Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель Фур'є-GARCH× | Модель TGARCH (Threshold GARCH)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2000–2012 | 1993-1994 |
| Автор методу≠ | Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Тип≠ | Volatility model | Asymmetric volatility model |
| Основоположне джерело≠ | Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| Інші назви | Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Пов'язані≠ | 5 | 6 |
| Підсумок≠ | The Fourier GARCH model embeds trigonometric Fourier terms into a standard GARCH framework to capture smooth, gradual shifts in the conditional variance process without requiring knowledge of exact structural break dates. By approximating unknown break patterns with sinusoidal functions, it jointly models volatility clustering and time-varying unconditional variance. | 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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