IDEAS home Printed from https://ideas.repec.org/a/wly/finmar/v18y2009i1p1-26.html
   My bibliography  Save this article

Credit Portfolio Loss Forecasts for Economic Downturns

Author

Listed:
  • Daniel Rösch
  • Harald Scheule

Abstract

Recent studies find a positive correlation between default and loss given default rates of credit portfolios. In response, financial regulators require financial institutions to base their capital on ‘Downturn’ loss rates given default which are also known as Downturn LGDs. This article proposes a concept for the Downturn LGD which incorporates econometric properties of credit risk as well as the information content of default and loss given default models. The concept is compared to an alternative proposal by the Department of the Treasury, the Federal Reserve System and the Federal Insurance Corporation. An empirical analysis is provided for US American corporate bond portfolios of different credit quality, seniority and security.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:finmar:v:18:y:2009:i:1:p:1-26
    DOI: 10.1111/j.1468-0416.2008.00145.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1468-0416.2008.00145.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1468-0416.2008.00145.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Laeven, Luc & Majnoni, Giovanni, 2003. "Loan loss provisioning and economic slowdowns: too much, too late?," Journal of Financial Intermediation, Elsevier, vol. 12(2), pages 178-197, April.
    2. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    3. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    4. Alfred Hamerle & Thilo Liebig & Harald Scheule, 2006. "Forecasting credit event frequency – empirical evidence for West German firms," Published Paper Series 2006-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    6. repec:uts:ppaper:2006:1 is not listed on IDEAS
    7. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2002. "Reliable estimation of generalized linear mixed models using adaptive quadrature," Stata Journal, StataCorp LP, vol. 2(1), pages 1-21, February.
    8. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    9. 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.
    10. repec:bla:jfinan:v:53:y:1998:i:4:p:1363-1387 is not listed on IDEAS
    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. Siemsen, Thomas & Vilsmeier, Johannes, 2018. "On a quest for robustness: About model risk, randomness and discretion in credit risk stress tests," Discussion Papers 31/2018, Deutsche Bundesbank.
    2. 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.
    3. Andrey Itkin & Fazlollah Soleymani, 2019. "Four-factor model of Quanto CDS with jumps-at-default and stochastic recovery," Papers 1912.08713, arXiv.org.
    4. 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.
    5. repec:czx:journl:v:21:y:2014:i:33:id:210 is not listed on IDEAS

    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. 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.
    2. 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.
    3. Bank for International Settlements, 2011. "Portfolio and risk management for central banks and sovereign wealth funds," BIS Papers, Bank for International Settlements, number 58.
    4. Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
    5. Daniel Rösch & Harald Scheule, 2014. "Forecasting Mortgage Securitization Risk Under Systematic Risk and Parameter Uncertainty," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 563-586, September.
    6. Daniel Rösch & Harald Scheule, 2011. "Securitization rating performance and agency incentives," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 287-314, Bank for International Settlements.
    7. 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.
    8. Daniel R÷Sch & Harald Scheule, 2010. "Downturn Credit Portfolio Risk, Regulatory Capital and Prudential Incentives-super-," International Review of Finance, International Review of Finance Ltd., vol. 10(Financial), pages 185-207.
    9. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    10. Benjamin Bade & Daniel Rösch & Harald Scheule, 2011. "Default and Recovery Risk Dependencies in a Simple Credit Risk Model," European Financial Management, European Financial Management Association, vol. 17(1), pages 120-144, January.
    11. M. B. Gordy & E. Lutkebohmert, 2013. "Granularity Adjustment for Regulatory Capital Assessment," International Journal of Central Banking, International Journal of Central Banking, vol. 9(3), pages 38-77, September.
    12. Dermine, J. & Neto de Carvalho, C., 2008. "Bank loan-loss provisioning, central bank rules vs. estimation: The case of Portugal," Journal of Financial Stability, Elsevier, vol. 4(1), pages 1-22, April.
    13. Gürtler, Marc & Heithecker, Dirk, 2005. "Systematic credit cycle risk of financial collaterals: Modelling and evidence," Working Papers FW15V2, Technische Universität Braunschweig, Institute of Finance.
    14. Stephen Zamore & Kwame Ohene Djan & Ilan Alon & Bersant Hobdari, 2018. "Credit Risk Research: Review and Agenda," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 811-835, March.
    15. Boudreault, Mathieu & Gauthier, Geneviève & Thomassin, Tommy, 2015. "Estimation of correlations in portfolio credit risk models based on noisy security prices," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 334-349.
    16. Krüger, Steffen & Rösch, Daniel & Scheule, Harald, 2018. "The impact of loan loss provisioning on bank capital requirements," Journal of Financial Stability, Elsevier, vol. 36(C), pages 114-129.
    17. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    18. Andrea Cipollini & Giuseppe Missaglia, 2008. "Measuring bank capital requirements through Dynamic Factor analysis," Center for Economic Research (RECent) 010, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    19. Siem Jan Koopman & André Lucas & Pieter Klaassen, 2002. "Pro-Cyclicality, Empirical Credit Cycles, and Capital Buffer Formation," Tinbergen Institute Discussion Papers 02-107/2, Tinbergen Institute.
    20. Hwang, Ruey-Ching & Chu, Chih-Kang & Yu, Kaizhi, 2020. "Predicting LGD distributions with mixed continuous and discrete ordinal outcomes," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1003-1022.

    More about this item

    Statistics

    Access and download statistics

    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:wly:finmar:v:18:y:2009:i:1:p:1-26. 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: Wiley Content Delivery (email available below). General contact details of provider: .

    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.