Salīdzināt metodes

	Modelis ar strukturālām pārtraukuma vietām DCC-GARCH	DCC-GARCH modelis (Dynamic Conditional Correlation)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	2002-2006	2002
Autors	Engle (2002) for DCC; break-augmented extensions by Pelletier (2006) and subsequent literature	Robert F. Engle
Tips	Multivariate volatility model with regime change	Multivariate volatility model
Pirmavots	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.
Citi nosaukumi	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
Saistītās	5	5
Kopsavilkums	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.