Polymarket Weather Temperature Arbitrage
Exploits overpriced 'YES' shares in Polymarket temperature markets by betting 'NO' using live METAR data and Gaussian probability models.
This strategy targets prediction markets for daily high/low temperatures. The bot scrapes live METAR observations and Open-Meteo forecasts to compute a Gaussian probability distribution for the actual temperature. It then identifies markets where the implied probability of a specific temperature range is significantly higher than the model's computed probability, presenting a favorable 'NO' bet. The entry is triggered when the model estimates a >5% edge on the NO side; exit is automatic at market resolution or when the edge dissipates. Paper-trading results show consistent profitability on overpriced temperature markets. Implementation uses Python, real-time weather APIs, and Polymarket's CLOB API for order placement.