Backtesting

How to backtest trading strategies using Polymarket historical data.

• Backtest Polymarket Strategy: A Practical Workflow

  A step-by-step workflow to backtest a Polymarket strategy using resolved markets, historical snapshots, realistic fills, and risk metrics.

• Backtesting Framework for Polymarket with Python

  Build a complete backtesting framework for Polymarket prediction markets using Python and PolyHistorical data.

• Common Backtesting Mistakes with Prediction Market Data

  Avoid these common pitfalls when backtesting strategies on Polymarket historical data.

• Data Cleaning for Prediction Market Backtests

  How to clean and prepare Polymarket historical order book data for accurate backtesting and strategy development.

• Monte Carlo Simulation for Prediction Market Backtests

  Apply Monte Carlo simulation methods to stress-test your Polymarket trading strategies using historical order book data.

• Polymarket Backtesting API: Replay Strategies with Historical Books

  Use a Polymarket backtesting API to replay resolved BTC, ETH, and SOL Up/Down markets with historical order books and realistic fills.

• Polymarket Backtesting Data: Order Books, Fills, and Slippage

  Get Polymarket backtesting data with historical order book snapshots, real depth, reference prices, and resolution metadata for strategy research.

• Polymarket Bot Backtesting Data: Train Before You Trade

  Use historical Polymarket order book data to backtest trading bots before deploying them against live markets.

• Polymarket BTC Up/Down Backtesting with Historical Order Books

  Backtest Polymarket BTC Up/Down strategies using historical order book snapshots, Binance and Chainlink reference prices, and realistic fill modeling.

• Polymarket Historical Replay: Rebuild Past Markets Tick by Tick

  Replay Polymarket historical snapshots to rebuild how prices, spreads, depth, and strategy fills changed before market resolution.

• Polymarket Paper Trading vs Backtesting: Which Comes First?

  Compare Polymarket paper trading and backtesting, including when to use each and why historical order book replay should come before live simulation.

• Polymarket Slippage Backtesting: Simulate Realistic Fills

  Backtest Polymarket strategies with slippage by consuming historical order book depth instead of assuming midpoint or last-price fills.

• Polymarket Strategy Replay: Test Rules on Historical Markets

  Replay Polymarket historical order books with strategy rules to measure fills, PnL, drawdown, and slippage on resolved markets.

• Polymarket Trading Strategy Backtest: Signals to Fills

  Turn Polymarket trading ideas into tested strategies by replaying historical order books and measuring signal quality, fills, and risk.

• Strategy Evaluation Metrics for Prediction Market Backtests

  Key performance metrics for evaluating backtested prediction market strategies — Sharpe ratio, drawdown, win rate, and more.

• Walk-Forward Optimization for Prediction Market Strategies

  How to use walk-forward optimization to validate trading strategies on Polymarket historical data and avoid overfitting.