Regression modelEconometrics / time series
动态条件相关 (DCC-GARCH) 模型
由 Engle (2002) 提出的 DCC-GARCH 模型将单变量 GARCH 模型扩展到能够捕捉多个金融时间序列之间随时间变化的协方差。它将多元条件协方差矩阵分解为个体波动率过程和一个动态相关性矩阵,从而允许协方差随时间波动,同时即使在序列很多的情况下也保持计算上的可行性。
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来源
- 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: 10.1198/073500102288618487 ↗
- Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007. DOI: 10.2307/1912773 ↗
如何引用本页
ScholarGate. (2026, June 3). Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/zh/econometrics/dcc-garch-model
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- 向量自回归 (VAR)计量经济学↔ compare
被引用于
自回归条件异方差 (ARCH) 模型贝叶斯自回归条件异方差模型贝叶斯动态条件相关GARCH (Bayesian DCC-GARCH)贝叶斯阈值GARCH模型 (Bayesian TGARCH)EGARCH modelFourier DCC-GARCH 模型傅里叶 GARCH 模型傅里叶对称GARCH模型非线性 DCC-GARCH 模型(非对称动态条件相关性)非线性GARCH模型面板DCC-GARCH模型面板GARCH模型分位数-分位数(QQ)回归稳健动态条件相关GARCH (Robust DCC-GARCH)稳健 EGARCH 模型稳健TGARCH结构突变DCC-GARCH模型结构性断点EGARCH模型TGARCH 模型(阈值 GARCH)时变参数DCC-GARCH模型