Stock Market Forecasting Based on Neural Network

摘要：

This paper is based on the stock forecast, quantizes the part of stocks effect factors and syncretizes to the technologically analytical method in traditional securities, to filter the input variables by Data Mining algorithm, and use the updated BPNN algorithm which is LM algorithm to set up a model to forecast and emulational Shanghai stock composite index. The results show that BPNN can efficiently forecast the stock market, and has feasibility.

关键词： Neural Network Stock Forecasting Data Mining

作者: Zhou Shaofu Xu Yang

作者单位: School of economics,huazhong university of science and techonology

会议类型: 国际会议

会议名称: 2008年国际应用统计学术研讨会(2008 International Institute of Applied Statistics Studies)

会议地点: 烟台

会议语种:英文

页码: 1-6

在线出版日期: 2008-08-14（万方平台首次上网日期，不代表论文的发表时间）