Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model
Since Professor L.A. Zadeh published “Fuzzy Set Theory” in the 1960s, the theory of fuzzy mathematics has been formally established and developed and has been gradually introduced into work in all walks of life. At the same time, fuzzy mathematics theory has also been widely used in VR industry sele...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Function Spaces |
| Online Access: | http://dx.doi.org/10.1155/2022/7556229 |
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| _version_ | 1849307456767787008 |
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| author | Jia-Ming Zhu Yu-Gan Geng Wen-Bo Li Xia Li Qi-Zhi He |
| author_facet | Jia-Ming Zhu Yu-Gan Geng Wen-Bo Li Xia Li Qi-Zhi He |
| author_sort | Jia-Ming Zhu |
| collection | DOAJ |
| description | Since Professor L.A. Zadeh published “Fuzzy Set Theory” in the 1960s, the theory of fuzzy mathematics has been formally established and developed and has been gradually introduced into work in all walks of life. At the same time, fuzzy mathematics theory has also been widely used in VR industry selection. In the stock strategy, the advantages of improving unit classification accuracy, screening high-quality stocks, and constructing near-perfect investment portfolios continue to emerge. On the other hand, with the increasing maturity and continuous development of China’s computer and Internet technologies, the VR industry has gained a new round of development space, and its own investment value and the investable space between related industries have been gradually tapped. Different from the analysis of quantitative stock selection by constructing a logistics multifactor stock selection model in the existing research, the research mainly adopts the random forest algorithm based on fuzzy mathematics to construct the initial investment strategy portfolio. Secondly, different from the single effective frontier algorithm, the research is based on the random forest algorithm, calculates the average AUC of the index, and continuously checks and tests the results to obtain the optimal investment portfolio. Finally, select appropriate risk indicators and performance indicators to evaluate the performance of the strategy portfolio. The study concludes that the portfolios selected by the random forest model are highly investable and have good stability. |
| format | Article |
| id | doaj-art-213bf1d2ce374d598b95c202350a66e0 |
| institution | Kabale University |
| issn | 2314-8888 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Function Spaces |
| spelling | doaj-art-213bf1d2ce374d598b95c202350a66e02025-08-20T03:54:47ZengWileyJournal of Function Spaces2314-88882022-01-01202210.1155/2022/7556229Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest ModelJia-Ming Zhu0Yu-Gan Geng1Wen-Bo Li2Xia Li3Qi-Zhi He4School of Statistics and Applied MathematicsSchool of FinanceSchool of FinanceSchool of FinanceSchool of Statistics and MathematicsSince Professor L.A. Zadeh published “Fuzzy Set Theory” in the 1960s, the theory of fuzzy mathematics has been formally established and developed and has been gradually introduced into work in all walks of life. At the same time, fuzzy mathematics theory has also been widely used in VR industry selection. In the stock strategy, the advantages of improving unit classification accuracy, screening high-quality stocks, and constructing near-perfect investment portfolios continue to emerge. On the other hand, with the increasing maturity and continuous development of China’s computer and Internet technologies, the VR industry has gained a new round of development space, and its own investment value and the investable space between related industries have been gradually tapped. Different from the analysis of quantitative stock selection by constructing a logistics multifactor stock selection model in the existing research, the research mainly adopts the random forest algorithm based on fuzzy mathematics to construct the initial investment strategy portfolio. Secondly, different from the single effective frontier algorithm, the research is based on the random forest algorithm, calculates the average AUC of the index, and continuously checks and tests the results to obtain the optimal investment portfolio. Finally, select appropriate risk indicators and performance indicators to evaluate the performance of the strategy portfolio. The study concludes that the portfolios selected by the random forest model are highly investable and have good stability.http://dx.doi.org/10.1155/2022/7556229 |
| spellingShingle | Jia-Ming Zhu Yu-Gan Geng Wen-Bo Li Xia Li Qi-Zhi He Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model Journal of Function Spaces |
| title | Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model |
| title_full | Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model |
| title_fullStr | Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model |
| title_full_unstemmed | Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model |
| title_short | Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model |
| title_sort | fuzzy decision making analysis of quantitative stock selection in vr industry based on random forest model |
| url | http://dx.doi.org/10.1155/2022/7556229 |
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