Estimating bank loans loss given default by generalized additive models

Raffaella Calabrese ()

No 201224, Working Papers from Geary Institute, University College Dublin

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.

Keywords: downturn LGD; generalized additive model; Basel II (search for similar items in EconPapers)
Pages: 18 pages
Date: 2012-10-22
New Economics Papers: this item is included in nep-ban, nep-cba, nep-ecm, nep-mac and nep-rmg
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Citations: View citations in EconPapers (3)

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