This paper provides a methodological analysis of credit risk in manufacturing firms. By using a representative sample of both healthy and bankrupted firms during the period 2003–2009 we provide an in-depth comparison of the standard discriminant approach for bankruptcy prediction based on a logistic regression model and a Robust Bayesian Approach. We conclude that the use of a robust GLM regression methodology enables us to provide a more accurate separation between sound and unsound firms thus suggesting that this methodological framework may be used to achieve a more reliable measure of firms credit worthiness.
Business Failure Prediction in Manufacturing: A Robust Bayesian Approach to Discriminant Scoring / Baussola, Maurizio; Bartoloni, Eleonora; Corbellini, Aldo. - STAMPA. - (2014), pp. 277-285. [10.1007/10104_2014_8]
Business Failure Prediction in Manufacturing: A Robust Bayesian Approach to Discriminant Scoring
BARTOLONI, ELEONORA;CORBELLINI, Aldo
2014-01-01
Abstract
This paper provides a methodological analysis of credit risk in manufacturing firms. By using a representative sample of both healthy and bankrupted firms during the period 2003–2009 we provide an in-depth comparison of the standard discriminant approach for bankruptcy prediction based on a logistic regression model and a Robust Bayesian Approach. We conclude that the use of a robust GLM regression methodology enables us to provide a more accurate separation between sound and unsound firms thus suggesting that this methodological framework may be used to achieve a more reliable measure of firms credit worthiness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.