Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo ARCH Robusto× | Modelo EGARCH (GARCH Exponencial)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2002–2008 | 1991 |
| Autor original≠ | Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s | Daniel B. Nelson |
| Tipo≠ | Volatility / conditional heteroscedasticity model | Volatility / conditional variance model |
| Fuente seminal≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Alias | robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Relacionados | 6 | 6 |
| Resumen≠ | The Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time series. | 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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