Módszerek összehasonlítása

	EGARCH modell (Exponenciális GARCH)	DCC-GARCH modell (Dinamikus Feltételes Korreláció)
Tudományterület	Ökonometria	Ökonometria
Módszercsalád	Regression model	Regression model
Keletkezés éve	1991	2002
Megalkotó	Daniel B. Nelson	Robert F. Engle
Típus	Volatility / conditional variance model	Multivariate volatility model
Alapmű	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350.
Alternatív nevek	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Kapcsolódó	6	5
Összefoglaló	The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.	The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series.