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| Fourier EGARCH: Modelowanie zmienności z płynnymi zmianami strukturalnymi× | Uogólniona warunkowa heteroskedastyczność z autoregresją (GARCH)× | |
|---|---|---|
| Dziedzina | Ekonometria | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2010s | 1986 |
| Twórca≠ | Extension of Nelson (1991) EGARCH using Fourier approximation frameworks | Tim Bollerslev |
| Typ≠ | Volatility model with smooth structural breaks | Conditional volatility model |
| Źródło pierwotne≠ | 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 ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ |
| Inne nazwy | Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli |
| Pokrewne≠ | 3 | 5 |
| Podsumowanie≠ | 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. | 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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