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نموذج بايزي للتقلب الشرطي الذاتي الانحداري×نموذج DCC-GARCH (الارتباط الشرطي الديناميكي)×
المجالالاقتصاد القياسيالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة1982 (ARCH); 1989 (Bayesian estimation)2002
صاحب الطريقةRobert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)Robert F. Engle
النوعVolatility model with Bayesian inferenceMultivariate volatility model
المصدر التأسيسيEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. 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 البديلةBayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
ذات صلة65
الملخصThe Bayesian ARCH model estimates Engle's Autoregressive Conditional Heteroskedasticity specification within a Bayesian framework. Instead of maximising a likelihood, it combines a prior distribution over the volatility parameters with the data likelihood to obtain a full posterior distribution, providing richer uncertainty quantification than classical maximum-likelihood ARCH.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: Bayesian ARCH model · DCC-GARCH model. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare