A structured multi-head attention prediction method based on heterogeneous financial data Article Swipe
Cheng Zhao
,
Fangyong Li
,
Zhe Peng
,
Zhou Xiao
,
Y. Zhuge
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.7717/peerj-cs.1653
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.7717/peerj-cs.1653
The diverse characteristics of heterogeneous data pose challenges in analyzing combined price and volume data. Therefore, appropriately handling heterogeneous financial data is crucial for accurate stock prediction. This article proposes a model that applies customized data processing methods tailored to the characteristics of different types of heterogeneous financial data, enabling finer granularity and improved feature extraction. By utilizing the structured multi-head attention mechanism, the model captures the impact of heterogeneous financial data on stock price trends by extracting data information from technical, financial, and sentiment indicators separately. Experimental results conducted on four representative individual stocks in China’s A-share market demonstrate the effectiveness of the proposed method. The model achieves an average MAPE of 1.378%, which is 0.429% lower than the benchmark algorithm. Moreover, the backtesting return rate exhibits an average increase of 28.56%. These results validate that the customized preprocessing method and structured multi-head attention mechanism can enhance prediction accuracy by attending to different types of heterogeneous data individually.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7717/peerj-cs.1653
- OA Status
- gold
- Cited By
- 3
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388766400
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388766400Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7717/peerj-cs.1653Digital Object Identifier
- Title
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A structured multi-head attention prediction method based on heterogeneous financial dataWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-11-17Full publication date if available
- Authors
-
Cheng Zhao, Fangyong Li, Zhe Peng, Zhou Xiao, Y. ZhugeList of authors in order
- Landing page
-
https://doi.org/10.7717/peerj-cs.1653Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.7717/peerj-cs.1653Direct OA link when available
- Concepts
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Computer science, Data mining, Data pre-processing, Preprocessor, Granularity, Benchmark (surveying), Finance, Artificial intelligence, Geodesy, Economics, Geography, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
- References (count)
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31Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W1989130706, https://openalex.org/W4304136478, https://openalex.org/W3045961212, https://openalex.org/W2766846435, https://openalex.org/W3124798136, https://openalex.org/W3100219394, https://openalex.org/W4307570893, https://openalex.org/W2624385633, https://openalex.org/W4250176440, https://openalex.org/W3162273446, https://openalex.org/W2101620928, https://openalex.org/W6758805977, https://openalex.org/W4308512597, https://openalex.org/W3146366485, https://openalex.org/W2025053102, https://openalex.org/W4285606719, https://openalex.org/W2053615983, https://openalex.org/W4385245566, https://openalex.org/W2998454530, https://openalex.org/W4285402398, https://openalex.org/W3124828689, https://openalex.org/W3082523044, https://openalex.org/W3203755200, https://openalex.org/W4282959107, https://openalex.org/W4311626321, https://openalex.org/W3145838940, https://openalex.org/W4224220755, https://openalex.org/W3093850747, https://openalex.org/W3204598003, https://openalex.org/W4306320857, https://openalex.org/W2915043312 |
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