Comparer des méthodes

	Modèle EGARCH (GARCH exponentiel)	Autoregressive Vectoriel (VAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1991	1980
Auteur d'origine	Daniel B. Nelson	Christopher A. Sims
Type	Volatility / conditional variance model	Multivariate time-series model
Source fondatrice	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Alias	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	VAR, VAR model, vector autoregressive model, multivariate autoregression
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.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.