Comparar métodos

	Modelo TGARCH no lineal	Modelo EGARCH (GARCH Exponencial)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1993–1994	1991
Autor original	Jean-Michel Zakoian; related work by Glosten, Jagannathan & Runkle	Daniel B. Nelson
Tipo	Conditional heteroskedasticity model	Volatility / conditional variance model
Fuente seminal	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Alias	NL-TGARCH, Nonlinear Threshold GARCH, Asymmetric TGARCH, GJR-GARCH variant	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Relacionados	4	6
Resumen	The Nonlinear TGARCH (Threshold GARCH) model extends the standard GARCH framework by allowing positive and negative shocks of equal magnitude to exert different effects on future volatility. It models conditional volatility in terms of the absolute value of lagged residuals split by a sign threshold, capturing the well-documented leverage effect in financial return 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.