Comparer des méthodes

	Modèle DCC-GARCH avec rupture structurelle	Modèle DCC-GARCH (Corrélation Conditionnelle Dynamique)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2002-2006	2002
Auteur d'origine	Engle (2002) for DCC; break-augmented extensions by Pelletier (2006) and subsequent literature	Robert F. Engle
Type	Multivariate volatility model with regime change	Multivariate volatility model
Source fondatrice	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.
Alias	DCC-GARCH with structural breaks, break-adjusted DCC-GARCH, regime-shift DCC-GARCH, SB-DCC-GARCH	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Apparentées	5	5
Résumé	Structural break DCC-GARCH extends Engle's Dynamic Conditional Correlation GARCH framework by explicitly allowing the correlation and volatility structure to shift at one or more structural break points in the sample. It models time-varying co-volatility between multiple financial series while accounting for sudden regime changes caused by crises, policy shifts, or market microstructure changes.	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.