Salīdzināt metodes

	Nelineārais EGARCH modelis	TGARCH modelis (sliekšņa GARCH)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1991	1993-1994
Autors	Daniel B. Nelson	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Tips	Conditional volatility model	Asymmetric volatility model
Pirmavots	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.
Citi nosaukumi	NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Saistītās	5	6
Kopsavilkums	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.