BP人工神经网络在股票预测中的应用

摘要

投资越大风险越大, 如何建立一个精确度和运算速度相对较高的股市预测模型对于金融投资者具有重大理论意义和实际应用价值.将人工神经网络应用到股票预测上面成为一个新的趋向.将用人工神经网络求解股票预测中的难题成分分析, 建立三层BP神经网络并且分析收敛速度, 得到当选择的数据合理且具有很好的性质时, 拟合效果会更加准确, 最终得到股票在短时间内的向.从而说明BP神经网络对于股票价格的预测具有可行性和合理性, 进而对提高股民的收益做出帮助.%The more invest, the more risk. This paper established a stock market prediction model with relatively high accuracy and speed of operation has great theoretical significance and practical application value for financial investors. It was a new trend to apply artificial neural network to stock forecasting. Used artificial neural network to solve the difficult problems in stock forecasting, established three-layer BP neural network and analyzed the convergence speed as well. The effect will be more accurate if the selected data were reasonable and have good properties. In this way, the direction of stock in a short time could be got.The results showed that BP neural network was feasible and reasonable for stock price prediction, and help shareholders to improve their earnings.