Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель Нелінійного TGARCH× | Модель EGARCH (Експоненційна GARCH)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1993–1994 | 1991 |
| Автор методу≠ | Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle | Daniel B. Nelson |
| Тип≠ | Conditional heteroskedasticity 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 | NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Пов'язані≠ | 4 | 6 |
| Підсумок≠ | The Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return series. | 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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