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Model Fouriera ARCH×Model GARCH (Prognozowanie zmienności)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2010s1986
TwórcaExtends Engle (1982) ARCH framework with Fourier terms following Enders & Lee (2012)Tim Bollerslev
TypVolatility model with smooth structural changeConditional volatility model
Źródło pierwotneEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Inne nazwyFourier-ARCH, F-ARCH, ARCH with Fourier terms, Fourier smooth transition ARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Pokrewne65
PodsumowanieThe Fourier ARCH model extends the classical ARCH framework by incorporating trigonometric (Fourier) terms into the conditional variance equation. This allows the model to capture smooth, gradual shifts in volatility dynamics over time without assuming abrupt structural breaks, making it well-suited for long financial or macroeconomic time series subject to slowly evolving regime changes.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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ScholarGatePorównaj metody: Fourier ARCH Model · GARCH Model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare