方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 门限向量自回归(TVAR)和光滑转换向量自回归(STVAR)× | GJR-GARCH (不对称 GARCH)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1998 | 1993 |
| 提出者≠ | Tsay (multivariate threshold modelling) | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| 类型≠ | Nonlinear multivariate time-series model | Asymmetric conditional volatility 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. DOI ↗ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ |
| 别名≠ | TVAR, STVAR, regime-switching VAR, threshold VAR | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| 相关 | 5 | 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. | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). |
| ScholarGate数据集 ↗ |
|
|