Salīdzināt metodes
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| Modelis "Fourier TGARCH"× | Furjē GARCH modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1994 / 2012 | 2000–2012 |
| Autors≠ | Zakoian (1994) for TGARCH; Enders and Lee (2012) for Fourier approximation framework | Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework |
| Tips≠ | Volatility model with asymmetric leverage and Fourier smooth breaks | Volatility model |
| Pirmavots≠ | Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. DOI ↗ | Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗ |
| Citi nosaukumi | Fourier TGARCH, Fourier Threshold GARCH, Fourier GJR-GARCH, smooth structural break TGARCH | Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Fourier TGARCH model extends the Threshold GARCH framework by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual structural breaks in volatility dynamics. It jointly models asymmetric leverage effects — where negative shocks amplify volatility more than positive shocks of the same magnitude — and time-varying intercept shifts caused by unobserved structural change. | 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. |
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