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	Model ARCH (Autoregresywna Heteroskedastyczność Warunkowa)	Model DCC-GARCH (Dynamic Conditional Correlation)
Dziedzina	Ekonometria	Ekonometria
Rodzina	Regression model	Regression model
Rok powstania	1982	2002
Twórca	Robert F. Engle	Robert F. Engle
Typ	Conditional volatility model	Multivariate volatility model
Źródło pierwotne	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	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.
Inne nazwy	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Pokrewne	6	5
Podsumowanie	The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.	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.