基于支持向量机的沪深300指数预测研究

基于沪深300股指时间序列的特点,提出了一种基于主成分分析和支持向量机相结合的方法,将影响沪深300股指的各个因子通过主成分法进行信息的提取,然后用支持向量回归机进行学习预测.最后通过比较预测值与真实值,发现所预测的10个时段的收盘价均方误差为2.11617,且由预测值和真实值对比的条形图发现预测趋势基本准确,可见运用支持向量机对沪深300指数进行预测是可行的.

Support vector machines-based forecasting in Shanghai and Shenzheng 300 index

Based on the characteristic of the time series of Shanghai and Shenzhen 300 index,proposed a method which based on combination of Principal Component Analysis(PCA) and Support Vector Machine(SVM).Firstly,extract the main information of the factors which influence Shanghai and Shenzhen 300 index through PCA,then SVM to train and forecast.Finally,in order to compare predicted value and true value,we calculate the Mean Square Error(MSE) of the predicted closing price in ten time periods,which is 2.11617.Moreov...