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Fourier EGARCH: Modeliranje volatilnosti s glatkim strukturnim promjenama×Generalizirani autoregresivni uvjetni heteroskedasticitet (GARCH)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka2010s1986
TvoracExtension of Nelson (1991) EGARCH using Fourier approximation frameworksTim Bollerslev
VrstaVolatility model with smooth structural breaksConditional volatility model
Temeljni izvorEnders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗
Drugi naziviFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Srodne35
SažetakFourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number.GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.
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ScholarGateUsporedite metode: Fourier EGARCH · GARCH. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare