EP-GAT: Energy-based Parallel Graph Attention Neural Network for Stock Trend Classification

📄 Paper accepted by IJCNN 2025

1. Configuration

Please refer to the Setup section in the code.

2. Dataset

• The raw data used in this paper is provided as .csv files under ~/data/.
• The dataset is collected from five markets: LSE, FTSE, NASDAQ, NYSE, S&P.
• For customed dataset, please refer to the code for expected CSV format and preprocessing steps.

3. Training

Please follow the instructions and the code in the ipynb file.

3. Citation

If you think this project is helpful, please feel free to leave a star or cite our paper:

@inproceedings{jiang2025ep,
  title={EP-GAT: Energy-based Parallel Graph Attention Neural Network for Stock Trend Classification},
  author={Jiang, Zhuodong and Zhang, Pengju and Martin, Peter},
  booktitle={2025 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2025},
  organization={IEEE}
}