基于小波与混沌集成的中国股票市场预测

应用小波变换和混沌理论提出了一种中国股票市场建模及其预测的小波与混沌集成的方法．首先应用小波分解理论对上证综指和深证成指日收益率序列进行分解，分别得到低频部分和高频部分，并在此基础上作进一步分析，结果表明中国股市存在混沌特性；然后应用混沌理论分别建立低频部分和高频部分的预测模型，对低频部分和高频部分进行预测；最后应用小波理论对混沌模型预测的结果予以重构，实现对原始收益率序列的预测．与现有方法比较，结果表明该方法具有较高的精度，有极大的应用前景．

Wavelet-chaotic integration-based forecasting of China stock market

Following wavelet transformation and chaos theory, a method is proposed to model and forecast stock market. First, using wavelet decomposition theory, Shanghai composite index (SCI) and Shenzhen sub_index (SSI) daily gain rate series are decomposed respectively into two parts: low frequency part and high frequency part and the further analysis of decomposition indicates that China stock market exists a chaos feature. Then, by using chaos theory, the chaotic forecasting models are established to forecast the low frequency part and the high frequency part respectively. Finally, the forecasting result of chaotic model is reconstructed by wavelet theory. By doing so, the forecasting of the original SCI and SSI daily gain rate series can be made. Our result demonstrates that the method is of high precision and wide potential applications.