workflow
- Preparing to Trade Beliefs:: Editorial
belief_list.jsonDocument defining an investment strategy for researching intelligences - triggering program: Run in the project root directory
python -m cli.main run - Setting the analysis date: Enter the date of analysis in YYYY-MM-DD format.
- View Results: The system will output including:
- Terminal Summary Report
- Transaction signals generated by the respective intelligences
- Detailed AI analysis report
Custom Analytics Strategy
Users can modify thebelief_list.jsonThe document fully customizes the analysis strategy of the intelligences, for example:
- Examples of aggressive strategies: Focus on short-term event-driven opportunities with a preference for small- and mid-cap high volatility stocks
- Examples of robust strategies: Focus on deterministic events such as dividend buybacks and earnings previews, with a preference for large-cap blue chips
Application Recommendations
Once the system has run its course, it will provide preliminary trading signals and recommendations. Professional users can combine these outputs with their own analysis to construct better investment decisions. It should be noted that the results generated by the system are for research purposes only and should not be used as the sole basis for investment.
This answer comes from the articleContestTrade: an AI multi-intelligence trading framework for event-driven investingThe
May not be reproduced without permission:AI productivity tools " How to use ContestTrade for real-world investment analysis?
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