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Fourier EGARCH: Modelování volatility s hladkými strukturálními změnami×Generalizovaná autoregresní podmíněná heteroskedasticita (GARCH)×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku2010s1986
TvůrceExtension of Nelson (1991) EGARCH using Fourier approximation frameworksTim Bollerslev
TypVolatility model with smooth structural breaksConditional volatility model
Původní zdrojEnders, 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 ↗
Další názvyFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Příbuzné35
ShrnutíFourier 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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ScholarGatePorovnat metody: Fourier EGARCH · GARCH. Získáno 2026-06-18 z https://scholargate.app/cs/compare