Bandingkan kaedah

	Fourier EGARCH: Pemodelan Volatiliti dengan Perubahan Struktur yang Lancar	Generalised Autoregressive Conditional Heteroskedasticity (GARCH)
Bidang	Ekonometrik	Ekonometrik
Keluarga	Regression model	Regression model
Tahun asal	2010s	1986
Pengasas	Extension of Nelson (1991) EGARCH using Fourier approximation frameworks	Tim Bollerslev
Jenis	Volatility model with smooth structural breaks	Conditional volatility model
Sumber perintis	Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
Alias	Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Berkaitan	3	5
Ringkasan	Fourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number.	GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.