Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model
With the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-facto...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5588018 |
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| _version_ | 1849405002299211776 |
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| author | Li-Jun Liu Wei-Kang Shen Jia-Ming Zhu |
| author_facet | Li-Jun Liu Wei-Kang Shen Jia-Ming Zhu |
| author_sort | Li-Jun Liu |
| collection | DOAJ |
| description | With the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-factor model and then analyzes them by using the higher-order moment model to find that different investors’ preferences will make the weight of the portfolio change accordingly, which will eventually make the optimal return and risk set of the composition of the portfolio change. The risk identification system designed in this paper can provide an effective risk identification tool for investors and help them make rational judgments. |
| format | Article |
| id | doaj-art-4907dc381ff1479488bdcb752310dd95 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-4907dc381ff1479488bdcb752310dd952025-08-20T03:36:47ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55880185588018Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment ModelLi-Jun Liu0Wei-Kang Shen1Jia-Ming Zhu2School of Economics, Hebei GEO University, Shijiazhuang 050031, ChinaSchool of Economics, Hebei GEO University, Shijiazhuang 050031, ChinaInstitute of Quantitative Economics, Anhui University of Finance and Economics, Bengbu 233030, ChinaWith the continuous development of the stock market, designing a reasonable risk identification tool will help to solve the irrational problem of investors. This paper first selects the stocks with the most valuable investment value in the future through the random forest algorithm in the nine-factor model and then analyzes them by using the higher-order moment model to find that different investors’ preferences will make the weight of the portfolio change accordingly, which will eventually make the optimal return and risk set of the composition of the portfolio change. The risk identification system designed in this paper can provide an effective risk identification tool for investors and help them make rational judgments.http://dx.doi.org/10.1155/2021/5588018 |
| spellingShingle | Li-Jun Liu Wei-Kang Shen Jia-Ming Zhu Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model Complexity |
| title | Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model |
| title_full | Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model |
| title_fullStr | Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model |
| title_full_unstemmed | Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model |
| title_short | Research on Risk Identification System Based on Random Forest Algorithm-High-Order Moment Model |
| title_sort | research on risk identification system based on random forest algorithm high order moment model |
| url | http://dx.doi.org/10.1155/2021/5588018 |
| work_keys_str_mv | AT lijunliu researchonriskidentificationsystembasedonrandomforestalgorithmhighordermomentmodel AT weikangshen researchonriskidentificationsystembasedonrandomforestalgorithmhighordermomentmodel AT jiamingzhu researchonriskidentificationsystembasedonrandomforestalgorithmhighordermomentmodel |