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Fourier DCC-GARCH -malli×DCC-GARCH-malli (dynaaminen ehdollinen korrelaatio)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward2002
KehittäjäEngle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometricsRobert F. Engle
TyyppiMultivariate volatility model with smooth structural breaksMultivariate volatility model
AlkuperäislähdeEngle, R. (2002). Dynamic conditional correlations: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. link ↗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 ↗
RinnakkaisnimetFourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Liittyvät55
TiivistelmäThe Fourier DCC-GARCH model extends Engle's Dynamic Conditional Correlation GARCH framework by embedding Fourier trigonometric terms in the conditional mean or variance equations. This allows the model to approximate smooth, gradual structural shifts in volatility dynamics and inter-asset correlations without requiring knowledge of the number or timing of break points.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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ScholarGateVertaile menetelmiä: Fourier DCC-GARCH · DCC-GARCH model. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare