方法对比

	门限向量自回归（TVAR）和光滑转换向量自回归（STVAR）	ARCH-LM检验用于波动率聚集	指数 GARCH (EGARCH)	马尔可夫状态转换模型 (MS-AR / MS-VAR)
领域	计量经济学	计量经济学	计量经济学	计量经济学
方法族	Regression model	Regression model	Regression model	Regression model
起源年份	1998	1982	1991	1989
提出者	Tsay (multivariate threshold modelling)	Robert F. Engle	Nelson	Hamilton (1989); Kim & Nelson (1999)
类型	Nonlinear multivariate time-series model	Lagrange multiplier diagnostic test for conditional heteroscedasticity	Conditional volatility model (asymmetric GARCH variant)	Regime-switching time series model
开创性文献	Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202.	Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987-1007.	Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370.	Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
别名	TVAR, STVAR, regime-switching VAR, threshold VAR	ARCH-LM Testi ve Volatilite Kümelenmesi Analizi, ARCH LM test, Engle's ARCH test, test for autoregressive conditional heteroscedasticity	exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH	regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
相关	5	6	4	5
摘要	Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences.	The ARCH-LM test is Robert Engle's (1982) Lagrange multiplier diagnostic for autoregressive conditional heteroscedasticity in the residuals of a fitted time-series model. It checks whether the error variance changes over time and clusters into calm and turbulent periods, and it is the standard pre-test run before fitting a GARCH-family volatility model.	EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.	The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.