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Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| GJR-GARCH (GARCH asimétrico)× | EGARCH de panel× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1993 | 1991 (EGARCH); panel extensions widely used from 2000s |
| Autor original≠ | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) | Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature |
| Tipo≠ | Asymmetric conditional volatility model | Volatility model |
| Fuente seminal≠ | 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 ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) | Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | 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). | Panel EGARCH extends Nelson's (1991) Exponential GARCH model to a panel setting, allowing conditional variance to evolve asymmetrically over time for each cross-sectional unit. The log specification ensures non-negative variance without parameter constraints, and the leverage term distinguishes whether negative shocks amplify volatility more than positive ones of equal magnitude. |
| ScholarGateConjunto de datos ↗ |
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