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Fourier EGARCH×GARCH (Generalized Autoregressive Conditional Heteroskedasticity)×GJR-GARCH (epäsymmetrinen GARCH)×
TieteenalaEkonometriaEkonometriaEkonometria
MenetelmäperheRegression modelRegression modelRegression model
Syntyvuosi2010s19861993
KehittäjäExtension of Nelson (1991) EGARCH using Fourier approximation frameworksTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TyyppiVolatility model with smooth structural breaksConditional volatility modelAsymmetric conditional volatility model
AlkuperäislähdeEnders, 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 ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
RinnakkaisnimetFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Liittyvät355
TiivistelmäFourier 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.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
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ScholarGateVertaile menetelmiä: Fourier EGARCH · GARCH · GJR-GARCH. Haettu 2026-06-20 osoitteesta https://scholargate.app/fi/compare