Factor Investment or Feature Selection Analysis?
This study has made significant findings in A-share market data processing and portfolio management. Firstly, by adopting the Lasso method and CPCA framework, we effectively addressed the problem of multicollinearity among feature indicators, with the Lasso method demonstrating superior performance...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/1/9 |
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| _version_ | 1841549177385910272 |
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| author | Jifang Mai Shaohua Zhang Haiqing Zhao Lijun Pan |
| author_facet | Jifang Mai Shaohua Zhang Haiqing Zhao Lijun Pan |
| author_sort | Jifang Mai |
| collection | DOAJ |
| description | This study has made significant findings in A-share market data processing and portfolio management. Firstly, by adopting the Lasso method and CPCA framework, we effectively addressed the problem of multicollinearity among feature indicators, with the Lasso method demonstrating superior performance in handling this issue, thus providing a new method for financial data processing. Secondly, Deep Feedforward Neural Networks (DFN) exhibited exceptional performance in portfolio management, significantly outperforming other evaluated machine learning methods, and achieving high levels of out-of-sample performance and Sharpe ratios. Additionally, we consistently identified price changes, earnings per share, net assets per share, and excess returns as key factors influencing predictive signals. Finally, this study combined the Lasso method with DFN, providing a new perspective and methodological support for asset pricing measurement in the financial field. |
| format | Article |
| id | doaj-art-caca5578c0b845ff93e2a772015e3e99 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-caca5578c0b845ff93e2a772015e3e992025-01-10T13:17:57ZengMDPI AGMathematics2227-73902024-12-01131910.3390/math13010009Factor Investment or Feature Selection Analysis?Jifang Mai0Shaohua Zhang1Haiqing Zhao2Lijun Pan3School of Economics, Jinan University, Guangzhou 510632, ChinaSchool of Economics and Statistics, Guangzhou University, Guangzhou 510006, ChinaSchool of Mathematics and Statistics, Lingnan Normal University, Zhanjiang 524033, ChinaSchool of Mathematics and Statistics, Lingnan Normal University, Zhanjiang 524033, ChinaThis study has made significant findings in A-share market data processing and portfolio management. Firstly, by adopting the Lasso method and CPCA framework, we effectively addressed the problem of multicollinearity among feature indicators, with the Lasso method demonstrating superior performance in handling this issue, thus providing a new method for financial data processing. Secondly, Deep Feedforward Neural Networks (DFN) exhibited exceptional performance in portfolio management, significantly outperforming other evaluated machine learning methods, and achieving high levels of out-of-sample performance and Sharpe ratios. Additionally, we consistently identified price changes, earnings per share, net assets per share, and excess returns as key factors influencing predictive signals. Finally, this study combined the Lasso method with DFN, providing a new perspective and methodological support for asset pricing measurement in the financial field.https://www.mdpi.com/2227-7390/13/1/9machine learningmulticollinearityCPCA frameworklasso method |
| spellingShingle | Jifang Mai Shaohua Zhang Haiqing Zhao Lijun Pan Factor Investment or Feature Selection Analysis? Mathematics machine learning multicollinearity CPCA framework lasso method |
| title | Factor Investment or Feature Selection Analysis? |
| title_full | Factor Investment or Feature Selection Analysis? |
| title_fullStr | Factor Investment or Feature Selection Analysis? |
| title_full_unstemmed | Factor Investment or Feature Selection Analysis? |
| title_short | Factor Investment or Feature Selection Analysis? |
| title_sort | factor investment or feature selection analysis |
| topic | machine learning multicollinearity CPCA framework lasso method |
| url | https://www.mdpi.com/2227-7390/13/1/9 |
| work_keys_str_mv | AT jifangmai factorinvestmentorfeatureselectionanalysis AT shaohuazhang factorinvestmentorfeatureselectionanalysis AT haiqingzhao factorinvestmentorfeatureselectionanalysis AT lijunpan factorinvestmentorfeatureselectionanalysis |