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	Nelineárny model DCC-GARCH (Asymetrická dynamická podmienená korelácia)	Model DCC-GARCH (dynamická podmienená korelácia)
Odbor	Ekonometria	Ekonometria
Rodina	Regression model	Regression model
Rok vzniku	2006	2002
Tvorca	Cappiello, Engle & Sheppard	Robert F. Engle
Typ	Multivariate volatility and correlation model	Multivariate volatility model
Pôvodný zdroj	Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537–572.	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.
Ďalšie názvy	ADCC-GARCH, Asymmetric DCC-GARCH, NL-DCC-GARCH, Nonlinear Asymmetric DCC	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Príbuzné	2	5
Zhrnutie	The Nonlinear DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation framework by allowing correlations to respond asymmetrically to negative versus positive return shocks. Proposed by Cappiello, Engle, and Sheppard (2006), it is the standard tool for measuring time-varying co-movement and contagion effects in multivariate financial time series when bad news is expected to increase correlations more than good news.	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.