Comparer des méthodes

	Modèle EGARCH (GARCH exponentiel)	Modèle ARCH (Hétéroscédasticité Conditionnelle Autorégressive)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1982
Auteur d'origine	Daniel B. Nelson	Robert F. Engle
Type	Volatility / conditional variance model	Conditional volatility model
Source fondatrice	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.