Applied Research on Stock Forcasting Model Based on BP neural network
making use of the function approximation and selflearning of BP neural network, we analyze the historical data in Shanghai Stock between June 2006 and November 2009, construct a stock forecasting model based on BP neural network, and verify the model through some test samples. Finally, we can use the Robust model to forcast the short-term stock. Matiab simulation experiments indicate that the model is feasible and effective in short-term stock forcasting.
BP neural network function approximability stock forcasting
Yue Ma Yu Chang Chunyu Xia
College of Management Northwestern Polytechnical University xian 710129, China
国际会议
哈尔滨
英文
4578-4580
2011-08-12(万方平台首次上网日期,不代表论文的发表时间)