Salīdzināt metodes

	Nelineārais TGARCH modelis	Autoregresīvās nosacītās heteroskedastiskuma (ARCH) modelis
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1993–1994	1982
Autors	Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle	Robert F. Engle
Tips	Conditional heteroskedasticity model	Conditional volatility model
Pirmavots	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.
Citi nosaukumi	NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
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 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.