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.
Original language | English |
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Title of host publication | Advances in Latent Variables |
Editors | Maurizio, Eugenio Brentari, and E. M. Qannari. Carpita |
Pages | 277-285 |
Number of pages | 9 |
DOIs | |
Publication status | Published - 2015 |
Keywords
- Bankruptcy
- Discriminant analysis
- Forward search
- Robust GLM regression