The forecasting of stock price affects directly the decisions and immediate economic interests of investors. So the demand for accurate forecasting is high.
对股票价格的预测直接影响到投资者的投资决策，关系到投资者的切身经济利益，因而对预测的准确性要求较高。
As a result, constructing the model of combined forecasting to predict the fluctuation of stock price has a theoretical value and a strong guidance.
因此，构建组合预测模型来预测证券价格的波动，既具有一定的理论价值又具有较强的现实指导意义。
A phase space reconstructed forecasting method of stock price was proposed based on least squares support vector machines (LS-SVM).
提出一种基于相空间重构的最小二乘支持向量机(LS - SVM)的股票价格预测方法。
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