So sánh phương pháp

	Mô hình Fourier GARCH	Mô hình ARCH (Autoregressive Conditional Heteroskedasticity)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2000–2012	1982
Người khởi xướng	Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework	Robert F. Engle
Loại	Volatility model	Conditional volatility model
Công trình gốc	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.
Tên gọi khác	Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Liên quan	5	6
Tóm tắt	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.