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GJR-GARCH (GARCH Asimetri)×Model ARCH (Heteroskedastisitas Bersyarat Autoregresif)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19931982
PengasasGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Robert F. Engle
JenisAsymmetric conditional volatility modelConditional volatility model
Sumber perintisGlosten, 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 ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Aliasasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Berkaitan56
RingkasanGJR-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).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.
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ScholarGateBandingkan kaedah: GJR-GARCH · ARCH model. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare