股票市场超高频数据具有交易间隔随机性的特点,传统的皮尔逊相关性度量不能够直接使用原始交易数据,需要通过插值得到均匀、同步的抽样序列.傅里叶分析法不需要对原始数据进行插值,能更精确地度量时间序列的相关性.将傅里叶分析法用于我国金融市场股票收益率的相关性分析中,对皮尔逊相关分析和傅里叶分析法的度量效果进行了比较. The UHF data in the stock market are characterized by the randomness of transaction intervals. The traditional Pearson correlation measure can not directly use the original transaction data, and needs to be interpolated to obtain a uniform and synchronous sampling sequence. Fourier analysis does not require the original data The interpolation can accurately measure the correlation of time series.The Fourier analysis method is used in the correlation analysis of the return of the stock market in our country’s financial market.The measurement results of Pearson correlation analysis and Fourier analysis Compare