Background and core ideas
Event-driven investing requires real-time capture of news, announcements and other market information, which is traditionally screened inefficiently by hand. contestTrade automates this process through a multi-intelligence collaboration framework.
Specific steps
- Basic Configuration: After installing the framework, configure the Tushare data interface key in config.yaml to ensure access to real-time announcements, money flows, etc.
- Deployment of IntelligenceModify the belief_list.json file, for example, add event strategies such as "prioritize the capture of M&A and restructuring announcements within 3 days of the capital inflow of the underlying".
- Start scanning: Implementation
python -m cli.main runcommand, which is automatically executed by the system after the target date is entered:- Data Processing Intelligence Body Cleaning Raw Data
- Studying Intelligentsia to Generate Candidate Lists Based on Preconceived Beliefs
Optimization Recommendations
The screening dimension can be enhanced by configuring BOCHA_KEY to supplement the network public opinion data, or by adding compound event strategies such as "pay attention to the resonance between institutional seats on the LHL list and northbound funds" in the BELIEF_LIST.
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 automate stock screening for event-driven investing?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil