混沌理论在股票价格预测中的应用

The Application of Chaos Theory to Stock Price Forecasting

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.