Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Векторна авторегресия с праг и плавен преход (TVAR / STVAR)× | Експоненциален GARCH (EGARCH)× | GJR-GARCH (Асиметричен GARCH)× | |
|---|---|---|---|
| Област | Иконометрия | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model | Regression model |
| Година на възникване≠ | 1998 | 1991 | 1993 |
| Създател≠ | Tsay (multivariate threshold modelling) | Nelson | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| Тип≠ | Nonlinear multivariate time-series model | Conditional volatility model (asymmetric GARCH variant) | Asymmetric conditional volatility model |
| Основополагащ източник≠ | Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. 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 ↗ |
| Други названия≠ | TVAR, STVAR, regime-switching VAR, threshold VAR | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| Свързани≠ | 5 | 4 | 5 |
| Резюме≠ | 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. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | 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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