基于SVM的股票时间序列的预测研究  

The Stock Market Forecast System Based on SVM

作　　者：吕琦[1] 

机构地区：[1]华北水利水电学院管理与经济学院,河南郑州450011

出　　处：《吉林工程技术师范学院学报》2011年第7期48-49,共2页Journal of Jilin Engineering Normal University

摘　　要：支持向量机(support vector machine,SVM)是以统计学理论为基础的一种新的模式识别方法,目前已广泛应用于股票价格的预测中。在股市投资问题的研究中,股价作为时间序列数据是复杂的、非线性的,并且极不稳定。文章将支持向量机引入到股价预测的建模中,并对效果进行了分析。SVM is a new type of machine learning method which was developed,and a new data mining method based on the statistical learning theory.It has been widely used in forecasting the stock price,which has become a hotspot in the international machine learning field.With the traditional timing prediction technique,it is very difficult to open out its inherent rules.In order to improve the pattern analysis of the stock market price based on SVM theory,this paper puts forward a new method using SVM to forecast the stock price.

关 键 词：支持向量机 SVM 股票价格预测 

分 类 号：F830.91[经济管理—金融学]