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Fourier GARCH model×ARCH model (Autoregressive Conditional Heteroskedasticity)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka2000–20121982
TvoracLudlow & Enders (2000); extended by Enders & Lee (2012) Fourier frameworkRobert F. Engle
VrstaVolatility modelConditional volatility model
Temeljni izvorLudlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Drugi naziviFourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Srodne56
SažetakThe Fourier GARCH model embeds trigonometric Fourier terms into a standard GARCH framework to capture smooth, gradual shifts in the conditional variance process without requiring knowledge of exact structural break dates. By approximating unknown break patterns with sinusoidal functions, it jointly models volatility clustering and time-varying unconditional variance.The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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ScholarGateUsporedite metode: Fourier GARCH Model · ARCH model. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare