Using financial and non-financial risk factors of a sample of more than 600 firms extracted from a financial institution database merged with “Centrale dei Rischi” database, we adopt generalized linear models in order to classify healthy and potentially insolvent firms in classes according with their default probability. One of the most relevant innovation of this paper is the introduction of a robust analysis for distress prediction methods using the forward search methodology (Atkinson and Riani, 2000). The main contribution of the forward search in the framework of rating system is the possibility to improve the classification rule avoiding the influence of outlying firms.
Credit risk management through robust generalized linear models
GROSSI, Luigi;
2006-01-01
Abstract
Using financial and non-financial risk factors of a sample of more than 600 firms extracted from a financial institution database merged with “Centrale dei Rischi” database, we adopt generalized linear models in order to classify healthy and potentially insolvent firms in classes according with their default probability. One of the most relevant innovation of this paper is the introduction of a robust analysis for distress prediction methods using the forward search methodology (Atkinson and Riani, 2000). The main contribution of the forward search in the framework of rating system is the possibility to improve the classification rule avoiding the influence of outlying firms.
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