小波神经网络在股票平均线交易规则中的应用

股票市场是一个复杂的非线性动态系统，利用传统的时间序列预测技术很难揭示其内在规律，而近十几年来发展起来的神经网络理论逐渐成为非线性动态系统预测与建模的强有力工其。该文介绍了小波分析中的趋势提取技术，建立小波分析与神经网络相结合的预测模型，将该模型应用于股票平均线交易规则中，同时还与普通神经网络预测模型进行厂对比，研究实例表明，小波神经网络方法提高了预测精度，对移动平均线交易规则作了一种有效的补允，是股市技术分析的一种自效实用的方法。

Application of Wavelet Neural Network in Stock Trade Rule of Average Line

Stock market is a complex non- linear dynamic system and it is very difficult to develop the inherent rules using the traditional timing prediction technology. In recent decade or so, neural network is becoming the most powerful tool for predicting non - linear dynamic system. This paper introduces the technology of drawing trend of wavelet analysis , sets up a modeI combined by the wavelet analysis and neural network, and applies it to the stock trade rule of average line. At the same time, a contrast with the ordinary neural network model is made. The simulation shows that wavelet neural network improves the precision of prediction and makes a supplement to the stock trade rule of average line, It is an effective and practical way for analysing the stock market.