Confronta i metodi

	Modello EGARCH Non Lineare	Modello ARCH (Autoregressive Conditional Heteroskedasticity)
Campo	Econometria	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1991	1982
Ideatore	Daniel B. Nelson	Robert F. Engle
Tipo	Conditional volatility model	Conditional volatility model
Fonte seminale	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	NL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCH	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Correlati	5	6
Sintesi	The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.	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.