Learning Dynamic Dependencies With Graph Evolution Recurrent Unit for Stock Predictions
Author:
Affiliation:
1. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Funder
Ministry of Science and Technology of China
Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software
Link
http://xplorestaging.ieee.org/ielx7/6221021/10286435/10176355.pdf?arnumber=10176355
Reference42 articles.
1. Multiobjective Automated Type-2 Parsimonious Learning Machine to Forecast Time-Varying Stock Indices Online
2. Applications of deep learning in stock market prediction: Recent progress
3. Deep Direct Reinforcement Learning for Financial Signal Representation and Trading
4. A theory of power-law distributions in financial market fluctuations
5. Analyzing the dynamic sectoral influence in Chinese and American stock markets
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1. Predicting Stock Price Movements in Volatile Markets: A Multi-Model Fusion Approach;2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE);2024-04-26
2. Diversified Adaptive Stock Selection Using Continual Graph Learning and Ensemble Approach;IEEE Access;2024
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