Salīdzināt metodes

	TGARCH modelis (sliekšņa GARCH)	EGARCH modelis (eksponenciālais GARCH)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1993-1994	1991
Autors	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)	Daniel B. Nelson
Tips	Asymmetric volatility model	Volatility / conditional variance model
Pirmavots	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Citi nosaukumi	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Saistītās	6	6
Kopsavilkums	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.	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.