方法对比

	自回归条件异方差 (ARCH) 模型	TGARCH 模型（阈值 GARCH）
领域	计量经济学	计量经济学
方法族	Regression model	Regression model
起源年份	1982	1993-1994
提出者	Robert F. Engle	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
类型	Conditional volatility model	Asymmetric volatility model
开创性文献	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.
别名	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
相关	6	6
摘要	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.