On the macroeconomic fundamentals of long-term volatilities and dynamic correlations in COMEX copper futures

Zian Wang, Xinshu Li
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Abstract

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.
论 COMEX 铜期货长期波动率和动态相关性的宏观经济基本要素
本文采用 GARCH-MIDAS 和 DCC-MIDAS 模型框架,研究了低频宏观经济变量对铜期货高频回报率的影响,以及铜期货与标准普尔 500 指数的长期相关性。GARCH-MIDAS的估计结果表明,已实现波动率(RV)、利率水平(IR)、工业生产(IP)和生产者价格指数(PPI)、斜率波动率、PPI、消费者情绪指数(CSI)和美元指数(DI)对期铜收益率有显著影响,其中PPI是最有效的宏观经济变量。从 DCC-GARCH 模型和 DCC-MIDAS 模型的比较来看,添加 PPI 的 MIDAS 滤波提高了模型的拟合度,在影响铜期货和标准普尔 500 指数的长期关系方面比 RV 有更好的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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