ScholarGate
Asistent

Uporedite metode

Pregledajte izabrane metode jednu pored druge; redovi koji se razlikuju su istaknuti.

Modelovanje kreditnog rizika (Merton, KMV, CreditMetrics)×Logistička regresija×
OblastFinansijeIstraživačka statistika
PorodicaRegression modelProcess / pipeline
Godina nastanka19741958
TvoracRobert C. Merton (structural model); J.P. Morgan / Gupton et al. (CreditMetrics)David Roxbee Cox
TipStructural and portfolio credit risk modelMethod
Temeljni izvorMerton, 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 ↗
Drugi naziviMerton model, KMV model, CreditMetrics, structural credit risk modellogit model, binomial logistic regression, LR
Srodne53
SažetakCredit 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.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretragu Preuzmi slajdove

ScholarGateUporedite metode: Credit Risk Models · Logistic Regression. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare