Estimating bank loans loss given default by generalized additive models
AbstractWith 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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Bibliographic InfoPaper provided by Geary Institute, University College Dublin in its series Working Papers with number 201224.
Length: 18 pages
Date of creation: 22 Oct 2012
Date of revision:
downturn LGD; generalized additive model; Basel II;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-03 (All new papers)
- NEP-BAN-2012-11-03 (Banking)
- NEP-CBA-2012-11-03 (Central Banking)
- NEP-ECM-2012-11-03 (Econometrics)
- NEP-MAC-2012-11-03 (Macroeconomics)
- NEP-RMG-2012-11-03 (Risk Management)
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