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Kopula modeli (Gauss, t, Clayton, Gumbel, Frank)×Johansenov test kointegracije i model vektorske korekcije pogrešaka×
PodručjeFinancijeFinancije
ObiteljRegression modelRegression model
Godina nastanka19591991
TvoracSklar (1959); dependence-concept treatment by Joe (1997)Søren Johansen
VrstaDependence modelMultivariate cointegration / vector error correction model
Temeljni izvorSklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231. link ↗Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗
Drugi nazivicopulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank)Johansen test, VECM, vector error correction model, multivariate cointegration
Srodne53
SažetakCopula models are a family of functions that describe the dependence structure between variables separately from their individual (marginal) distributions. The foundation is Sklar's theorem (1959), which shows that any multivariate distribution can be split into its marginals plus a copula; Joe (1997) developed the modern catalogue of dependence concepts. They are central to portfolio risk and credit modelling.The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.
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ScholarGateUsporedite metode: Copula Models · Johansen Cointegration Test. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare