Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo EGARCH Robusto× | Modelo EGARCH (GARCH Exponencial)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2008 | 1991 |
| Autor original≠ | Nelson (1991) for EGARCH; robust adaptation via Muler & Yohai (2008) and related authors | Daniel B. Nelson |
| Tipo≠ | Robust volatility model | Volatility / conditional variance model |
| Fuente seminal≠ | Muler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | Robust EGARCH model, outlier-robust EGARCH, robust exponential GARCH, REGARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Relacionados | 6 | 6 |
| Resumen≠ | Robust EGARCH extends Nelson's (1991) Exponential GARCH model by replacing standard quasi-maximum likelihood estimation with outlier-resistant procedures — typically bounded-influence or M-estimation — so that a small fraction of extreme observations or data errors cannot distort the estimated volatility dynamics or the leverage effect. | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. |
| ScholarGateConjunto de datos ↗ |
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