Weather Edge Paper Trading

This bot trades the NO side of Polymarket temperature markets that are deemed overpriced. It uses live METAR (surface weather observation) data and Open-Meteo forecasts to estimate the probability of a given temperature outcome.

The bot employs a Gaussian probability model to compare its fair probability estimate against the market's implied probability. If the market price is significantly higher than the model's probability for a 'yes' outcome, the bot will bet NO.

This is a paper-trading bot for now, meaning it simulates trades rather than risking real capital. This allows for testing and refinement of the strategy without financial risk. The repo has a modest 5 stars, indicating small but possibly genuine interest.

Implementation notes: Written in Python, the bot is well-structured with a clear focus on weather markets. The use of METAR observations provides high-quality real-time data, while Open-Meteo provides forecast data. The Gaussian model is a standard statistical approach for temperature distributions.

Risks: Paper trading results don't guarantee real-world performance. Slippage, liquidity, and execution issues could impact profitability when using real funds. The model may also be systematically biased if the Gaussian assumption is wrong for temperature distributions.