Usporedite metode

	Model GARCH (Prognoziranje volatilnosti)	Jednostavno i dvostruko eksponencijalno izglađivanje (SES / Holt)
Područje	Ekonometrija	Ekonometrija
Obitelj	Regression model	Regression model
Godina nastanka	1986	1957
Tvorac	Tim Bollerslev	Robert G. Brown (SES); Charles C. Holt (linear trend)
Vrsta	Conditional volatility model	Exponential smoothing forecasting model
Temeljni izvor	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.	Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill.
Drugi nazivi	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
Srodne	5	3
Sažetak	The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.	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.