中文摘要：

为了顺应股市价值回归趋势和引导理性投资，在价值投资理论指导下，采用PCA—SVM方法建立了基于价值投资的股票选择模型．根据股票的价值特征集，采用主成分分析方法实现对股票价值特征的提取．采用多组不同的训练样本对支持向量机进行训练，并对训练成功的支持向量机进行样本内和样本外测试．利用该股票选择模型对上证180指数的成分股票进行识别．结果证明PCA-SVM股票选择模型具有良好的选股能力．

英文摘要：

In order to accommodate the value regression trends of the stock market and guide rational investment, under the guidance of the value investment theory, the stock option model based on value investment is set up by PCA-SVM method. In accordance with the characteristics set of the shares value, the principal component analysis is used to realize the extraction of the characteristics of the shares value. Then multiple sets of different training samples are adopted to train support vector machines and tested inside and outside the samples if they were success. The Shanghai＇s 180 index component stocks are identified by this model. The finding is that the PCA- SVM stock option model has a good stock picking ability.