Regression modelMixed-frequency correlation
DCC-MIDAS
DCC-MIDAS 结合了动态条件相关性 (DCC) GARCH 模型与混合频率数据采样 (MIDAS) 技术，能够估计不同频率观测值变量之间随时间变化的协方差。该模型由 Engle 等人 (2013) 提出，用于模拟协方差如何利用高频资产价格信息随低频宏观经济条件演变。这对于投资组合风险管理和理解宏观金融联系至关重要。
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来源
- Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock market volatility and macroeconomic fundamentals. Review of Economics and Statistics, 95(3), 776-797. DOI: 10.1162/rest_a_00300 ↗
- Colacito, R., Engle, R. F., & Ghysels, E. (2011). A component model for dynamic correlations. Journal of Econometrics, 164(1), 45-59. DOI: 10.1016/j.jeconom.2011.02.013 ↗
如何引用本页
ScholarGate. (2026, June 3). Dynamic Conditional Correlation MIDAS. ScholarGate. https://scholargate.app/zh/econometrics/dcc-midas
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 分量GARCH模型计量经济学↔ compare
- GARCH-MIDAS计量经济学↔ compare
- Quantile VAR计量经济学↔ compare