Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| TGARCH modelis (sliekšņa GARCH)× | Vektora autoregresija (VAR)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1993-1994 | 1980 |
| Autors≠ | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) | Christopher A. Sims |
| Tips≠ | Asymmetric volatility model | Multivariate time-series model |
| Pirmavots≠ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Citi nosaukumi | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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