Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Nelineární model EGARCH× | Model TGARCH (Threshold GARCH)× | |
|---|---|---|
| Obor | Ekonometrie | Ekonometrie |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1991 | 1993-1994 |
| Tvůrce≠ | Daniel B. Nelson | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Typ≠ | Conditional volatility model | Asymmetric volatility model |
| Původní zdroj≠ | 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 ↗ |
| Další názvy | NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Příbuzné≠ | 5 | 6 |
| Shrnutí≠ | 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. |
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