Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| TGARCH-malli (Threshold GARCH)× | Vektorimallit (VAR)× | |
|---|---|---|
| Tieteenala | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1993-1994 | 1980 |
| Kehittäjä≠ | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) | Christopher A. Sims |
| Tyyppi≠ | Asymmetric volatility model | Multivariate time-series model |
| Alkuperäislähde≠ | 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 ↗ |
| Rinnakkaisnimet | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Liittyvät≠ | 6 | 5 |
| Tiivistelmä≠ | 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. |
| ScholarGateAineisto ↗ |
|
|