摘要：The wavelet neural network has been widely applied in the forecasting field. However, due to its disadvantages of local minimal and slow convergence speed, its forecasting precision is limited in some extent. A forecasting model for stock index future price based on wavelet analysis and the improved PSO-based neural network would be put forward in this essay using the improved PSO-based algorithm to optimize the neural network. By using the Shanghai and Shenzhen 300 stock index futures’ statistics as the samples, the sym 8 wavelet transformation techniques to denoise the statistics and then use the denoised stats to train and test the improved PSO-based neural networks. The study results show that t he model in this essay could efficiently improve the forecasting quality of the stock index futures price.
关键词：Forecasting Model;Stock Index Future Price;Wavelet Analysis;PSO;Neural Networks
