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TGARCH-malli (Threshold GARCH)×Autoregressiivisen ehdollisen heteroskedastisuuden (ARCH) malli×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi1993-19941982
KehittäjäZakoian (1994); Glosten, Jagannathan & Runkle (1993)Robert F. Engle
TyyppiAsymmetric volatility modelConditional volatility model
AlkuperäislähdeZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
RinnakkaisnimetThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Liittyvät66
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 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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ScholarGateVertaile menetelmiä: TGARCH model · ARCH model. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare