Quotation Hirk, Rainer, Vana, Laura, Pichler, Stefan, Hornik, Kurt. 2021. A Joint Model of Failures and Credit Ratings. IAQF & Thalesians Seminar Series, Zoom, United States/USA, 08.03-08.03. Invited Talk


RIS


BibTeX

Abstract

We propose a novel framework for credit risk modeling, where default or failure information together with rating or expert information are jointly incorporated in the model. These sources of information are modeled as response variables in a multivariate ordinal regression model estimated by a composite likelihood procedure. The proposed framework provides probabilities of default conditional on the rating information observed at the beginning of a predetermined period and is able to account for missing failure or credit rating information. Our approach is the first that consistently combines failure prediction models, where default indicators are used as responses, with so called “shadow rating models”, where the responses are estimates of default probabilities usually derived from the leading credit rating agencies. In our empirical analysis we apply the proposed framework to a data set of US firms over the period from 1985 to 2014. Different sets of financial ratios constructed from financial statements and market information are selected as bankruptcy predictors in line with standard literature in failure prediction modeling. We find that the joint model of failures and credit ratings outperforms state-of-the-art failure prediction models and shadow rating approaches in terms of prediction accuracy and discriminatory power.

Tags

Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title A Joint Model of Failures and Credit Ratings
Event IAQF & Thalesians Seminar Series
Year 2021
Date 08.03-08.03
Country United States/USA
Location Zoom
URL https://www.iaqf.org/event-4089892
Invited Talk Y

Associations

Projects
Multivariate ordinal regression models for enhanced credit risk modeling
People
Hirk, Rainer (Details)
Vana Gür, Laura (Details)
Pichler, Stefan (Details)
Hornik, Kurt (Details)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
5361 Financial management (Details)
5701 Applied statistics (Details)
Google Scholar: Search