Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Нелінійна модель EGARCH× | Модель TGARCH (Threshold GARCH)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1991 | 1993-1994 |
| Автор методу≠ | Daniel B. Nelson | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Тип≠ | Conditional volatility model | Asymmetric volatility model |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Пов'язані≠ | 5 | 6 |
| Підсумок≠ | The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns. | 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. |
| ScholarGateНабір даних ↗ |
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