Сравнение методов

	Нелинейная модель EGARCH	Модель TGARCH (Threshold GARCH)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1991	1993-1994
Автор метода	Daniel B. Nelson	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Тип	Conditional volatility model	Asymmetric volatility model
Основополагающий источник	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.
Другие названия	NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Связанные	5	6
Сводка	The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.	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.