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GARCH model (predviđanje volatilnosti)×GJR-GARCH (Asimetrični GARCH)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19861993
TvoracTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipConditional volatility modelAsymmetric conditional volatility model
Temeljni izvorBollerslev, 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 ↗
Drugi naziviGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Srodne55
SažetakThe 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.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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ScholarGateUporedite metode: GARCH Model · GJR-GARCH. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare