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Fourier GARCH-modell×Autoregressiv modell för betingad heteroskedasticitet (ARCH-modell)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår2000–20121982
UpphovspersonLudlow & Enders (2000); extended by Enders & Lee (2012) Fourier frameworkRobert F. Engle
TypVolatility modelConditional volatility model
UrsprungskällaLudlow, 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 ↗
AliasFourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Närliggande56
SammanfattningThe 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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ScholarGateJämför metoder: Fourier GARCH Model · ARCH model. Hämtad 2026-06-18 från https://scholargate.app/sv/compare