So sánh phương pháp

	Mô hình TGARCH (Threshold GARCH)	Mô hình ARCH (Autoregressive Conditional Heteroskedasticity)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1993-1994	1982
Người khởi xướng	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)	Robert F. Engle
Loại	Asymmetric volatility model	Conditional volatility model
Công trình gốc	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.
Tên gọi khác	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Liên quan	6	6
Tóm tắt	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 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.