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。
| 面板TGARCH（面板数据阈值GARCH模型）× | DCC-GARCH（动态条件相关性）× | |
|---|---|---|
| 领域≠ | 计量经济学 | 金融学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1993–1994 (panel extension: 2000s onward) | 2002 |
| 提出者≠ | Glosten, Jagannathan & Runkle (1993); Zakoian (1994); extended to panel settings by subsequent applied finance literature | Robert F. Engle |
| 类型≠ | Asymmetric conditional volatility model | Multivariate volatility model |
| 开创性文献≠ | 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. Journal of Finance, 48(5), 1779–1801. DOI ↗ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ |
| 别名 | Panel GJR-GARCH, Panel Asymmetric GARCH, Panel Threshold GARCH, TGARCH panel model | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon |
| 相关≠ | 4 | 5 |
| 摘要≠ | Panel TGARCH extends the Threshold GARCH (GJR-GARCH) model to panel data, allowing each cross-sectional unit to exhibit asymmetric volatility responses — where negative shocks generate larger variance increases than positive shocks of the same magnitude — while exploiting the cross-sectional dimension to obtain more efficient parameter estimates. | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. |
| ScholarGate数据集 ↗ |
|
|