Polymarket Quant
Finding systematic alpha in prediction markets
Why prediction markets
I want to get into quant trading, but I'm not interested in competing directly with teams of PhDs in math and physics in hyper-efficient markets. Betting markets are relatively new, attract many amateur participants, and often price events under uncertainty rather than fundamentals. This project is about finding out if it's possible to find real, systematic alpha in prediction markets by building and testing quant strategies.
How it works
Polymarket lets you bet on real-world events. You buy YES or NO on outcomes like elections, sports, crypto prices. The bot watches for opportunities, places bets automatically, and manages positions. I get Discord alerts whenever it makes a trade.
Polymarket Quant Tested every technical analysis / price-action strategy I could think of, none came close to showing an edge. Polymarket price data just doesn't seem to carry exploitable patterns. I'm fairly confident in ruling out TA-based approaches.
Next hypothesis to test: information speed. The thesis is that smaller, lower-volume markets may not have sophisticated news-parsing bots monitoring them, especially if the news is not easily accessible and requires custom-built information retrieval.
Polymarket Quant Built the full trading infrastructure in a single day:
- Strategy framework
- Backtesting
- Paper trading
- Live execution
- Discord webhooks for real-time P&L notifications
Then let two Cursor instances run full 200k context quant research sessions, which produced a mean reversion strategy projecting ~350% annualized (backtests, so grain of salt). Bot is live on paper now. Letting it run for 2 weeks while I focus on school, then switching to real money if the numbers hold.