Application of SVM in Financial Research

被引：3
|
作者：
Cao, Bingyu [1 ]
Zhan, Deping [1 ]
Wu, Xianbin [2 ]
机构：
[1] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha, Peoples R China
[2] Zhejiang Wanly Univ, Ningbo, Zhejiang, Peoples R China
来源：
INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL SCIENCES AND OPTIMIZATION, VOL 2, PROCEEDINGS | 2009年
关键词：
D O I：
10.1109/CSO.2009.313
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Based on the structural risk minimization, support vector machine is a new method of data mining. Since it has effectively solved complicated problems of classification and prediction, it has been widely used in many cross-disciplinary fields. This paper has reviewed and analyzed SVM's application to the classification and prediction in the financial field It has a promising future of applying to company's credit rating, early warning, stock prices forecast and so on. However, we hold that the correct selection of kernel and different sub-assembly function, as well as parameters, is the key point to optimize the application of SVM.
引用
收藏
页码：507 / +
页数：3
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