Comparer des méthodes

	DCC-GARCH (Dynamic Conditional Correlation)	Lissage exponentiel simple et double (SES / Holt)
Domaine	Finance	Économétrie
Famille	Regression model	Regression model
Année d'origine	2002	1957
Auteur d'origine	Robert F. Engle	Robert G. Brown (SES); Charles C. Holt (linear trend)
Type	Multivariate volatility model	Exponential smoothing forecasting model
Source fondatrice	Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350.	Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill.
Alias	dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
Apparentées	5	3
Résumé	DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.	Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.