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| DCC-GARCH (Dynamická podmienená korelácia)× | Kopula modely (Gaussovské, t, Clayton, Gumbel, Frank)× | Exponential GARCH (EGARCH)× | |
|---|---|---|---|
| Odbor≠ | Financie | Financie | Ekonometria |
| Rodina | Regression model | Regression model | Regression model |
| Rok vzniku≠ | 2002 | 1959 | 1991 |
| Tvorca≠ | Robert F. Engle | Sklar (1959); dependence-concept treatment by Joe (1997) | Nelson |
| Typ≠ | Multivariate volatility model | Dependence model | Conditional volatility model (asymmetric GARCH variant) |
| Pôvodný zdroj≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | 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 ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| Ďalšie názvy | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank) | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| Príbuzné≠ | 5 | 5 | 4 |
| Zhrnutie≠ | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. | 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. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. |
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