mapledust0/AI-Stock-Nowcasting

Real-Time AI Cross-sectional stock nowcasting project initiated by Zefeng Chen and Darcy Pu at Guanghua School of Management, Peking University

33
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Emerging

This project helps active portfolio managers, traders, or quantitative analysts identify promising stocks for short-term gains. It takes real-time web information and an AI agent to generate daily stock attractiveness scores for Russell 1000 companies. The output is a daily ranked list of stocks, allowing users to build a portfolio of top-ranked stocks, which have shown superior returns compared to the broader market.

Use this if you are a professional investor or trader seeking an AI-driven signal to identify potential 'winner' stocks daily from the Russell 1000 index, specifically for short-term, high-conviction strategies.

Not ideal if you are a long-term investor, interested in predicting 'loser' stocks, or focusing on stocks outside the Russell 1000.

quantitative-investing algorithmic-trading stock-selection market-intelligence portfolio-management
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 13 / 25
Community 4 / 25

How are scores calculated?

Stars

21

Forks

1

Language

HTML

License

MIT

Last pushed

Mar 08, 2026

Commits (30d)

0

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