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مدل DCC-GARCH فوریه×مدل EGARCH (نمایی GARCH)×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward1991
پدیدآورEngle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometricsDaniel B. Nelson
نوعMultivariate volatility model with smooth structural breaksVolatility / conditional variance model
منبع بنیادینEngle, 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 ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
نام‌های دیگرFourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCHExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
مرتبط56
خلاصهThe 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 Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.
ScholarGateمجموعه‌داده
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  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Fourier DCC-GARCH · EGARCH model. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare