Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures
With the advancement of deep learning, its application in financial market forecasting has become a research hotspot. This paper proposes an innovative Multi-Scale TsMixer model for predicting stock index futures in the A-share market, covering SSE50, CSI300, and CSI500. By integrating Multi-Scale t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/9/1415 |
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| author | Zhiyuan Pei Jianqi Yan Jin Yan Bailing Yang Xin Liu |
| author_facet | Zhiyuan Pei Jianqi Yan Jin Yan Bailing Yang Xin Liu |
| author_sort | Zhiyuan Pei |
| collection | DOAJ |
| description | With the advancement of deep learning, its application in financial market forecasting has become a research hotspot. This paper proposes an innovative Multi-Scale TsMixer model for predicting stock index futures in the A-share market, covering SSE50, CSI300, and CSI500. By integrating Multi-Scale time-series features across the short, medium, and long term, the model effectively captures market fluctuations and trends. Moreover, since stock index futures reflect the collective movement of their constituent stocks, we introduce a novel approach: predicting individual constituent stocks and merging their forecasts using three fusion strategies (average fusion, weighted fusion, and weighted decay fusion). Experimental results demonstrate that the weighted decay fusion method significantly improves the prediction accuracy and stability, validating the effectiveness of Multi-Scale TsMixer. |
| format | Article |
| id | doaj-art-c8b378eed71f4e86b1fd9db8399c2c49 |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-c8b378eed71f4e86b1fd9db8399c2c492025-08-20T02:59:11ZengMDPI AGMathematics2227-73902025-04-01139141510.3390/math13091415Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index FuturesZhiyuan Pei0Jianqi Yan1Jin Yan2Bailing Yang3Xin Liu4School of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, ChinaSchool of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, ChinaSchool of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, ChinaSchool of Computer Science and Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, ChinaMacau Institute of Systems Engineering, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078, ChinaWith the advancement of deep learning, its application in financial market forecasting has become a research hotspot. This paper proposes an innovative Multi-Scale TsMixer model for predicting stock index futures in the A-share market, covering SSE50, CSI300, and CSI500. By integrating Multi-Scale time-series features across the short, medium, and long term, the model effectively captures market fluctuations and trends. Moreover, since stock index futures reflect the collective movement of their constituent stocks, we introduce a novel approach: predicting individual constituent stocks and merging their forecasts using three fusion strategies (average fusion, weighted fusion, and weighted decay fusion). Experimental results demonstrate that the weighted decay fusion method significantly improves the prediction accuracy and stability, validating the effectiveness of Multi-Scale TsMixer.https://www.mdpi.com/2227-7390/13/9/1415deep learningA-shares marketstock index futuresMulti-Scale TsMixercomponent stock weightingtime-series prediction |
| spellingShingle | Zhiyuan Pei Jianqi Yan Jin Yan Bailing Yang Xin Liu Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures Mathematics deep learning A-shares market stock index futures Multi-Scale TsMixer component stock weighting time-series prediction |
| title | Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures |
| title_full | Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures |
| title_fullStr | Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures |
| title_full_unstemmed | Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures |
| title_short | Multi-Scale TsMixer: A Novel Time-Series Architecture for Predicting A-Share Stock Index Futures |
| title_sort | multi scale tsmixer a novel time series architecture for predicting a share stock index futures |
| topic | deep learning A-shares market stock index futures Multi-Scale TsMixer component stock weighting time-series prediction |
| url | https://www.mdpi.com/2227-7390/13/9/1415 |
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