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| Modèle TGARCH à paramètres variant dans le temps× | Modèle TGARCH (Threshold GARCH)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1990s–2000s | 1993-1994 |
| Auteur d'origine≠ | Extension combining Zakoïan (1994) TGARCH and time-varying parameter methods | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Type≠ | Volatility model with asymmetry and parameter evolution | Asymmetric volatility model |
| Source fondatrice≠ | Zakoïan, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| Alias | TVP-TGARCH, time-varying TGARCH, threshold GARCH with time-varying parameters, TVP Threshold GARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Apparentées≠ | 4 | 6 |
| Résumé≠ | The TVP-TGARCH model extends Threshold GARCH by allowing its volatility parameters to evolve over time via a state-space representation. It captures both the leverage effect — that negative return shocks increase volatility more than positive ones — and structural change in that asymmetry, making it well-suited for long financial time series subject to regime shifts. | 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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