COMEX铜期货长期波动率与动态相关性的宏观经济基本面研究
On the macroeconomic fundamentals of long-term volatilities and dynamic correlations in COMEX copper futures
AI总结：
本文利用GARCH-MIDAS和DCC-MIDAS模型，研究低频宏观变量对COMEX铜期货高频收益及与标普500长期相关性的影响，发现PPI是最有效的宏观变量，加入PPI的MIDAS滤波器可提升模型拟合效果。
摘要：
本文采用GARCH-MIDAS（广义自回归条件异方差-混频数据抽样）和DCC-MIDAS（动态条件相关-混频数据抽样）建模框架，考察低频宏观经济变量对铜期货高频收益的影响，以及其与标普500指数的长期相关性。GARCH-MIDAS的估计结果显示，已实现波动率（RV）、利率水平（IR）、工业生产（IP）、生产者价格指数（PPI）、收益率曲线斜率波动率、PPI波动率、消费者信心指数（CSI）以及美元指数（DI）均对铜期货收益有显著影响，其中PPI是效用最强的宏观经济变量。通过DCC-GARCH与DCC-MIDAS模型的对比可知，加入PPI的MIDAS滤波器提升了模型拟合度，且在影响铜期货与标普500指数的长期关系方面表现优于RV。
英文摘要：
This paper examines the influence of low-frequency macroeconomic variables on the high-frequency returns of copper futures and the long-term correlation with the S&P 500 index, employing GARCH-MIDAS and DCC-MIDAS modeling frameworks. The estimated results of GARCH-MIDAS show that realized volatility (RV), level of interest rates (IR), industrial production (IP) and producer price index (PPI), volatility of Slope, PPI, consumer sentiment index (CSI), and dollar index (DI) have significant impacts on Copper futures returns, among which PPI is the most efficient macroeconomic variable. From comparison among DCC-GARCH and DCC-MIDAS model, the added MIDAS filter of PPI improves the model fitness and have better performance than RV in effecting the long-run relationship between Copper futures and S&P 500.
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