Guides / Education

Walk-Forward Optimization for Prediction Market Strategies

Walk-forward optimization tunes a strategy on one window of historical data, then tests it on the next window forward — repeating this across the full history — instead of tuning once on the whole dataset and risking overfitting to it.

Related

• Common backtesting mistakes
• Strategy evaluation metrics

Related guides

• Prediction Market Data for Academic Research
• Building a Polymarket Backtesting Framework in Python
• Common Backtesting Mistakes in Prediction Markets
• Data Cleaning for Prediction Market Backtests

Data from Kalshi and Polymarket. Search live · API docs · Pricing