IDEAS home Printed from https://ideas.repec.org/p/bth/wpaper/2012-02.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.bot.or.th/Thai/EconomicConditions/Publication/DiscussionPaper/dp022012_eng.pdf
    Download Restriction: no
    ---><---

    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.
    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. 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.

    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. 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.
    2. Marcin Chlebus, 2014. "One-day prediction of state of turbulence for financial instrument based on models for binary dependent variable," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 37.
    3. Morone, Marco & Cornaglia, Anna, 2010. "An econometric model to quantify benchmark downturn LGD on residential mortgages," MPRA Paper 25588, University Library of Munich, Germany.
    4. François Coppens & Fernando Gonzáles & Gerhard Winkler, 2007. "The performance of credit rating systems in the assessment of collateral used in Eurosystem monetary policy operations," Working Paper Research 118, National Bank of Belgium.
    5. Mr. Jorge A Chan-Lau, 2006. "Fundamentals-Based Estimation of Default Probabilities - A Survey," IMF Working Papers 2006/149, International Monetary Fund.
    6. Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.
    7. 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.
    8. Patnaik, Ila & Mittal, Shalini & Pandey, Radhika, 2019. "Examining the trade-off between price and financial stability in India," Working Papers 19/248, National Institute of Public Finance and Policy.
    9. 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.
    10. Mark Joy & Marek Rusnák & Kateřina Šmídková & Bořek Vašíček, 2017. "Banking and Currency Crises: Differential Diagnostics for Developed Countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 44-67, January.
    11. Salim Lahmiri, 2016. "Features selection, data mining and finacial risk classification: a comparative study," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 265-275, October.
    12. Casu, Barbara & Clare, Andrew & Saleh, Nashwa, 2011. "Towards a new model for early warning signals for systemic financial fragility and near crises: an application to OECD countries," MPRA Paper 37043, University Library of Munich, Germany.
    13. Savona, Roberto, 2014. "Hedge fund systemic risk signals," European Journal of Operational Research, Elsevier, vol. 236(1), pages 282-291.
    14. Anand, Kartik & Gai, Prasanna & Kapadia, Sujit & Brennan, Simon & Willison, Matthew, 2013. "A network model of financial system resilience," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 219-235.
    15. 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.
    16. 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.
    17. Carmine Gabriele, 2019. "Learning from trees: A mixed approach to building early warning systems for systemic banking crises," Working Papers 40, European Stability Mechanism.
    18. R. John Irwin & Timothy C. Irwin, 2013. "Appraising Credit Ratings: Does The Cap Fit Better Than The Roc?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 396-408, October.
    19. 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.
    20. Dirk Tasche, 2012. "The art of probability-of-default curve calibration," Papers 1212.3716, arXiv.org, revised Nov 2013.

    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:bth:wpaper:2012-02. 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: Pornpinun Chantapacdepong (email available below). General contact details of provider: https://edirc.repec.org/data/botgvth.html .

    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.