Порівняння методів

	Модель Фур'є-GARCH	Модель DCC-GARCH (динамічна умовна кореляція)
Галузь	Економетрика	Економетрика
Родина	Regression model	Regression model
Рік появи	2000–2012	2002
Автор методу	Ludlow & Enders (2000); extended by Enders & Lee (2012) Fourier framework	Robert F. Engle
Тип	Volatility model	Multivariate volatility model
Основоположне джерело	Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16(3), 333–347.	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.
Інші назви	Fourier GARCH, Fourier-flexible GARCH, GARCH with Fourier terms, smooth-break GARCH	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Пов'язані	5	5
Підсумок	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.