中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
ST-Trader: A Spatial-Temporal Deep Neural Network for Modeling Stock Market Movement

文献类型:期刊论文

作者Xiurui Hou; Kai Wang; Cheng Zhong; Zhi Wei
刊名IEEE/CAA Journal of Automatica Sinica
出版日期2021
卷号8期号:5页码:1015-1024
关键词Graph convolution network long-short term memory network stock market forecasting variational autoencoder (VAE)
ISSN号2329-9266
DOI10.1109/JAS.2021.1003976
英文摘要Stocks that are fundamentally connected with each other tend to move together. Considering such common trends is believed to benefit stock movement forecasting tasks. However, such signals are not trivial to model because the connections among stocks are not physically presented and need to be estimated from volatile data. Motivated by this observation, we propose a framework that incorporates the inter-connection of firms to forecast stock prices. To effectively utilize a large set of fundamental features, we further design a novel pipeline. First, we use variational autoencoder (VAE) to reduce the dimension of stock fundamental information and then cluster stocks into a graph structure (fundamentally clustering). Second, a hybrid model of graph convolutional network and long-short term memory network (GCN-LSTM) with an adjacency graph matrix (learnt from VAE) is proposed for graph-structured stock market forecasting. Experiments on minute-level U.S. stock market data demonstrate that our model effectively captures both spatial and temporal signals and achieves superior improvement over baseline methods. The proposed model is promising for other applications in which there is a possible but hidden spatial dependency to improve time-series prediction.
源URL[http://ir.ia.ac.cn/handle/173211/43963]  
专题自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
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GB/T 7714
Xiurui Hou,Kai Wang,Cheng Zhong,et al. ST-Trader: A Spatial-Temporal Deep Neural Network for Modeling Stock Market Movement[J]. IEEE/CAA Journal of Automatica Sinica,2021,8(5):1015-1024.
APA Xiurui Hou,Kai Wang,Cheng Zhong,&Zhi Wei.(2021).ST-Trader: A Spatial-Temporal Deep Neural Network for Modeling Stock Market Movement.IEEE/CAA Journal of Automatica Sinica,8(5),1015-1024.
MLA Xiurui Hou,et al."ST-Trader: A Spatial-Temporal Deep Neural Network for Modeling Stock Market Movement".IEEE/CAA Journal of Automatica Sinica 8.5(2021):1015-1024.

入库方式: OAI收割

来源:自动化研究所

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