विधियों की तुलना करें

	गार्छ मॉडल (अस्थिरता पूर्वानुमान)	सरल और दोहरा घातीय समतलन (SES / Holt)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1986	1957
प्रवर्तक	Tim Bollerslev	Robert G. Brown (SES); Charles C. Holt (linear trend)
प्रकार	Conditional volatility model	Exponential smoothing forecasting model
मौलिक स्रोत	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.
उपनाम	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)
संबंधित	5	3
सारांश	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.