方法对比
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| 傅里叶对称GARCH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≠ | 1994 / 2012 | 1993-1994 |
| 提出者≠ | Zakoian (1994) for TGARCH; Enders and Lee (2012) for Fourier approximation framework | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| 类型≠ | Volatility model with asymmetric leverage and Fourier smooth breaks | Asymmetric volatility model |
| 开创性文献 | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| 别名 | Fourier TGARCH, Fourier Threshold GARCH, Fourier GJR-GARCH, smooth structural break TGARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| 相关≠ | 5 | 6 |
| 摘要≠ | The Fourier TGARCH model extends the Threshold GARCH framework by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual structural breaks in volatility dynamics. It jointly models asymmetric leverage effects — where negative shocks amplify volatility more than positive shocks of the same magnitude — and time-varying intercept shifts caused by unobserved structural change. | 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. |
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