| 基于LPRE和LASSO方法的股指追踪研究 |
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| 引用本文： | 陈银钧,刘惠篮.基于LPRE和LASSO方法的股指追踪研究[J].经济数学,2020,37(1):92-96. |
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| 作者姓名： | 陈银钧 刘惠篮 |
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| 作者单位： | 贵州大学 数学与统计学院,贵州 贵阳 550025;贵州大学 数学与统计学院,贵州 贵阳 550025 |
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| 基金项目： | 贵州省科技计划;国家自然科学基金;贵州省教育厅青年科技人才成长项目 |
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| 摘 要： | 将最小化乘积相对误差(LPRE)和最小绝对压缩选择算子(LASSO)方法应用到乘积回归模型,结合BIC信息准则实现股票指数的追踪,成功选取了26支对上证50指数影响较大的成分股,并比较了所提方法与线性模型下LASSO方法的表现,验证了所提方法的有效性.
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| 关 键 词： | 乘积模型 LPRE方法 LASSO估计 BIC准则 |
Research on Stock Index Tracking Based on LPRE and LASSO Methods |
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| CHEN Yinjun,LIU Huilan.Research on Stock Index Tracking Based on LPRE and LASSO Methods[J].Mathematics in Economics,2020,37(1):92-96. |
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| Authors: | CHEN Yinjun LIU Huilan |
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| Institution: | (School of Mathematics and Statistics,Guizhou University,Guiyang,Guizhou 550025,China) |
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| Abstract: | Because the stock price is non-negative data, the multiplicative regression model can be applied to such data. The LPRE and LASSO method are applied to the multiplicative regression model for tracking the stock index. And the BIC information criterion is used to select the penalty parameters. 26 constituent stocks of Shanghai 50 Index are successfully selected. The performance of LASSO method in linear model is compared with our method, which verifies the effectiveness of the proposed method. |
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| Keywords: | multiplicative regression model LPRE method LASSO method BIC criterion |
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