Comparer des méthodes

	Fourier EGARCH	Autoregressive Conditional Heteroskedasticity généralisée (GARCH)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2010s	1986
Auteur d'origine	Extension of Nelson (1991) EGARCH using Fourier approximation frameworks	Tim Bollerslev
Type	Volatility model with smooth structural breaks	Conditional volatility model
Source fondatrice	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
Apparentées	3	5
Résumé	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.