Methoden vergleichen

	Nichtlineares GARCH-Modell	EGARCH-Modell (Exponential GARCH)
Fachgebiet	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	1991-1993	1991
Urheber	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Daniel B. Nelson
Typ	Volatility model	Volatility / conditional variance model
Wegweisende Quelle	Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance, 48(5), 1779-1801.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Aliasnamen	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Verwandt	6	6
Zusammenfassung	The Nonlinear GARCH model extends the standard GARCH framework to capture asymmetric and nonlinear responses of conditional volatility to past shocks. It allows negative returns (bad news) to amplify volatility more than positive returns of equal magnitude, a phenomenon known as the leverage effect, which is empirically pervasive in financial markets.	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.