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Modèle GARCH de Fourier×Test de Cointégration ARDL de Fourier×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine2000–20122001-2021
Auteur d'origineLudlow & Enders (2000); extended by Enders & Lee (2012) Fourier frameworkPesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
TypeVolatility modelCointegration / bounds test
Source fondatriceLudlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗Nazlioglu, S., Gormus, A., & Soytas, U. (2021). Oil prices and monetary policy in emerging markets: structural breaks, asymmetries, and Fourier approximations. Energy Economics, 95, 105119. link ↗
AliasFourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCHFourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test
Apparentées55
RésuméThe Fourier GARCH model embeds trigonometric Fourier terms into a standard GARCH framework to capture smooth, gradual shifts in the conditional variance process without requiring knowledge of exact structural break dates. By approximating unknown break patterns with sinusoidal functions, it jointly models volatility clustering and time-varying unconditional variance.The Fourier ARDL bounds test augments the Pesaran-Shin-Smith cointegration framework with trigonometric (Fourier) terms that capture gradual, smooth structural breaks in the data-generating process. It tests for a long-run level relationship between variables without requiring the researcher to specify the number, timing, or form of structural breaks in advance.
ScholarGateJeu de données
  1. v1
  2. 2 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Fourier GARCH Model · Fourier ARDL Bounds Test. Consulté le 2026-06-19 sur https://scholargate.app/fr/compare