방법 비교

	비선형 GARCH 모형	EGARCH 모형 (Exponential GARCH)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1991-1993	1991
창시자	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Daniel B. Nelson
유형	Volatility model	Volatility / conditional variance model
원전	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.
별칭	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
관련	6	6
요약	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.