Feb. 13, 2024, 5:43 a.m. | Hao Qian Hongting Zhou Qian Zhao Hao Chen Hongxiang Yao Jingwei Wang Ziqi Liu Fei Yu Z

cs.LG updates on arXiv.org arxiv.org

The stock market is a crucial component of the financial system, but predicting the movement of stock prices is challenging due to the dynamic and intricate relations arising from various aspects such as economic indicators, financial reports, global news, and investor sentiment. Traditional sequential methods and graph-based models have been applied in stock movement prediction, but they have limitations in capturing the multifaceted and temporal influences in stock price movements. To address these challenges, the Multi-relational Dynamic Graph Neural Network …

cs.ir cs.lg dynamic economic financial global graph graph-based graph neural network investment investor network neural network prediction q-fin.st relational relations reports sentiment stock

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