Comparer des méthodes

	Modèle EGARCH (GARCH exponentiel)	Modèle TGARCH (Threshold GARCH)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1993-1994
Auteur d'origine	Daniel B. Nelson	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Type	Volatility / conditional variance model	Asymmetric volatility model
Source fondatrice	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Alias	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Apparentées	6	6
Résumé	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.	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.