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Fourier EGARCH: Uundaji wa Volatiliti kwa Mapumziko Laini ya Kimuundo×Umuundo wa Kujirudia kwa Kujitegemea wenye Masharti ya Ugomvi (GARCH)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili2010s1986
MwanzilishiExtension of Nelson (1991) EGARCH using Fourier approximation frameworksTim Bollerslev
AinaVolatility model with smooth structural breaksConditional volatility model
Chanzo asiliaEnders, 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 ↗
Majina mbadalaFourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
Zinazohusiana35
MuhtasariFourier 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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ScholarGateLinganisha mbinu: Fourier EGARCH · GARCH. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare