Comparer des méthodes

	Lissage exponentiel simple et double (SES / Holt)	Autoregressive Conditional Heteroskedasticity généralisée (GARCH)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1957	1986
Auteur d'origine	Robert G. Brown (SES); Charles C. Holt (linear trend)	Tim Bollerslev
Type	Exponential smoothing forecasting model	Conditional volatility model
Source fondatrice	Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
Alias	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Apparentées	3	5
Résumé	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.	GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.