方法对比

	分量GARCH模型	方差因果关系检验
领域	计量经济学	计量经济学
方法族	Regression model	Regression model
起源年份	1999	1996
提出者	Engle and Lee	Yin-Wong Cheung and Lilian Ng
类型	Decomposed variance model	Conditional variance test
开创性文献	Engle, R. F., & Lee, G. (1999). A permanent and transitory component model of stock return volatility. Journal of Political Economy, 107(6), 1363-1384.	Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-61.
别名	Volatility components model	Volatility spillover test
相关	3	3
摘要	Component GARCH decomposes conditional variance into transitory (short-term) and permanent (long-term) components with different dynamics, allowing flexibility in capturing volatility behavior at multiple frequencies. Introduced by Engle and Lee (1999), it elegantly models the empirical finding that volatility exhibits both rapid mean-reversion (daily shocks) and slow mean-reversion (level shifts). This framework is crucial for understanding volatility persistence and improving long-horizon volatility forecasting.	The causality-in-variance test detects whether shocks to one variable cause changes in the conditional variance (volatility) of another variable, distinct from mean-level causality. Introduced by Cheung and Ng (1996), it identifies volatility spillovers and contagion effects—crucial for risk management and understanding financial market interdependencies. This approach has become standard in studying shock transmission across asset classes and geographies.