Comparer des méthodes

	Autoregressive Conditional Heteroskedasticity généralisée (GARCH)	GJR-GARCH (GARCH asymétrique)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1986	1993
Auteur d'origine	Tim Bollerslev	Glosten, Jagannathan & Runkle (1993); Zakoian (1994)
Type	Conditional volatility model	Asymmetric conditional volatility model
Source fondatrice	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.	Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801.
Alias	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli	asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Apparentées	5	5
Résumé	GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.	GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).