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| 푸리에 DCC-GARCH 모형× | Vector Autoregression (VAR)× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward | 1980 |
| 창시자≠ | Engle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometrics | Christopher A. Sims |
| 유형≠ | Multivariate volatility model with smooth structural breaks | Multivariate time-series 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 ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| 별칭 | Fourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCH | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| 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. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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