How do AI bots trade on Polymarket prediction markets?
AI trading bots use machine learning models to estimate the true probability of events and compare their estimates to Polymarket's current prices. When there's a significant gap (e.g., AI estimates 72% but market says 55%), the bot places a trade. The edge comes from processing information faster and more accurately than the average market participant — news articles, data feeds, social media sentiment, and historical patterns.
What AI models work best for Polymarket prediction trading?
Ensemble approaches using multiple models perform best: large language models (GPT-4, Claude) for parsing news and context, custom classifiers trained on historical Polymarket resolution data, and statistical models for time-series analysis. The key is consensus — when multiple independent models agree that a market is mispriced, confidence is highest. Single-model approaches are too noisy for consistent profitability.
How much does it cost to run an AI trading bot on Polymarket?
AI API costs for ensemble models range from $500-$2,000/month depending on query volume. With 380 trades/day, each requiring multiple model evaluations, API fees add up. However, simpler strategies like arbitrage and momentum achieve similar monthly profits with just $6-12/month VPS costs and zero API fees — making them more capital-efficient for most traders.
What Polymarket categories are best for AI trading bots?
AI bots perform best on markets with frequent new information: crypto price predictions (continuous data flow), politics (polls, news cycles), sports (injury reports, performance data), and tech events (earnings, product launches). Markets with rare or unpredictable triggers (e.g., earthquake predictions) are poor candidates because there's insufficient data for model training.
What is the Kelly Criterion and how does it apply to Polymarket?
The Kelly Criterion is a formula that determines optimal position size based on your edge and the odds: f = (bp - q) / b, where b is odds, p is win probability, q is loss probability. On Polymarket, if your AI estimates 70% probability but the market is at 55%, Kelly suggests sizing ~33% of bankroll. Most traders use fractional Kelly (25-50%) to reduce variance while maintaining positive expected value.