The Impact of Incorporating the Cost of Errors into Bankruptcy Prediction Models

Abstract : The current methodology to evaluate default and bankruptcy prediction models is to determine their precision - the percentage of firms predicted correctly. In this study we develop a framework for incorporating Type I (the amount lost from lending to a firm which goes bankrupt) and Type II (the opportunity cost of not lending to a firm which does not go bankrupt) error costs into the evaluation of prediction models. We then test this new framework by comparing the prediction model with a naive model of lending to all firms in the population based on the net profit each would generate. Our results indicate that prediction models can outperform naive models or other models only under certain conditions. This supports our hypothesis that the usefulness of prediction models cannot be fully assessed independently of the costs of forecast errors.
Type de document :
Rapport
2012
Liste complète des métadonnées

https://hal-hec.archives-ouvertes.fr/hal-00675309
Contributeur : Amaury Bouvet <>
Soumis le : mercredi 29 février 2012 - 17:56:04
Dernière modification le : jeudi 11 janvier 2018 - 06:19:31

Identifiants

  • HAL Id : hal-00675309, version 1

Collections

Citation

Vedran Capkun, L. A. Weiss. The Impact of Incorporating the Cost of Errors into Bankruptcy Prediction Models. 2012. 〈hal-00675309〉

Partager

Métriques

Consultations de la notice

235