Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Моделі копули (Гауссова, t, Клейтона, Гумбеля, Франка)× | Johansen Cointegration Test× | |
|---|---|---|
| Галузь | Фінанси | Фінанси |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1959 | 1991 |
| Автор методу≠ | Sklar (1959); dependence-concept treatment by Joe (1997) | Søren Johansen |
| Тип≠ | Dependence model | Multivariate cointegration / vector error correction model |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) | Johansen test, VECM, vector error correction model, multivariate cointegration |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
|
|