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Modello TGARCH di Fourier×Modello DCC-GARCH (Dynamic Conditional Correlation)×
CampoEconometriaEconometria
FamigliaRegression modelRegression model
Anno di origine1994 / 20122002
IdeatoreZakoian (1994) for TGARCH; Enders and Lee (2012) for Fourier approximation frameworkRobert F. Engle
TipoVolatility model with asymmetric leverage and Fourier smooth breaksMultivariate volatility model
Fonte seminaleZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗Engle, 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 ↗
AliasFourier TGARCH, Fourier Threshold GARCH, Fourier GJR-GARCH, smooth structural break TGARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Correlati55
SintesiThe Fourier TGARCH model extends the Threshold GARCH framework by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual structural breaks in volatility dynamics. It jointly models asymmetric leverage effects — where negative shocks amplify volatility more than positive shocks of the same magnitude — and time-varying intercept shifts caused by unobserved structural change.The 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.
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  3. PUBLISHED
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ScholarGateConfronta i metodi: Fourier TGARCH · DCC-GARCH model. Consultato il 2026-06-18 da https://scholargate.app/it/compare