree of conservatism in order to reflect the prudential risk management style banks are required to apply. In case of credit portfolios that did not at all suffer defaults, or very few defaults only over years, the resulting naive zero or close to zero estimates would clearly not involve such a sufficient conservatism. As an attempt to overcome this issue, we suggest the "most prudent estimation" principle. This means to estimate the PDs by upper confidence bounds while guaranteeing at the same time a PD ordering that respects the differences in credit quality indicated by the rating grades. The methodology is most easily applied under an assumption of independent default events but can be adapted to the case of correlated defaults.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • 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.
    • Handle: RePEc:spr:sprchp:978-3-540-33087-5_5
    DOI: 10.1007/3-540-33087-9_5
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Jafry, Yusuf & Schuermann, Til, 2004. "Measurement, estimation and comparison of credit migration matrices," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2603-2639, November.
    3. Samuel Hanson & Til Schuermann, 2004. "Estimating probabilities of default," Staff Reports 190, Federal Reserve Bank of New York.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. R Florez-Lopez, 2010. "Effects of missing data in credit risk scoring. A comparative analysis of methods to achieve robustness in the absence of sufficient data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 486-501, March.
    2. Yi-Ping Chang & Chih-Tun Yu, 2014. "Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk," Computational Statistics, Springer, vol. 29(1), pages 331-361, February.
    3. Jinyu Yang & Weiguo Zhang & Donglai Li, 2015. "Pricing Model for Financial Guaranty Products Using Actuarial Methodology and Most Prudent Principle," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(1), pages 101-110, January.
    4. J. Crook & T. Bellotti, 2012. "Asset correlations for credit card defaults," Applied Financial Economics, Taylor & Francis Journals, vol. 22(2), pages 87-95, January.
    5. 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.
    6. Tasche, Dirk, 2013. "Bayesian estimation of probabilities of default for low default portfolios," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 6(3), pages 302-326, July.
    7. Steffi Höse & Stefan Huschens, 2011. "Confidence Intervals for Asset Correlations in the Asymptotic Single Risk Factor Model," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 111-116, Springer.
    8. 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.
    9. Gourieroux, Christian & Tiomo, Andre, 2019. "The Evaluation of Model Risk for Probability of Default and Expected Loss," MPRA Paper 95795, University Library of Munich, Germany.
    10. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    11. P Beling & G Overstreet & K Rajaratnam, 2010. "Estimation error in regulatory capital requirements: theoretical implications for consumer bank profitability," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 381-392, March.
    12. Andrius Grigutis, 2023. "Probabilistic Overview of Probabilities of Default for Low Default Portfolios by K. Pluto and D. Tasche," Papers 2303.06148, arXiv.org.
    13. Chang Liu & Biqian Zhang & Xuefei Wang & Min Guo, 2022. "Account-level analytic hierarchical mixing modeling for credit risk of Chinese Government financing vehicle portfolios," Empirical Economics, Springer, vol. 62(6), pages 2771-2798, June.
    14. Gustavo F. Serenelli & Emiliano Delfau, 2023. "Estimation of Probabilities for Ordered Sets and Application to Calibration of Rating Models," CEMA Working Papers: Serie Documentos de Trabajo. 849, Universidad del CEMA.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M. Hashem Pesaran & Til Schuermann & Bjorn-Jakob Treutler, 2007. "Global Business Cycles and Credit Risk," NBER Chapters, in: The Risks of Financial Institutions, pages 419-469, National Bureau of Economic Research, Inc.
    2. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle," IJFS, MDPI, vol. 2(1), pages 1-22, March.
    3. Yi-Ping Chang & Chih-Tun Yu, 2014. "Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk," Computational Statistics, Springer, vol. 29(1), pages 331-361, February.
    4. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
    5. Hanson, Samuel G. & Pesaran, M. Hashem & Schuermann, Til, 2008. "Firm heterogeneity and credit risk diversification," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 583-612, September.
    6. Jankowitsch, Rainer & Nagler, Florian & Subrahmanyam, Marti G., 2014. "The determinants of recovery rates in the US corporate bond market," Journal of Financial Economics, Elsevier, vol. 114(1), pages 155-177.
    7. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    8. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    9. Varotto, Simone, 2012. "Stress testing credit risk: The Great Depression scenario," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3133-3149.
    10. Xin Huang & Hao Zhou & Haibin Zhu, 2012. "Systemic Risk Contributions," Journal of Financial Services Research, Springer;Western Finance Association, vol. 42(1), pages 55-83, October.
    11. Patrick Gagliardini & Christian Gouriéroux, 2011. "Approximate Derivative Pricing for Large Classes of Homogeneous Assets with Systematic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 237-280, Spring.
    12. María Hierro & Adolfo Maza, 2015. "From Discrete To Continuous-Time Transition Matrices In Intra-Distribution Dynamics Analysis: An Application To Per Capita Wealth In Europe," Bulletin of Economic Research, Wiley Blackwell, vol. 67(3), pages 227-235, July.
    13. Arturo Cortés Aguilar, 2011. "Estimación del residual de un bono respaldado por hipotecas mediante un modelo de riesgo crédito: una comparación de resultados de la teoría de cópulas y el modelo IRB de Basilea II en datos del merca," Revista de Administración, Finanzas y Economía (Journal of Management, Finance and Economics), Tecnológico de Monterrey, Campus Ciudad de México, vol. 5(1), pages 50-64.
    14. Wajeeh Mustafa Sarsour & Shamsul Rijal Muhammad Sabri, 2020. "A Simulation Study: Obtaining a Sufficient Sample Size of Discrete-Time Markov Chains of Investment in a Short Frequency of Time," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(8), pages 906-919, August.
    15. Mendicino, Caterina & Nikolov, Kalin & Ramirez, Juan-Rubio & Suarez, Javier & Supera, Dominik, 2020. "Twin defaults and bank capital requirements," Working Paper Series 2414, European Central Bank.
    16. Lionel Sopgoui, 2024. "Impact of Climate transition on Credit portfolio's loss with stochastic collateral," Papers 2408.13266, arXiv.org.
    17. Ildiko Orban & Oday Tamimi, 2020. "Accounting Model for Impairment under IFRS 9 and its Impact on Loss Allowance," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1259-1277.
    18. Paul Kupiec, 2007. "Financial stability and Basel II," Annals of Finance, Springer, vol. 3(1), pages 107-130, January.
    19. Jürgen Eichberger & Klaus Rheinberger & Martin Summer, 2014. "Credit risk in general equilibrium," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 57(2), pages 407-435, October.
    20. Georges Dionne & Geneviève Gauthier & Khemais Hammami & Mathieu Maurice & Jean‐Guy Simonato, 2010. "Default Risk in Corporate Yield Spreads," Financial Management, Financial Management Association International, vol. 39(2), pages 707-731, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-540-33087-5_5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.