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| Модел TGARCH (Threshold GARCH)× | Модел EGARCH (Експоненциален GARCH)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1993-1994 | 1991 |
| Създател≠ | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) | Daniel B. Nelson |
| Тип≠ | Asymmetric volatility model | Volatility / conditional variance model |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Свързани | 6 | 6 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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