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Model GARCH (Peramalan Volatiliti)×Model TGARCH (Threshold GARCH)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19861993-1994
PengasasTim BollerslevZakoian (1994); Glosten, Jagannathan & Runkle (1993)
JenisConditional volatility modelAsymmetric volatility model
Sumber perintisBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗
AliasGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Berkaitan56
RingkasanThe 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.The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.
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ScholarGateBandingkan kaedah: GARCH Model · TGARCH model. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare