Research Scenarios
The framework can be utilized by researchers:
- Testing the market efficiency hypothesis
- Testing the Effect of Intelligent Body Collaboration Patterns on Winning Rates
- Developing an Event Factor Library
Operation Guide
- Experimental design::
- Implant a control group in the belief_list (e.g. purely technical vs. fundamental + event driven)
- Turn off real-time data in favor of historical datasets via config.yaml
- Analysis of results::
- View the decision process log in the logs/ directory
- Output attribution analysis with report_generator module
Advanced Techniques
Custom intelligences can be developed by inheriting the ResearchAgent base class, for example, to implement:
- Transformer-based event impact level prediction
- Risk hedging algorithms combining option volatility
Note that you need to add the corresponding dependencies in requirements.txt.
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 can ContestTrade be applied to test novel trading strategies in a quantitative research scenario?
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