Uporedite metode
Pregledajte izabrane metode jednu pored druge; redovi koji se razlikuju su istaknuti.
| Nelinearni EGARCH model× | Model TGARCH (Prag GARCH)× | |
|---|---|---|
| Oblast | Ekonometrija | Ekonometrija |
| Porodica | Regression model | Regression model |
| Godina nastanka≠ | 1991 | 1993-1994 |
| Tvorac≠ | Daniel B. Nelson | Zakoian (1994); Glosten, Jagannathan & Runkle (1993) |
| Tip≠ | Conditional volatility model | Asymmetric volatility model |
| Temeljni izvor≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ |
| Drugi nazivi | NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH | Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH |
| Srodne≠ | 5 | 6 |
| Sažetak≠ | The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns. | 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. |
| ScholarGateSkup podataka ↗ |
|
|