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نموذج TGARCH القوي×نموذج DCC-GARCH (الارتباط الشرطي الديناميكي)×
المجالالاقتصاد القياسيالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة1994–2000s2002
صاحب الطريقةZakoian (1994) for TGARCH; robust extensions developed through quasi-maximum likelihood and M-estimation literatureRobert F. Engle
النوعVolatility model with asymmetry and robust estimationMultivariate volatility model
المصدر التأسيسيZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗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. DOI ↗
الأسماء البديلةrobust GJR-GARCH, robust threshold GARCH, heavy-tail TGARCH, outlier-robust TGARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
ذات صلة65
الملخصRobust TGARCH extends the Threshold GARCH model by replacing the conventional maximum likelihood objective with an estimator that is resistant to heavy-tailed innovations and outlying observations. It captures asymmetric volatility responses — where negative shocks amplify variance more than positive shocks — while remaining reliable when the return distribution deviates strongly from normality.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.
ScholarGateمجموعة البيانات
  1. v1
  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Robust TGARCH · DCC-GARCH model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare