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| 푸리에 DCC-GARCH 모형× | 푸리에 GARCH 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward | 2000–2012 |
| 창시자≠ | Engle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometrics | Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework |
| 유형≠ | Multivariate volatility model with smooth structural breaks | Volatility model |
| 원전≠ | Engle, R. (2002). Dynamic conditional correlations: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. link ↗ | Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347. DOI ↗ |
| 별칭 | Fourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCH | Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH |
| 관련 | 5 | 5 |
| 요약≠ | The Fourier DCC-GARCH model extends Engle's Dynamic Conditional Correlation GARCH framework by embedding Fourier trigonometric terms in the conditional mean or variance equations. This allows the model to approximate smooth, gradual structural shifts in volatility dynamics and inter-asset correlations without requiring knowledge of the number or timing of break points. | 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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