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| Modèle ARCH à Rupture Structurelle× | Modèle TGARCH (Threshold GARCH)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1982–1990 | 1993-1994 |
| Auteur d'origine≠ | Engle (1982) for ARCH; Lamoureux & Lastrapes (1990) for break-adjusted variance persistence | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Type≠ | Volatility model with regime change | Asymmetric volatility model |
| Source fondatrice≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| Alias | ARCH with structural breaks, break-adjusted ARCH, regime-switching ARCH, SB-ARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Apparentées≠ | 5 | 6 |
| Résumé≠ | The Structural Break ARCH model extends Engle's (1982) Autoregressive Conditional Heteroscedasticity framework by explicitly accounting for abrupt, permanent shifts in the conditional variance process. Ignoring structural breaks in variance causes ARCH parameters to appear spuriously persistent, so incorporating break dummies or regime-specific parameters yields more accurate volatility estimates and better model fit. | 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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