说明：  比较分析了传统滤波方法对金融数据去噪的缺陷 , 提出采用小波分析对金融时间序列进行去噪 。根 据 Donoho 提出的小波去噪中的非线性阈值理论 , 结合金融时间序列的特点 , 分析了相应去噪参数的选取问题 。 以深圳成份指数数据为例进行实验 , 结果表明了该方法的有效性
(This paper analyzes the shortcomings of traditional filtering methods in denoising financial data, and proposes the denoising of financial time series using wavelet analysis. According to Donoho s theory of nonlinear threshold in wavelet denoising and the characteristics of financial time series, the selection of corresponding denoising parameters is analyzed. Taking Shenzhen component index data as an example, the results show that the method is effective)