Prediction-Markets

AI Agents vs. Polymarket: 90 Days, 800 Trades — Who’s Actually More Rational? TL;DR A live trading experiment running 90 days and 800 real trades put AI agents head-to-head against Polymarket’s crowd wisdom — and the results are raising eyebrows in the algo trading community. The question isn’t just “can AI beat prediction markets?” — it’s whether AI models approach probability differently than human traders. Platforms like Oracle Markets are now building public leaderboards specifically to stress-test this. And at least one model family, MiniMax, has shown consistent profits in live trading conditions. ...

Months of L3 Orderbook Data From Prediction Markets Is Up for Grabs — Here’s Why That Matters TL;DR A researcher on Reddit’s r/algotrading has accumulated months of Level 3 orderbook data across major prediction market platforms and is asking the community how best to release it publicly. L3 data — the deepest, most granular view of market microstructure — is extremely rare in the prediction market space. The post sparked 40 comments and significant community interest, signaling real demand for this kind of dataset. If released properly, it could become a foundational resource for algo traders, researchers, and market microstructure analysts. ...

I Gave My AI Agent $50 and Let It Trade on Kalshi: What Happened Next TL;DR A developer decided to experiment with autonomous AI trading by giving an AI agent $50 and letting it trade independently on Kalshi, a prediction market platform. The experiment was shared on Hacker News, sparking interest in the growing trend of AI agents managing real money in financial markets. While the source package doesn’t reveal the detailed results, this experiment represents a microcosm of the broader debate around AI autonomy in trading, risk management, and whether we’re ready to trust algorithms with our money. If you’re curious about AI trading agents or considering building one yourself, this experiment offers a real-world case study worth examining. ...