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作 者:郭燊 周石鹏[1] GUO Shen;ZHOU Shipeng(School of Management,University of Shanghai for Science and Technology,Shanghai 200093,China)
机构地区:[1]上海理工大学管理学院
出 处:《经济数学》2019年第4期14-19,共6页Journal of Quantitative Economics
摘 要:在传统主成分分析的基础上,复数希尔伯特主成分分析通过将希尔伯特变换与随机矩阵理论相结合获取滤噪经济数据的频域信息,为揭示股票市场与货币市场波动的超前滞后关系提供了途径.实证研究结果显示,在样本区间内,中国股票市场指标相对于货币市场指标来说大部分呈现出超前的变化,而在货币市场中,数量型指标波动较为靠前,价格型指标的反应则较为滞后.此外,股票价格与货币供应量的波动之间存在反馈效应.探索两市场间这样一种动态关系能为政府对金融市场的监管工作提供相应的政策建议.Based on the traditional principal component analysis,the complex Hilbert principal component analysis method combines Hilbert transform with random matrix theory to obtain the frequency domain information of denoising economic data,which provides a way to reveal the lead-lag relationship between stock market and money market volatility.Empirical results show that,in the sample interval,the most of the stock market indicators in China's show advanced changes compared with the monetary market indicators,while in the money market,the quantitative indicators change earlier and the price indicators lag behind.In addition,there exist feedback effects between money fluctuation and stock price fluctuation.By exploring such a dynamic relationship between stock market and monetary,this paper can provide the government with the corresponding policy recommendations for the supervision of financial markets.
关 键 词:货币市场 股票市场 复数希尔伯特主成分分析 随机矩阵理论
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