Thriving 
PY Automated paper-trading bot that bets the NO side of overpriced Polymarket temperature markets, using live METAR observations and Open-Meteo forecasts with a Gaussian probability model.
HEALTH ? 80 / Healthy
Thriving PY // readme
POLYMARKET WEATHER EDGE BOT
This project builds an automated paper trading bot that exploits a systematic mispricing in Polymarket’s daily temperature markets. I noticed that the market consistently overprices extreme temperature outcomes (YES side), so I built a pipeline that combines live METAR observations from each market’s resolution station and Open-Meteo forecasts with a Gaussian probability model to trade the NO side. The live entry rule is an explicit NO-price band validated on historical trade buckets; every trade records the full set of weather features so a Random Forest calibrator can be retrained on clean data and reintroduced as a gate.
WHAT I WORKED ON
- Weather market pipeline: Connected to Polymarket’s Gamma API to fetch active daily temperature contracts and parsed each market to extract city, date, and temperature range from the question text, handling both °C and °F market formats with unit-aware bin corrections.
- Resolution-source alignment: Audited every market’s resolution station against its live description (catching that Paris resolves at Le Bourget, not CDG) and validated data sources against the actual resolution of 500+…