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Received:March 16, 2013 Revised:May 17, 2013
Received:March 16, 2013 Revised:May 17, 2013
中文摘要: 将支持向量机方法应用于新股IPO首日价格变动的预测, 预测效果令人满意. 目前的股票价格预测研究都局限于通过已知的时间序列来预测将来的时间序列, 这类模型对于预测没有历史时间序列的新股IPO无能为力, 因此基于支持向量机的新股IPO价格预测模型对股票价格研究有着重要的参考价值.
Abstract:We use SVM to predict IPO stock price and achieve good result. There are different kinds of stock price forecasting models. But none of them can predict IPO stocks. So this paper has important reference value in stock price forecasting field.
keywords: stock price forecasting machine learning SVM
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| SHI Jian | School of Computer Science, Fudan University, Shanghai 201203, China |
| Author Name | Affiliation |
| SHI Jian | School of Computer Science, Fudan University, Shanghai 201203, China |
引用文本：
施剑.基于SVM的IPO首日投资策略分析.计算机系统应用,2013,22(10):206-209,158
SHI Jian.IPO Stock Price Forecasting Using Support Vector Machines.COMPUTER SYSTEMS APPLICATIONS,2013,22(10):206-209,158
施剑.基于SVM的IPO首日投资策略分析.计算机系统应用,2013,22(10):206-209,158
SHI Jian.IPO Stock Price Forecasting Using Support Vector Machines.COMPUTER SYSTEMS APPLICATIONS,2013,22(10):206-209,158
