Comparer des méthodes

	Modèle GARCH de Fourier	Modèle TGARCH (Threshold GARCH)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2000–2012	1993-1994
Auteur d'origine	Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Type	Volatility model	Asymmetric volatility model
Source fondatrice	Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Alias	Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Apparentées	5	6
Résumé	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 Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.