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	Robustný GARCH model s dynamickou podmienkou korelácie (Robust DCC-GARCH)	Vektorová autoregresia (VAR)
Odbor	Ekonometria	Ekonometria
Rodina	Regression model	Regression model
Rok vzniku	2002–2021	1980
Tvorca	Engle (2002) for DCC; robust extensions by Pakel, Shephard, Sheppard, and Engle (2021)	Christopher A. Sims
Typ	Multivariate volatility model with robust estimation	Multivariate time-series model
Pôvodný zdroj	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.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Ďalšie názvy	robust DCC-GARCH, robust dynamic conditional correlation, outlier-robust DCC, composite-likelihood DCC-GARCH	VAR, VAR model, vector autoregressive model, multivariate autoregression
Príbuzné	6	5
Zhrnutie	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.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.