Сравнение методов

	Обобщенная авторегрессионная условная гетероскедастичность (GARCH)	Простое и двойное экспоненциальное сглаживание (SES / Холт)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1986	1957
Автор метода	Tim Bollerslev	Robert G. Brown (SES); Charles C. Holt (linear trend)
Тип	Conditional volatility model	Exponential smoothing forecasting model
Основополагающий источник	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.
Другие названия	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
Связанные	5	3
Сводка	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.	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.