Report Quality Improvement Program
A systematic approach to ensuring the reliability of analytical results:
- multi-source authentication mechanism::
- Configure alternative_data.py to supplement alternate data sources such as Oriental Wealth.
- Difference threshold alarms for key metrics (e.g., EPS difference > 10% triggers review)
- Transparency of the analytical process::
- Enable debug mode to record the reasoning process of each intelligent body
- Demonstration of key data sources and calculation logic in the appendix of the report
- Continuous Optimization Program::
- Regular updates of llm's financial knowledge base (model updates via ollama pull)
- Establishment of a feedback assessment system between historical forecasts and actual performance
Professionalism checklist:
- Risk-return ratio calculation included or not
- Whether the technical analysis indicates the parameters of the indicators used
- Whether the target price provides sensitivity analysis
This answer comes from the articleDeepAgents: an AI Intelligence for Professional-Grade Equity ResearchThe
May not be reproduced without permission:AI productivity tools " How to enhance the professional credibility of the generated reports?
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