Comparar métodos

	Modelo EGARCH (GARCH Exponencial)	Modelo ARCH (Heterocedasticidad Autoregresiva Condicional)
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1991	1982
Autor original	Daniel B. Nelson	Robert F. Engle
Tipo	Volatility / conditional variance model	Conditional volatility model
Fuente seminal	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Relacionados	6	6
Resumen	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.	The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.