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| Progowy i gładko-przejściowy VAR (TVAR / STVAR)× | GJR-GARCH (Asymetryczny GARCH)× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1998 | 1993 |
| Twórca≠ | Tsay (multivariate threshold modelling) | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| Typ≠ | Nonlinear multivariate time-series model | Asymmetric conditional volatility model |
| Źródło pierwotne≠ | Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗ | Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗ |
| Inne nazwy≠ | TVAR, STVAR, regime-switching VAR, threshold VAR | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences. | GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994). |
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