Bandingkan metode

	Model GARCH Fourier	Model ARCH (Autoregressive Conditional Heteroskedasticity)
Bidang	Ekonometrika	Ekonometrika
Keluarga	Regression model	Regression model
Tahun asal	2000–2012	1982
Pencetus	Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework	Robert F. Engle
Tipe	Volatility model	Conditional volatility model
Sumber perintis	Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Terkait	5	6
Ringkasan	The 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.