Research on Stock Price Prediction Based on BP Wavelet Neural Network with Mexico Hat Wavelet Basis

In order to improve the prediction ability of stock price, a prediction method based on Wavelet Neural Network (WNN) is proposed. First BP algorithm is used to optimize the parameters of WNN with Mexico Hat wavelet basis for the establishment of the stock price prediction model, and then the built model is applied to predict the stock price movement on the basis of 15 features. The simulations on daily closing price index of SSE Composite Index indicate that, the proposed method has the advantages of simple structure, strong implementation and good prediction accuracy, and gets better stock price prediction in contrast with single neural network and genetic neural network. This verifies the feasibility and effectiveness of the method in the application of stock price prediction.