Comparar métodos

	Modelo EGARCH con Parámetros Variables en el Tiempo	Modelo GARCH (Predicción de Volatilidad)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1991–2000s	1986
Autor original	Nelson (1991) for EGARCH; TVP extension developed across the 1990s–2000s literature (e.g., Harvey, Engle and co-authors)	Tim Bollerslev
Tipo	Conditional volatility model	Conditional volatility model
Fuente seminal	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Alias	TVP-EGARCH, time-varying EGARCH, EGARCH with time-varying parameters, dynamic parameter EGARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relacionados	3	5
Resumen	The TVP-EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the volatility equation's parameters — including the leverage effect coefficient — to drift continuously over time. This makes it possible to capture structural change and regime evolution in financial return volatility without imposing a fixed break date.	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.