方法对比

	稳健 EGARCH 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	2008	1993-1994
提出者	Nelson (1991) for EGARCH; robust adaptation via Muler & Yohai (2008) and related authors	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
类型	Robust volatility model	Asymmetric volatility model
开创性文献	Muler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
别名	Robust EGARCH model, outlier-robust EGARCH, robust exponential GARCH, REGARCH	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
相关	6	6
摘要	Robust EGARCH extends Nelson's (1991) Exponential GARCH model by replacing standard quasi-maximum likelihood estimation with outlier-resistant procedures — typically bounded-influence or M-estimation — so that a small fraction of extreme observations or data errors cannot distort the estimated volatility dynamics or the leverage effect.	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.