Comparer des méthodes

	Modèle ARCH Non Linéaire (NARCH)	Modèle ARCH (Hétéroscédasticité Conditionnelle Autorégressive)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1992	1982
Auteur d'origine	Higgins & Bera	Robert F. Engle
Type	Volatility model	Conditional volatility model
Source fondatrice	Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
Alias	NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Apparentées	4	6
Résumé	The Nonlinear ARCH (NARCH) model, introduced by Higgins and Bera (1992), extends Engle's original ARCH framework by allowing the power transformation of volatility to be estimated from the data rather than fixed at two. This flexibility captures a broader class of volatility dynamics observed in financial and macroeconomic time series.	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.