方法对比
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| 已实现波动率与HAR模型× | 指数 GARCH (EGARCH)× | |
|---|---|---|
| 领域≠ | 金融学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2009 | 1991 |
| 提出者≠ | Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility) | Nelson |
| 类型≠ | Time-series regression of realized variance | Conditional volatility model (asymmetric GARCH variant) |
| 开创性文献≠ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| 别名≠ | realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| 相关≠ | 5 | 4 |
| 摘要≠ | Realized volatility estimates an asset's variance directly from high-frequency intraday returns rather than from a parametric latent process. The Heterogeneous Autoregressive (HAR) model of Corsi (2009), building on the realized-volatility framework of Andersen, Bollerslev, Diebold and Labys (2003), forecasts this measure by combining daily, weekly, and monthly volatility components, and is a strong alternative to GARCH for volatility prediction. | 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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