| 鲁棒SVR在金融时间序列预测中的应用 |
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| 引用本文： | 王快妮,钟萍,赵耀红.鲁棒SVR在金融时间序列预测中的应用[J].计算机工程,2011,37(15):155-157,163. |
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| 作者姓名： | 王快妮 钟萍 赵耀红 |
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| 作者单位： | 1. 石河子大学师范学院,新疆,石河子,832003
2. 中国农业大学理学院,北京,100083 |
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| 基金项目： | 国家自然科学基金，中国农业大学研究生科研创新专项基金 |
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| 摘 要： | 针对标准支持向量机对噪声和异常值比较敏感的问题,通过限定噪声和异常值的损失上界,提出一种基于不对称Ramp损失函数的鲁棒支持向量回归机模型,应用凹凸过程将其由非凸优化问题转化为凸优化问题并利用牛顿法进行求解.对上证指数和香港恒生指数收盘价的预测结果表明,该模型能在一定程度上抑制噪声和异常值的影响,从而提高预测精度及减少...
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| 关 键 词： | 支持向量机 时间序列 鲁棒性 不对称损失函数 牛顿法 |
| 收稿时间： | 2011-02-16 |
Application of Robust Support Vector Regression in Financial Time Sequence Prediction |
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| WANG Kuai-ni,ZHONG Ping,ZHAO Yao-hong.Application of Robust Support Vector Regression in Financial Time Sequence Prediction[J].Computer Engineering,2011,37(15):155-157,163. |
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| Authors: | WANG Kuai-ni ZHONG Ping ZHAO Yao-hong |
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| Affiliation: | 1.Normal College,Shihezi University,Shihezi 832003,China;2.College of Science,China Agricultural University,Beijing 100083,China) |
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| Abstract: | Aiming at the problem that standard Support Vector Machine（SVM） is sensitive to noise and oufliers, by setting the upper bound of loss caused by noise and outliers, this paper presents a robust Support Vector Regression（SVR） based on asymmetric ramp loss function. The concave-convex procedure is employed to transform the associated non-convex optimization problem into a convex one. A Newton method is introduced to solve the robust model. Numerical experiments on the closing price of Hong Kong＇s Hang Seng index and Shanghai Stock index show that the model can reduce the noise and the influence of the abnormal values to a certain extent, increase the prediction accuracy and reduce risk of falling to avoid risk. |
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| Keywords: | Support Vector Machine（SVM） time sequence robustness asymmetric loss function Newton method |
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