Confronta i metodi

	Modello TGARCH non lineare	Modello ARCH (Autoregressive Conditional Heteroskedasticity)
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1993–1994	1982
Ideatore	Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle	Robert F. Engle
Tipo	Conditional heteroskedasticity model	Conditional volatility model
Fonte seminale	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Correlati	4	6
Sintesi	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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.