Comparer des méthodes

	Modèle TGARCH de Fourier	Modèle EGARCH (GARCH exponentiel)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1994 / 2012	1991
Auteur d'origine	Zakoian (1994) for TGARCH; Enders and Lee (2012) for Fourier approximation framework	Daniel B. Nelson
Type	Volatility model with asymmetric leverage and Fourier smooth breaks	Volatility / conditional variance model
Source fondatrice	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Alias	Fourier TGARCH, Fourier Threshold GARCH, Fourier GJR-GARCH, smooth structural break TGARCH	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Apparentées	5	6
Résumé	The Fourier TGARCH model extends the Threshold GARCH framework by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual structural breaks in volatility dynamics. It jointly models asymmetric leverage effects — where negative shocks amplify volatility more than positive shocks of the same magnitude — and time-varying intercept shifts caused by unobserved structural change.	The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.