Abstract: A novel forecasting model of petroleum futures price based on Least Squared Support Vector Machine（LS-SVM） is proposed.The experiment on the prediction of 2 kinds of daily petroleum futures price recorded in New York Mercantile Exchange（NYMEX） is carried out.RBF neural network prediction method is also applied to petroleum futures price time series.The results indicate that the best precision of fitting and forecasting can be obtained with LS-SVM prediction model，and LS-SVM prediction model outperforms RBF network prediction model.

Key words: petroleum futures, prediction, time series, Least Squared Support Vector Machine（LS-SVM）

摘要： 建立了基于最小二乘支持向量机的石油期货价格预测模型。应用该模型对纽约商品交易市场的两种石油期货价格数据进行了预测，并将预测结果与RBF神经网络的预测结果进行了比较。研究结果表明最小二乘支持向量机预测模型具有较高的拟合和预测精度，明显优于RBF神经网络预测模型。

关键词: 石油期货, 预测, 时间序列, 最小二乘支持向量机