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TGARCH-malli (Threshold GARCH)×GARCH-malli (volatiliteetin ennustaminen)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi1993-19941986
KehittäjäZakoian (1994); Glosten, Jagannathan & Runkle (1993)Tim Bollerslev
TyyppiAsymmetric volatility modelConditional volatility model
AlkuperäislähdeZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
RinnakkaisnimetThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Liittyvät65
TiivistelmäThe 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.The 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.
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ScholarGateVertaile menetelmiä: TGARCH model · GARCH Model. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare