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Muundo wa Fourier DCC-GARCH×Modeli wa GARCH (Utabiri wa Msukosuko)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward1986
MwanzilishiEngle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometricsTim Bollerslev
AinaMultivariate volatility model with smooth structural breaksConditional volatility model
Chanzo asiliaEngle, 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 ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Majina mbadalaFourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Zinazohusiana55
MuhtasariThe 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 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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ScholarGateLinganisha mbinu: Fourier DCC-GARCH · GARCH Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare