Exposure at default models with and without the credit conversion factor

DOI10.1016/j.ejor.2016.01.054zbMath1346.62111OpenAlexW2264287315MaRDI QIDQ323002

Lyn C. Thomas, Edward N. C. Tong, Iain Brown, Christophe Mues

Publication date: 7 October 2016

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2016.01.054

zbMATH Keywords

risk analysisregressiongeneralized additive modelscredit cardsexposure at default

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Credit risk (91G40)

Related Items (3)

A class of residuals for outlier identification in zero adjusted regression models ⋮ Modelling credit card exposure at default using vine copula quantile regression ⋮ Sharp asymptotics for large portfolio losses under extreme risks

Uses Software

• GAMLSS
• ElemStatLearn

Cites Work

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• Estimation of Relationships for Limited Dependent Variables
• A new mixture model for the estimation of credit card exposure at default
• Mixture cure models in credit scoring: if and when borrowers default
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Survival Analysis Methods for Personal Loan Data
• Generalized Additive Models for Location, Scale and Shape
• A new look at the statistical model identification

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