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Modeling the loss distribution / Sudheer Chava in Management science, Vol. 57 N° 7 (Juillet 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 7 (Juillet 2011) . - pp. 1267-1287 Titre : Modeling the loss distribution Type de document : texte imprimé Auteurs : Sudheer Chava, Auteur ; Catalina Stefanescu, Auteur ; Stuart Turnbull, Auteur Année de publication : 2011 Article en page(s) : pp. 1267-1287 Note générale : Management Langues : Anglais (eng) Mots-clés : Loss  distribution  Default  prediction  Recovery  rates  Basel  II Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : In this paper, we focus on modeling and predicting the loss distribution for credit risky assets such as bonds and loans. We model the probability of default and the recovery rate given default based on shared covariates. We develop a new class of default models that explicitly accounts for sector specific and regime dependent unobservable heterogeneity in firm characteristics. Based on the analysis of a large default and recovery data set over the horizon 1980–2008, we document that the specification of the default model has a major impact on the predicted loss distribution, whereas the specification of the recovery model is less important. In particular, we find evidence that industry factors and regime dynamics affect the performance of default models, implying that the appropriate choice of default models for loss prediction will depend on the credit cycle and on portfolio characteristics. Finally, we show that default probabilities and recovery rates predicted out of sample are negatively correlated and that the magnitude of the correlation varies with seniority class, industry, and credit cycle. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/7.toc [article] Modeling the loss distribution [texte imprimé] / Sudheer Chava, Auteur ; Catalina Stefanescu, Auteur ; Stuart Turnbull, Auteur . - 2011 . - pp. 1267-1287. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 7 (Juillet 2011) . - pp. 1267-1287 Mots-clés : Loss  distribution  Default  prediction  Recovery  rates  Basel  II Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : In this paper, we focus on modeling and predicting the loss distribution for credit risky assets such as bonds and loans. We model the probability of default and the recovery rate given default based on shared covariates. We develop a new class of default models that explicitly accounts for sector specific and regime dependent unobservable heterogeneity in firm characteristics. Based on the analysis of a large default and recovery data set over the horizon 1980–2008, we document that the specification of the default model has a major impact on the predicted loss distribution, whereas the specification of the recovery model is less important. In particular, we find evidence that industry factors and regime dynamics affect the performance of default models, implying that the appropriate choice of default models for loss prediction will depend on the credit cycle and on portfolio characteristics. Finally, we show that default probabilities and recovery rates predicted out of sample are negatively correlated and that the magnitude of the correlation varies with seniority class, industry, and credit cycle. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/7.toc