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	Modello GARCH a Correlazione Condizionale Dinamica Robusto (Robust DCC-GARCH)	Autoregressione Vettoriale (VAR)
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	2002–2021	1980
Ideatore	Engle (2002) for DCC; robust extensions by Pakel, Shephard, Sheppard, and Engle (2021)	Christopher A. Sims
Tipo	Multivariate volatility model with robust estimation	Multivariate time-series model
Fonte seminale	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.
Alias	robust DCC-GARCH, robust dynamic conditional correlation, outlier-robust DCC, composite-likelihood DCC-GARCH	VAR, VAR model, vector autoregressive model, multivariate autoregression
Correlati	6	5
Sintesi	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.