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Autoregressiu Condicional Heteroscedàstic Generalitzat (GARCH)×GJR-GARCH (GARCH asimètric)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen19861993
Autor originalTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipusConditional volatility modelAsymmetric conditional volatility model
Font seminalBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗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. DOI ↗
ÀliesGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Relacionats55
ResumGARCH 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).
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ScholarGateCompara mètodes: GARCH · GJR-GARCH. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare