Special Treatment Prediction on Chinas listed Stocks Using Gradient Boosting

摘要：

We apply Gradient Boosting to examine whether stocks will be special treated, a problem that is concerned with both stock issuers and investors. Gradient Boosting is an effective yet rarely used method for financial crisis prediction. The results show that when compared with SVM, the prediction accuracy of Gradient Boosting is 90％ higher one year prior to special treatment.

关键词： Special Treatment Gradient Boosting SVM

作者: Xiaoxu Wang Zhengming Qian Yun Luo

作者单位: School of Economics, Xiamen University, Xiamen, P.R. of China School of Economics, Xiamen University,Xiamen, P.R. of China

会议类型: 国际会议

会议名称: The 5th International Conference on Cooperation and Promotion of Information Resources in Science and Technology(第五届科技信息资源共享促进国际会议COINFO10)

会议地点: 北京

会议语种:英文

页码: 296-301

在线出版日期: 2010-11-27（万方平台首次上网日期，不代表论文的发表时间）