مقایسهٔ روشها
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| مدل فوریر گارچ (Fourier GARCH)× | مدل DCC-GARCH (Dynamic Conditional Correlation)× | |
|---|---|---|
| حوزه | اقتصادسنجی | اقتصادسنجی |
| خانواده | Regression model | Regression model |
| سال پیدایش≠ | 2000–2012 | 2002 |
| پدیدآور≠ | Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework | Robert F. Engle |
| نوع≠ | Volatility model | Multivariate volatility model |
| منبع بنیادین≠ | Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ |
| نامهای دیگر | Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH | DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC |
| مرتبط | 5 | 5 |
| خلاصه≠ | 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 DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series. |
| ScholarGateمجموعهداده ↗ |
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