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.
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- 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.
- 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, 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.
- 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.
- 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.
- Carlos González-Aguado & Max Bruche, 2006. "Recovery Rates, Default Probabilities and the Credit Cycle," FMG Discussion Papers dp572, Financial Markets Group.
- Max Bruche & Carlos González Aguado, 2006. "Recovery Rates, Default Probabilities And The Credit Cycle," Working Papers wp2006_0612, CEMFI.
- Altman, Edward I, 1989. " Measuring Corporate Bond Mortality and Performance," Journal of Finance, American Finance Association, vol. 44(4), pages 909-22, September.
- 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, vol. 34(1), pages 1-34, August.
- 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.
- 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.
- 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.
- Gourieroux Christian & Monfort Alain & Trognon A, 1981.
"Pseudo maximum likelihood methods : theory,"
CEPREMAP Working Papers (Couverture Orange)
- 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..
- 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.
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