Black-Scholes on Polymarket: Finding Mispriced Binary Events with Python

1. 1Apply the Black-Scholes model to calculate the theoretical price of a binary option using Python
2. 2Use the calculated price to compare with the market price on Polymarket and identify potential mispricings
3. 3Analyze the volatility and risk factors that contribute to mispricings
4. 4Backtest the strategy using historical data to evaluate its performance
5. 5Refine the model by incorporating additional factors, such as market sentiment and liquidity

Quantitative analysts and traders can benefit from this technique to identify undervalued or overvalued binary events on Polymarket, while data scientists can apply the Black-Scholes model to other prediction markets

💡 The Black-Scholes model can be applied to binary options on Polymarket to identify mispricings, allowing for potential trading opportunities

Detect mispriced binary events on Polymarket with Black-Scholes & Python!