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Model DCC-GARCH (dynamická podmienená korelácia)×Model TGARCH (Threshold GARCH)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku20021993-1994
TvorcaRobert F. EngleZakoian (1994); Glosten, Jagannathan & Runkle (1993)
TypMultivariate volatility modelAsymmetric volatility model
Pôvodný zdrojEngle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗
Ďalšie názvyDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCCThreshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
Príbuzné56
ZhrnutieThe DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many 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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ScholarGatePorovnať metódy: DCC-GARCH model · TGARCH model. Získané 2026-06-18 z https://scholargate.app/sk/compare