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The single risk factor approach to capital charges in case of correlated loss given default rates

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  • Dirk Tasche

Abstract

A new methodology for incorporating LGD correlation effects into the Basel II risk weight functions is introduced. This methodology is based on modelling of LGD and default event with a single loss variable. The resulting formulas for capital charges are numerically compared to the current proposals by the Basel Committee on Banking Supervision. Keywords: Regulatory capital charge, loss given default (LGD).

Suggested Citation

  • Dirk Tasche, 2004. "The single risk factor approach to capital charges in case of correlated loss given default rates," Papers cond-mat/0402390, arXiv.org, revised Feb 2004.
    • Handle: RePEc:arx:papers:cond-mat/0402390
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    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.
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    Cited by:

    1. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 71986, University Library of Munich, Germany, revised 30 Apr 2013.
    2. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
    3. Xiao, Tim, 2018. "Incremental Risk Charge Methodology," FrenXiv 6b3hu, Center for Open Science.
    4. Gürtler, Marc & Heithecker, Dirk, 2005. "Systematic credit cycle risk of financial collaterals: Modelling and evidence," Working Papers FW15V2, Technische Universität Braunschweig, Institute of Finance.
    5. António Santos, 2020. "The relation between PD and LGD: an application to a corporate loan portfolio," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    6. Daniel Rösch & Harald Scheule, 2009. "Credit Portfolio Loss Forecasts for Economic Downturns," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 18(1), pages 1-26, February.
    7. Thomas Hartmann-Wendels & Christopher Paulus Imanto, 2023. "Is the regulatory downturn LGD adequate? Performance analysis and alternative methods," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(3), pages 736-747, March.
    8. Aneta Ptak-Chmielewska & Paweł Kopciuszewski, 2024. "Credit loss modelling using beta distribution in a Bayesian approach," Bank i Kredyt, Narodowy Bank Polski, vol. 55(3), pages 313-332.
    9. Franco Varetto, 2017. "La correlazione tra PD ed LGD nell’analisi del rischio di credito/The correlation between probability of default and loss given default in the credit risk analysis," IRCrES Working Paper 201714, CNR-IRCrES Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY - former Institute for Economic Research on Firms and Growth - Torino (TO) ITALY.
    10. repec:ptu:bdpart:r202009 is not listed on IDEAS
    11. Rösch, Daniel & Scheule, Harald, 2009. "The Empirical Relation between Credit Quality, Recovery and Correlation," Hannover Economic Papers (HEP) dp-418, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    12. Kim, Joocheol & Kim, KiHyung, 2006. "Loss Given Default Modelling under the Asymptotic Single Risk Factor Assumption," MPRA Paper 860, University Library of Munich, Germany.
    13. Li, Hui, 2010. "Downturn LGD: A Spot Recovery Approach," MPRA Paper 20010, University Library of Munich, Germany.
    14. Weißbach, Rafael & von Lieres und Wilkau, Carsten, 2006. "On partial defaults in portfolio credit risk: Comparing economic and regulatory view," Technical Reports 2006,02, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    15. Annalisa Di Clemente, 2020. "Modeling Portfolio Credit Risk Taking into Account the Default Correlations Using a Copula Approach: Implementation to an Italian Loan Portfolio," JRFM, MDPI, vol. 13(6), pages 1-24, June.
    16. Richard J Martin, 2011. "A CDS Option Miscellany," Papers 1201.0111, arXiv.org, revised May 2019.
    17. Janette Larney & Gerrit Lodewicus Grobler & James Samuel Allison, 2022. "Introducing Two Parsimonious Standard Power Mixture Models for Bimodal Proportional Data with Application to Loss Given Default," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    18. Annalisa Di Clemente, 2013. "Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2013(109), pages 5-24.
    19. Daniel Rosch & Harald Scheule, 2008. "Credit Losses in Economic Downturns - Empirical Evidence for Hong Kong Mortgage Loans," Working Papers 152008, Hong Kong Institute for Monetary Research.
    20. Jiri Witzany, 2013. "Estimating Default and Recovery Rate Correlations," Working Papers IES 2013/03, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2013.
    21. Aneta Ptak-Chmielewska & Paweł Kopciuszewski, 2023. "Application of the Bayesian approach in loss given default modelling," Bank i Kredyt, Narodowy Bank Polski, vol. 54(6), pages 625-650.
    22. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.
    23. Wei, Li & Yuan, Zhongyi, 2016. "The loss given default of a low-default portfolio with weak contagion," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 113-123.
    24. Rafael Weißbach & Carsten Lieres und Wilkau, 2010. "Economic capital for nonperforming loans," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(1), pages 67-85, March.
    25. repec:czx:journl:v:21:y:2014:i:33:id:210 is not listed on IDEAS

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