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Kreditrisikomodelle (Merton, KMV, CreditMetrics)×Logistische Regression×
FachgebietFinanzwirtschaftForschungsstatistik
FamilieRegression modelProcess / pipeline
Entstehungsjahr19741958
UrheberRobert C. Merton (structural model); J.P. Morgan / Gupton et al. (CreditMetrics)David Roxbee Cox
TypStructural and portfolio credit risk modelMethod
Wegweisende QuelleMerton, R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. The Journal of Finance, 29(2), 449-470. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
AliasnamenMerton model, KMV model, CreditMetrics, structural credit risk modellogit model, binomial logistic regression, LR
Verwandt53
ZusammenfassungCredit risk models estimate the probability that a borrower defaults and the resulting distribution of credit losses. The structural approach was introduced by Robert C. Merton in 1974, treating a firm's equity as a call option on its assets, and was later extended into the KMV distance-to-default framework and the CreditMetrics rating-transition portfolio model published by J.P. Morgan in 1997.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.
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ScholarGateMethoden vergleichen: Credit Risk Models · Logistic Regression. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare