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

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.
978-3-319-02966-5
978-3-319-02967-2
978-3-319-02966-5
978-3-319-02967-2
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2817276
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