Comparer des méthodes

	Modèle TGARCH Non Linéaire	Modèle EGARCH (GARCH exponentiel)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1993–1994	1991
Auteur d'origine	Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle	Daniel B. Nelson
Type	Conditional heteroskedasticity model	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	NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Apparentées	4	6
Résumé	The Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series.	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.