方法对比
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| 自回归条件异方差 (ARCH) 模型× | EGARCH model× | TGARCH 模型(阈值 GARCH)× | |
|---|---|---|---|
| 领域 | 计量经济学 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model | Regression model |
| 起源年份≠ | 1982 | 1991 | 1993-1994 |
| 提出者≠ | Robert F. Engle | Daniel B. Nelson | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| 类型≠ | Conditional volatility model | Volatility / conditional variance model | Asymmetric volatility model |
| 开创性文献≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| 别名 | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| 相关 | 6 | 6 | 6 |
| 摘要≠ | The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering. | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. | 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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