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| 傅里叶EGARCH：具有平滑结构性断裂的波动率建模× | 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≠ | 2010s | 1993 |
| 提出者≠ | Extension of Nelson (1991) EGARCH using Fourier approximation frameworks | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| 类型≠ | Volatility model with smooth structural breaks | Asymmetric conditional volatility model |
| 开创性文献≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. 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 | Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| 相关≠ | 3 | 5 |
| 摘要≠ | Fourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number. | 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). |
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