Forecasting bank loans loss-given-default
With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametric fractional response regression and a nonparametric regression tree model to forecast bank loan credit losses. The out-of-sample predictive ability of these models is evaluated at several recovery horizons after the default event. The out-of-time predictive ability is also estimated for a recovery horizon of 1 year. The performance of the models is benchmarked against recovery estimates given by historical averages. The results suggest that regression trees are an interesting alternative to parametric models in modeling and forecasting loss-given-default.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Carlos González-Aguado & Max Bruche, 2006.
"Recovery Rates, Default Probabilities and the Credit Cycle,"
FMG Discussion Papers
dp572, Financial Markets Group.
- Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
- Max Bruche & Carlos González Aguado, 2006. "Recovery Rates, Default Probabilities And The Credit Cycle," Working Papers wp2006_0612, CEMFI.
- Max Bruche & Carlos Gonzalez-Aguado, 2006. "Recovery rates, default probabilities and the credit cycle," LSE Research Online Documents on Economics 24524, London School of Economics and Political Science, LSE Library.
- Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
- Bonfim, Diana, 2009.
"Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics,"
Journal of Banking & Finance,
Elsevier, vol. 33(2), pages 281-299, February.
- Diana Bonfim, 2006. "Credit Risk Drivers: Evaluating the Contribution of Firm Level Information and of Macroeconomic Dynamics," Economic Bulletin and Financial Stability Report Articles, Banco de Portugal, Economics and Research Department.
- Diana Bonfim, 2007. "Credit Risk Drivers: Evaluating the Contribution of Firm Level Information and of Macroeconomic Dynamics," Working Papers w200707, Banco de Portugal, Economics and Research Department.
- Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
- Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
- Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
- Leslie E. Papke & Jeffrey M. Wooldridge, 1993.
"Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates,"
NBER Technical Working Papers
0147, National Bureau of Economic Research, Inc.
- Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-32, Nov.-Dec..
- Qi, Min & Yang, Xiaolong, 2009. "Loss given default of high loan-to-value residential mortgages," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 788-799, May.
- Jankowitsch, Rainer & Pullirsch, Rainer & Veza, Tanja, 2008. "The delivery option in credit default swaps," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1269-1285, July.
- Gourieroux Christian & Monfort Alain & Trognon A, 1981.
"Pseudo maximum likelihood methods : theory,"
CEPREMAP Working Papers (Couverture Orange)
- Altman, Edward I, 1989. " Measuring Corporate Bond Mortality and Performance," Journal of Finance, American Finance Association, vol. 44(4), pages 909-22, September.
When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:34:y:2010:i:10:p:2510-2517. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.