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Generaliserad Autoregressiv Konditionell Heteroskedasticitet (GARCH)×Enkel och dubbel exponentiell utjämning (SES / Holt)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19861957
UpphovspersonTim BollerslevRobert G. Brown (SES); Charles C. Holt (linear trend)
TypConditional volatility modelExponential smoothing forecasting model
UrsprungskällaBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗
AliasGARCH(1,1), generalized ARCH, conditional volatility model, GARCH ModeliSES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
Närliggande53
SammanfattningGARCH 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.
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ScholarGateJämför metoder: GARCH · Exponential Smoothing. Hämtad 2026-06-17 från https://scholargate.app/sv/compare