قارن الطرق

	نموذج DCC-GARCH (الارتباط الشرطي الديناميكي)	نموذج EGARCH (نموذج التباين الشرطي المتغير الأسي)
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	2002	1991
صاحب الطريقة	Robert F. Engle	Daniel B. Nelson
النوع	Multivariate volatility model	Volatility / conditional variance model
المصدر التأسيسي	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.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
الأسماء البديلة	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
ذات صلة	5	6
الملخص	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.	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.