Weather Temperature NO-Side Betting

This automated paper-trading bot focuses on Polymarket markets that predict daily high or low temperatures at specific locations. It uses live METAR observations and Open-Meteo forecast data along with a Gaussian probability model to estimate the fair probability of a temperature threshold being exceeded. When the market price for the YES outcome is significantly higher than the model's estimated probability, the bot bets the NO side (effectively selling overpriced YES shares). The entry condition is a minimum edge threshold (e.g., market implied probability > model probability + buffer). Exit occurs at market resolution. The model continuously updates with new weather data, providing a statistical edge over uninformed traders.