Usporedite metode

	Nelinearni GARCH model	EGARCH model (eksponencijalni GARCH)
Područje	Ekonometrija	Ekonometrija
Obitelj	Regression model	Regression model
Godina nastanka	1991-1993	1991
Tvorac	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Daniel B. Nelson
Vrsta	Volatility model	Volatility / conditional variance model
Temeljni izvor	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.
Drugi nazivi	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Srodne	6	6
Sažetak	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.