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Fourier EGARCH: スムーズな構造変化を伴うボラティリティモデリング×GJR-GARCH(非対称GARCH)×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年2010s1993
提唱者Extension of Nelson (1991) EGARCH using Fourier approximation frameworksGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
種類Volatility model with smooth structural breaksAsymmetric conditional volatility model
原典Enders, 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 ↗
別名Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCHasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
関連35
概要Fourier 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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ScholarGate手法を比較: Fourier EGARCH · GJR-GARCH. 2026-06-19に以下より取得 https://scholargate.app/ja/compare