AI News Analysis and Automated Trading for Polymarket Markets

Summary

The document describes an automated approach to trading Polymarket prediction contracts. It scans popular markets by recent volume, asks an AI model to create search queries, gathers current web and news results, and then uses the model’s assessment to choose whether to buy YES or NO, skip, or block a market. The system also covers order execution, position limits, account checks, redemption of settled positions, and manual commands.

The examples show how news about economic policy or crypto could inform a decision, but they are illustrative rather than measured results. Suggested controls include limiting each trade by account equity and a maximum amount, restricting the number of open positions, and avoiding simultaneous exposure to opposing sides of a question. These measures do not ensure sound predictions or prevent losses. The document notes model errors, event shocks, search and model API costs, and the possibility of losing an entire position; it reports no backtest or verified trading performance.

Key ideas

• The workflow combines market screening, AI-generated search terms, web research, a trading decision, and order execution.
• The AI may choose a YES or NO position, skip a market, or place it on a blacklist.
• Suggested controls include trade sizing by equity, a maximum trade amount, and a cap on open positions.
• The examples illustrate the decision process but do not establish predictive accuracy or profitability.
• Model errors, sudden events, API costs, and total position loss remain material risks.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.