Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modele de copulă (Gaussian, t, Clayton, Gumbel, Frank)× | Testul de cointegrare Johansen și Modelul Vectorial de Corecție a Erorilor× | |
|---|---|---|
| Domeniu | Finanțe | Finanțe |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1959 | 1991 |
| Autorul original≠ | Sklar (1959); dependence-concept treatment by Joe (1997) | Søren Johansen |
| Tip≠ | Dependence model | Multivariate cointegration / vector error correction model |
| Sursa seminală≠ | Sklar, 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 ↗ |
| Denumiri alternative≠ | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) | Johansen test, VECM, vector error correction model, multivariate cointegration |
| Înrudite≠ | 5 | 3 |
| Rezumat≠ | Copula 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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