News-driven financial warning based on label information attention
Authors: 
Ren Zhilin, Chen Long, Huang Xiaohua, Wang Wenjing, Xu Cai, Zhao Wei, Guan ZiyuAuthors Info & Claims
Ren Zhilin, Chen Long, Huang Xiaohua, Wang Wenjing, Xu Cai, Zhao Wei, Guan ZiyuAuthors Info & ClaimsPages 1177 - 1182
Abstract
Most existing news-driven stock market prediction methods ignore the potential relationship between financial news and stocks. The complex relationship can help us to improve the accuracy of algorithmic trading systems. Therefore, we propose a deep learning method for financial warning by fusing Stock Label Information (SLI). We extract events from news texts and fuse stock information together as feature vectors, using neural networks to model the underlying relationship between news and stocks. Experimental results show that our method outperforms other baseline methods in experiments on TPX500 and TPX100 datasets.
CCS CONCEPTS • Computing methodologies • Artificial intelligence • Natural language processing
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- News-driven financial warning based on label information attention
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Published In
September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
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Association for Computing Machinery
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Publication History
Published: 16 May 2023
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AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
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