Jämför metoder

	Autoregressiv modell för betingad heteroskedasticitet (ARCH-modell)	TGARCH-modell (Threshold GARCH)
Ämnesområde	Ekonometri	Ekonometri
Familj	Regression model	Regression model
Ursprungsår	1982	1993-1994
Upphovsperson	Robert F. Engle	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
Typ	Conditional volatility model	Asymmetric volatility model
Ursprungskälla	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Alias	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Närliggande	6	6
Sammanfattning	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.	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.