支持向量机在股票价格预测中的应用  

Application of Support Vector Machines in Stock Price Predicting

作　　者：张玉川[1] 张作泉[1] 

机构地区：[1]北京交通大学理学院,北京100044

出　　处：《北京交通大学学报》2007年第6期73-76,共4页JOURNAL OF BEIJING JIAOTONG UNIVERSITY

基　　金：国家自然科学基金资助项目(70471002)

摘　　要：综合在中国市场上流行的主要几种技术指标,应用支持向量机分类方法,对个股的价格涨跌进行预测分析.以当前几天的技术指标值为输入向量,若下一天的股价上涨则把该向量归为正类,若下跌则把它归为负类.先利用支持向量机对样本进行训练学习,建立一个分类模式,然后根据当天及前3天指标数据对明天股价进行预测,实证结果表明对个股的预测准确率都大于60%.Technical indicators are very important tools in the analysis of securities investment. In this paper, considering several main technical indicators prevailed in China security market, we predict whether the price of a stock rise or fall with the support vector machines （SVM）. We represent the technical indicators of the current four days as input vector. If the price of next day rise, we say the vector belongs to opposite set, if it fall, we say it belongs to negative set. Studying the samples, the SVM support vector machines construct a classification model. Then, based on the data of today and three days before, the SVM gives a prediction of tomorrow price. The experiment shows that the predicting accuracy are all greater than 60%.

关 键 词：个股价格 涨跌预测 支持向量机 技术指标 分类模式 

分 类 号：F830[经济管理—金融学]