Comparer des méthodes

	Modèle EGARCH non linéaire	Modèle EGARCH (GARCH exponentiel)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1991
Auteur d'origine	Daniel B. Nelson	Daniel B. Nelson
Type	Conditional volatility model	Volatility / conditional variance model
Source fondatrice	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Alias	NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Apparentées	5	6
Résumé	The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.	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.