Salīdzināt metodes

	Nelineārais TGARCH modelis	TGARCH modelis (sliekšņa GARCH)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1993–1994	1993-1994
Autors	Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Tips	Conditional heteroskedasticity model	Asymmetric volatility model
Pirmavots	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Citi nosaukumi	NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Saistītās	4	6
Kopsavilkums	The Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series.	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.