Methoden vergelijken

	Robuuste Dynamische Conditionele Correlatie GARCH (Robuuste DCC-GARCH)	DCC-GARCH Model (Dynamic Conditional Correlation)
Vakgebied	Econometrie	Econometrie
Familie	Regression model	Regression model
Jaar van ontstaan	2002–2021	2002
Grondlegger	Engle (2002) for DCC; robust extensions by Pakel, Shephard, Sheppard, and Engle (2021)	Robert F. Engle
Type	Multivariate volatility model with robust estimation	Multivariate volatility model
Oorspronkelijke bron	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.	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.
Aliassen	robust DCC-GARCH, robust dynamic conditional correlation, outlier-robust DCC, composite-likelihood DCC-GARCH	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Verwant	6	5
Samenvatting	The Robust DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation framework by replacing standard quasi-maximum likelihood estimation with outlier-resistant or composite-likelihood techniques. This preserves accurate time-varying correlation estimation even when financial return data contain extreme observations, heavy tails, or structural irregularities.	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.