Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique
In this research, a novel approach called SMOTE-FRS is proposed for movement prediction and trading simulation of the Chinese Stock Index 300 (CSI300) futures, which is the most crucial financial futures in the Chinese A-share market. First, the SMOTE- (Synthetic Minority Oversampling Technique-) ba...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2022/7622906 |
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| _version_ | 1832561616741203968 |
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| author | Shangkun Deng Yingke Zhu Ruijie Liu Wanyu Xu |
| author_facet | Shangkun Deng Yingke Zhu Ruijie Liu Wanyu Xu |
| author_sort | Shangkun Deng |
| collection | DOAJ |
| description | In this research, a novel approach called SMOTE-FRS is proposed for movement prediction and trading simulation of the Chinese Stock Index 300 (CSI300) futures, which is the most crucial financial futures in the Chinese A-share market. First, the SMOTE- (Synthetic Minority Oversampling Technique-) based method is employed to address the sample unbalance problem by oversampling the minority class and undersampling the majority class of the futures price change. Then, the FRS- (fuzzy rough set-) based method, as an efficient tool for analyzing complex and nonlinear information with high noise and uncertainty of financial time series, is adopted for the price change multiclassification of the CSI300 futures. Next, based on the multiclassification results of the futures price movement, a trading strategy is developed to execute a one-year simulated trading for an out-of-sample test of the trained model. From the experimental results, it is found that the proposed method averagely yielded an accumulated return of 6.36%, a F1-measure of 65.94%, and a hit ratio of 62.39% in the four testing periods, indicating that the proposed method is more accurate and more profitable than the benchmarks. Therefore, the proposed method could be applied by the market participants as an alternative prediction and trading system to forecast and trade in the Chinese financial futures market. |
| format | Article |
| id | doaj-art-19b579625ab646b1a7eab9a59e217949 |
| institution | Kabale University |
| issn | 1687-9139 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-19b579625ab646b1a7eab9a59e2179492025-02-03T01:24:36ZengWileyAdvances in Mathematical Physics1687-91392022-01-01202210.1155/2022/7622906Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling TechniqueShangkun Deng0Yingke Zhu1Ruijie Liu2Wanyu Xu3College of Economics and ManagementCollege of Economics and ManagementCollege of Economics and ManagementCollege of Economics and ManagementIn this research, a novel approach called SMOTE-FRS is proposed for movement prediction and trading simulation of the Chinese Stock Index 300 (CSI300) futures, which is the most crucial financial futures in the Chinese A-share market. First, the SMOTE- (Synthetic Minority Oversampling Technique-) based method is employed to address the sample unbalance problem by oversampling the minority class and undersampling the majority class of the futures price change. Then, the FRS- (fuzzy rough set-) based method, as an efficient tool for analyzing complex and nonlinear information with high noise and uncertainty of financial time series, is adopted for the price change multiclassification of the CSI300 futures. Next, based on the multiclassification results of the futures price movement, a trading strategy is developed to execute a one-year simulated trading for an out-of-sample test of the trained model. From the experimental results, it is found that the proposed method averagely yielded an accumulated return of 6.36%, a F1-measure of 65.94%, and a hit ratio of 62.39% in the four testing periods, indicating that the proposed method is more accurate and more profitable than the benchmarks. Therefore, the proposed method could be applied by the market participants as an alternative prediction and trading system to forecast and trade in the Chinese financial futures market.http://dx.doi.org/10.1155/2022/7622906 |
| spellingShingle | Shangkun Deng Yingke Zhu Ruijie Liu Wanyu Xu Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique Advances in Mathematical Physics |
| title | Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique |
| title_full | Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique |
| title_fullStr | Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique |
| title_full_unstemmed | Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique |
| title_short | Financial Futures Prediction Using Fuzzy Rough Set and Synthetic Minority Oversampling Technique |
| title_sort | financial futures prediction using fuzzy rough set and synthetic minority oversampling technique |
| url | http://dx.doi.org/10.1155/2022/7622906 |
| work_keys_str_mv | AT shangkundeng financialfuturespredictionusingfuzzyroughsetandsyntheticminorityoversamplingtechnique AT yingkezhu financialfuturespredictionusingfuzzyroughsetandsyntheticminorityoversamplingtechnique AT ruijieliu financialfuturespredictionusingfuzzyroughsetandsyntheticminorityoversamplingtechnique AT wanyuxu financialfuturespredictionusingfuzzyroughsetandsyntheticminorityoversamplingtechnique |