基于引入技术指标的Elman网络的股市预测

利用能够反映动态系统特性的Elman回归神经网络,结合传统的技术分析方法,通过对股票市场的技术指标的建模,寻求股票价格的变化规律,实现对股票价格的预测.实验结果表明,Elman网络具有较好的的逼近性能,能够实现对股票市场的预测.因此,引入技术指标的Elman神经网络用于股市预测是可行、有效的,具有很好的应用前景.

Stock Market Forecasting Based on Elman Neural Network with Technical Indexes

A model based on the Elman neural network, which can reflect the characteristics of the dynamic system is used to predict the prices at the stock market. Combined with the traditional technical and analytical methods, through the modeling for the technical indexes of the stock market, we have found the variational rules for the stock values. The results show that the Elman neuralnetwork has a preferable approaching property, which predicts the stock market well. It is proved that the Elman neural network combined with traditional technical and analytical methods is feasible and effective. It has a bright prospect in application.