中文摘要：

以上证指数和深圳成分指数日收盘价的时间序列为样本，利用小波分析方法剔除序列的噪声干扰，对序列保留的波动趋势进行多重分形辨识．通过WTMM（小波变换模极大）计算配分函数，尺度函数和多重分形谱等，全面细致的量化了序列的局部及不同层次的波动奇异性．计算结果表明：去除噪声干扰后，中国现行证券市场的波动呈现显著的多重分形特征．

英文摘要：

The Shanghai Composite Index and Shenzhen Component Index on the closing price time series as a sample, using the wavelet analysis eliminate noise sequence, sequence to retain the fluctuations of the multifractal trends identified. By WTMM （wavelet transform modulus maxima） calculate the partition function, scaling function and multifractal spectra, a comprehensive and detailed quantification of the sequence of the fluctuations at different levels of local and singularity. The results show that： after the removal of noise, Chinese current stock market existing securities significant fluctuations in the market multifractal characteristics.