방법 비교

	EGARCH 모형 (Exponential GARCH)	TGARCH 모형 (Threshold GARCH)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1991	1993-1994
창시자	Daniel B. Nelson	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
유형	Volatility / conditional variance model	Asymmetric volatility model
원전	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
별칭	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
관련	6	6
요약	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.	The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.