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| Fourier EGARCH: Моделиране на волатилността с плавни структурни промени× | Обобщена авторегресионна условна хетероскедастичност (GARCH)× | GJR-GARCH (Асиметричен GARCH)× | |
|---|---|---|---|
| Област | Иконометрия | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model | Regression model |
| Година на възникване≠ | 2010s | 1986 | 1993 |
| Създател≠ | Extension of Nelson (1991) EGARCH using Fourier approximation frameworks | Tim Bollerslev | Glosten, Jagannathan & Runkle (1993); Zakoian (1994) |
| Тип≠ | Volatility model with smooth structural breaks | Conditional volatility model | Asymmetric conditional volatility model |
| Основополагащ източник≠ | 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 ↗ | 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 ↗ |
| Други названия | Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli | asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle) |
| Свързани≠ | 3 | 5 | 5 |
| Резюме≠ | 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. | 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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