Comparer des méthodes

	Modèle EGARCH (GARCH exponentiel)	Régression quantile
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1978
Auteur d'origine	Daniel B. Nelson	Koenker & Bassett
Type	Volatility / conditional variance model	Conditional quantile regression
Source fondatrice	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	6	5
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.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.