灰色神经网络在股价预测中的应用研究

股票价格受多种因素的综合影响，具有趋势性、较大波动性和随机性等变化特点，单一模型难准确对其变化规律进行准确描述，将灰色理论和BP神经网络相结合构建一种股票价格组合预测模型。采用灰色GM（1，1）预测模型动态预测股票价格变化趋势，运用BP神经网络对灰色GM（1，1）模型预测结果进行修正，以提高股票价格预测精度。采用ST东北高（600003）股票价格对预测模型性能进行测试，结果表明，组合预测模型提高了股票价格的预测精度，更能挖掘股票价格变化规律。

Application of grey model and neural network in stock prediction

The stock price is influenced by many factors. The change has tendency, large fluctuation and stochastic characteristics. This paper proposes a stock price prediction model based on gray theory and BP neural network. The stock price based changes are simulated by the grey GM（1，1） prediction model, and the grey GM（1，1） model prediction results are modified by BP neural network to improve the prediction precision of the stock price. The model performance is tested by 60 000 stock prices. The results show that the proposed model can greatly improve the prediction precision of the stock price; it can mine the stock price changes.