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| Fourier-GARCH-Modell× | Fourier-ARDL-Bounds-Test (Fourier ARDL Bounds Test)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2000–2012 | 2001-2021 |
| Urheber≠ | Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework | Pesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors |
| Typ≠ | Volatility model | Cointegration / bounds test |
| Wegweisende Quelle≠ | Ludlow, 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 ↗ |
| Aliasnamen | Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH | Fourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | The 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. |
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