摘要
针对股票时间序列的非线性特点,结合混沌理论和神经网络理论,提出了基于混沌理论的股票价格神经网络预测方法。同时利用重构相空间的嵌入维数确定神经网络的结构,对实际的股票时间序列预测结果表明,该方法能有效地进行短期预测,在股票时间序列预测中有广泛的实用价值。
A method of stock price prediction based on chaos theory is presented by hypothesis of stock time series being non-linear and by taking advantages of BP neural network and chaos theory. Mean- while, structures of neural network are determined by embedding dimension of phase space reconstruct. Predicting results for practical stock time series show that the method is able to do short-term prediction effectively, thus it can be widely used in stock time series prediction.
出处
《系统仿真技术》
2008年第4期228-232,246,共6页
System Simulation Technology
基金
湖南省高等学校科学研究资助项目(08C249)
关键词
混沌时间序列
股票价格
神经网络
预测
chaotic time series
stock price
neural network
prediction