A representation-learning-based approach to predict stock price trend via 
dynamic spatiotemporal feature embedding

Pang, Bowen; Wei, Wei; Li, Xing; Feng, Xiangnan; Li, Chao

doi:10.1016/j.engappai.2023.106849

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A representation-learning-based approach to predict stock price trend via dynamic spatiotemporal feature embedding

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Feng, Xiangnan
Center for Humans and Machines, Max Planck Institute for Human Development, Max Planck Society;

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https://doi.org/10.1016/j.engappai.2023.106849
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Pang, B., Wei, W., Li, X., Feng, X., & Li, C. (2023). A representation-learning-based approach to predict stock price trend via dynamic spatiotemporal feature embedding. Engineering Applications of Artificial Intelligence, 126, Part A: 106849. doi:10.1016/j.engappai.2023.106849.

Cite as: https://hdl.handle.net/21.11116/0000-000D-93EC-3

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