方法对比
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| GARCH 模型（波动率预测）× | 指数 GARCH (EGARCH)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1986 | 1991 |
| 提出者≠ | Tim Bollerslev | Nelson |
| 类型≠ | Conditional volatility model | Conditional volatility model (asymmetric GARCH variant) |
| 开创性文献≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| 别名 | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| 相关≠ | 5 | 4 |
| 摘要≠ | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. | 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. |
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