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Estimating bank loans loss given default by generalized additive models

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Author Info

  • Raffaella Calabrese

    (University of Milano-Bicocca)

Abstract

With the implementation of the Basel II accord, the development of accurate loss given default models is becoming increasingly important. The main objective of this paper is to propose a new model to estimate Loss Given Default (LGD) for bank loans by applying generalized additive models. Our proposal allows to represent the high concentration of LGDs at the boundaries. The model is useful in uncovering nonlinear covariate effects and in estimating the mean and the variance of LGDs. The suggested model is applied to a comprehensive survey on loan recovery process of Italian banks. To model LGD in downturn conditions, we include macroeconomic variables in the model. Out-of-time validation shows that our model outperforms popular models like Tobit, decision tree and linear regression models for different time horizons.

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File URL: http://www.ucd.ie/geary/static/publications/workingpapers/gearywp201224.pdf
File Function: First version, 2012
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Bibliographic Info

Paper provided by Geary Institute, University College Dublin in its series Working Papers with number 201224.

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Length: 18 pages
Date of creation: 22 Oct 2012
Date of revision:
Handle: RePEc:ucd:wpaper:201224

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Related research

Keywords: downturn LGD; generalized additive model; Basel II;

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References

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  1. Joao A. Bastos, 2009. "Forecasting bank loans loss-given-default," CEMAPRE Working Papers 0901, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  2. 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.
  3. 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.
  4. Radovan Chalupka & Juraj Kopecsni, 2008. "Modelling Bank Loan LGD of Corporate and SME Segments: A Case Study," Working Papers IES 2008/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2008.
  5. 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.
  6. 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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