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Ikke-lineær glidende gennemsnit (NMA) model×GARCH-model (volatilitetsprognoser)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår19781986
OphavspersonGranger & Andersen (bilinear/NMA framework); Tong (nonlinear time series theory)Tim Bollerslev
TypeNonlinear time series modelConditional volatility model
Oprindelig kildeGranger, C. W. J., & Andersen, A. P. (1978). An Introduction to Bilinear Time Series Models. Vandenhoeck and Ruprecht, Gottingen. link ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
AliasserNMA model, nonlinear moving average, NLMA model, nonlinear MAGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relaterede45
ResuméThe Nonlinear Moving Average (NMA) model extends the classical linear MA model by allowing the current observation to depend on past innovations through a nonlinear function rather than a simple weighted sum. It is used in time series analysis when error shocks transmit to outcomes in an asymmetric or state-dependent fashion.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.
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ScholarGateSammenlign metoder: Nonlinear MA model · GARCH Model. Hentet 2026-06-17 fra https://scholargate.app/da/compare