Vertaile menetelmiä

	Epälineaarinen GARCH-malli	EGARCH-malli (Exponential GARCH)
Tieteenala	Ekonometria	Ekonometria
Menetelmäperhe	Regression model	Regression model
Syntyvuosi	1991-1993	1991
Kehittäjä	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Daniel B. Nelson
Tyyppi	Volatility model	Volatility / conditional variance model
Alkuperäislähde	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.
Rinnakkaisnimet	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Liittyvät	6	6
Tiivistelmä	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.