This is the codebase for the paper - News-Based Sparse Machine Learning Models for Adaptive Asset Pricing - by Liao Zhu, Haoxuan Wu, and Martin T. Wells.
If you want to replicate the paper mentioned above, please purchase the stock returns data from the Center for Research in Security Prices, LLC (CRSP) database (https://www.crsp.org/), and purchased the news data from Dow Jones ``Data, News and Analytics (DNA)'' news database (https://network-effects.dowjones.com/). Save the data in the folder "data" and run compute.ipynb.
Any code that uses this repository must state that it is obtained from this repository and must have a reference to the following paper:
@article{zhu2023news, title={News-Based Sparse Machine Learning Models for Adaptive Asset Pricing}, author={Zhu, Liao and Wu, Haoxuan and Wells, Martin T}, journal={Data Science in Science}, volume={2}, number={1}, pages={2187895}, year={2023}, publisher={Taylor & Francis} }
The paper mentioned above is open-source and has full text available here https://www.tandfonline.com/doi/pdf/10.1080/26941899.2023.2187895
For more related papers, please see the google scholar link: https://scholar.google.com/citations?user=WDX3NZsAAAAJ&hl=en
Should you have any questions, please feel free to email me via LZ384 at CORNELL.EDU.