Comparer des méthodes

	Modèle ARCH Non Linéaire (NARCH)	Modèle GARCH (Prévision de la volatilité)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1992	1986
Auteur d'origine	Higgins & Bera	Tim Bollerslev
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.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Alias	NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Apparentées	4	5
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 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.