sthgcn-icdm
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Code for Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting
Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting
This codebase contains the python scripts for STHGCN, the model for the ICDM 2020 paper link.
Environment & Installation Steps
Python 3.6, Pytorch, Pytorch-Geometric and networkx.
Dataset and Preprocessing
Download the dataset and follow preprocessing steps from here.
bash download.sh
Run
Execute the following python command to train STHGCN:
make test_phase=1 save_dir=save
test_phase : phase that you want to test
Cite
Consider citing our work if you use our codebase
@INPROCEEDINGS{9338303, author={Sawhney, Ramit and Agarwal, Shivam and Wadhwa, Arnav and Shah, Rajiv Ratn}, booktitle={2020 IEEE International Conference on Data Mining (ICDM)}, title={Spatiotemporal Hypergraph Convolution Network for Stock Movement Forecasting}, year={2020}, volume={}, number={}, pages={482-491}, doi={10.1109/ICDM50108.2020.00057}}