ALSGCN

This repository supports the development and validation of the paper: "An Attention-based Long and Short-term Graph Convolutional Network for Stock Recommendation".

Environment and Dataset

1. Install python3.7, 3.8 or 3.9.
2. Install the requirements in requirements.txt
3. Install the quantitative investment platform Qlib and download the data from Qlib:

   # install Qlib from source
   pip install --upgrade  cython
   git clone https://github.com/microsoft/qlib.git && cd qlib
   python setup.py install
   
   # Download the stock features of Alpha360 from Qlib
   python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --region cn --version v2
   

Structure

1. data:

• csi300_market_value_07to20.pkl: Contains the market value data for the CSI 300 index from 2007 to 2020.
• csi300_stock2concept.npy: Contains the mapping of CSI 300 stocks to their respective concepts.
• csi300_stock_index.npy: Contains the mapping of CSI 300 stocks to their respective indexes.

2. ALSGCN.py: Contains the implementation of the ALSGCN model.
3. dataloader.py: Contains the data loading and preprocessing functions.
4. learn_ALSGCN.py: Contains the training and evaluation code for the ALSGCN model.
5. requirements.txt: Lists the required Python packages.
6. utils.py: Contains utility functions used in the project.

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If you find this work useful in yours, please consider citing.

@inproceedings{yu2025alsgcn,
  title={{ALSGCN}: An Attention-based Long and Short-term Graph Convolutional Network for Stock Recommendation},
  author={Yu, Junpeng and Yao, Wenjie and Li, Zhihao and Gao, Lele and Xiao, Wenyun and Wang, Hongnian},
  booktitle={2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
  year={2025},
  month={October},
  address={Vienna, Austria},
  organization={IEEE},
}