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Fourier EGARCH: Volatilitetsmodellering med glatte strukturelle brudd×GJR-GARCH (Asymmetrisk GARCH)×
FagfeltØkonometriØkonometri
FamilieRegression modelRegression model
Opprinnelsesår2010s1993
OpphavspersonExtension of Nelson (1991) EGARCH using Fourier approximation frameworksGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TypeVolatility model with smooth structural breaksAsymmetric conditional volatility model
Opprinnelig kildeEnders, 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 ↗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 ↗
AliasFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Relaterte35
SammendragFourier 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.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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ScholarGateSammenlign metoder: Fourier EGARCH · GJR-GARCH. Hentet 2026-06-15 fra https://scholargate.app/no/compare