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Fourier EGARCH: Modellierung von Volatilität mit glatten strukturellen Brüchen×Exponential GARCH (EGARCH)×Generalisierte Autoregressive Bedingte Heteroskedastizität (GARCH)×
FachgebietÖkonometrieÖkonometrieÖkonometrie
FamilieRegression modelRegression modelRegression model
Entstehungsjahr2010s19911986
UrheberExtension of Nelson (1991) EGARCH using Fourier approximation frameworksNelsonTim Bollerslev
TypVolatility model with smooth structural breaksConditional volatility model (asymmetric GARCH variant)Conditional volatility model
Wegweisende QuelleEnders, 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 ↗Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗
AliasnamenFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Verwandt345
ZusammenfassungFourier 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.EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.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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ScholarGateMethoden vergleichen: Fourier EGARCH · EGARCH · GARCH. Abgerufen am 2026-06-20 von https://scholargate.app/de/compare