Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель TGARCH (Threshold GARCH)× | Модель EGARCH (Експоненційна GARCH)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1993-1994 | 1991 |
| Автор методу≠ | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) | Daniel B. Nelson |
| Тип≠ | Asymmetric volatility model | Volatility / conditional variance model |
| Основоположне джерело≠ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Інші назви | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Пов'язані | 6 | 6 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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