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نموذج TGARCH القوي×نموذج ARCH القوي×
المجالالاقتصاد القياسيالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة1994–2000s2002–2008
صاحب الطريقةZakoian (1994) for TGARCH; robust extensions developed through quasi-maximum likelihood and M-estimation literatureEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s
النوعVolatility model with asymmetry and robust estimationVolatility / conditional heteroscedasticity model
المصدر التأسيسيZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
الأسماء البديلةrobust GJR-GARCH, robust threshold GARCH, heavy-tail TGARCH, outlier-robust TGARCHrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model
ذات صلة66
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 Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time 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 · Robust ARCH model. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare