Comparar métodos

	Modelo EGARCH Robusto	Modelo GARCH (Predicción de Volatilidad)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	2008	1986
Autor original	Nelson (1991) for EGARCH; robust adaptation via Muler & Yohai (2008) and related authors	Tim Bollerslev
Tipo	Robust volatility model	Conditional volatility model
Fuente seminal	Muler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Alias	Robust EGARCH model, outlier-robust EGARCH, robust exponential GARCH, REGARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relacionados	6	5
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 Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.