| 基于高斯核支持向量机的商品期货市场套利研究 |
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| 引用本文： | 邓亚东,王 波.基于高斯核支持向量机的商品期货市场套利研究[J].经济数学,2018(1):27-30. |
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| 作者姓名： | 邓亚东 王 波 |
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| 作者单位： | 上海理工大学管理学院 |
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| 摘 要： | 基于高斯RBF核支持向量机预测棉花商品期货主力和次主力合约协整关系的价差序列,确定最优SVM参数,并选择合适的开平仓阈值,进行同品种跨期套利.再与多项式核支持向量机套利结果对比,得到在所有开平仓阈值上,基于高斯RBF核支持向量机套利的收益率都明显高于多项式核支持向量机套利的收益率.
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| 关 键 词： | 机器学习 高斯核支持向量机 套利策略 |
Arbitrage Research of Commodity Futures Market Based on Gaussian Kernel Support Vector Machine |
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| DENG Yadong,WANG Bo.Arbitrage Research of Commodity Futures Market Based on Gaussian Kernel Support Vector Machine[J].Mathematics in Economics,2018(1):27-30. |
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| Authors: | DENG Yadong WANG Bo |
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| Institution: | (College of Management, University of Shanghai for Science and Technology, Shanghai 200093, China) |
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| Abstract: | To predict price difference sequence between cotton commodity futures based on Gaussian RBF kernel support vector machine, we determined the optimal SVM parameters, and chose the proper threshold. Compared with the polynomial kernel SVM arbitrage results obtained in all threshold, the Gaussian RBF kernel support vector machine arbitrage yields are significantly higher than the polynomial kernel support vector machine based on arbitrage yield. |
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| Keywords: | machine learning Gaussian kernel support vector machine arbitrage |
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