Intelligent stock picking mechanism implementation
ContestTrade's automated screening capabilities enable an end-to-end process from massive market data to portfolios.
Technology realization path
- data acquisition layer: Access to market, financial and opinion data through interfaces such as Tushare
- event recognition layer: Parsing news bulletins using NLP techniques to identify 8 categories of catalytic events
- strategy implementation layer: Multi-layer filtering based on 50+ trading beliefs configured in belief_list.json
Practical application performance
In the test case, the system was able to complete a full market scan in 20 minutes: 300-500 candidate stocks were screened in the first round, and a portfolio of 10-20 stocks was finally generated after intelligent body analysis. The screening dimensions include 12 core indicators such as market capitalization volatility, event correlation, and capital flow.
User value embodiment
This feature frees up 90%'s manual screening time and, through multi-intelligence cross-validation, brings the stock selection results up to the level of a professional analyst team. Users only need to focus on the final signals without intervening in the intermediate process.
This answer comes from the articleContestTrade: an AI multi-intelligence trading framework for event-driven investingThe
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