PredictionToolkit
A Kalshi-first research assistant with backtests, scheduled alerts and Polymarket comparisons; users execute orders themselves.
- Trading mode Read-only
- Access Web
Find your toolkit
Polymarket backtesting and replay tools | Page 2
Replay a strategy or recorded execution, compare scenarios and inspect modeled fills. Choose the engine for the past-period question you want to investigate.
How to choose backtesting
Read the replay assumptions
The result depends on the window and the engine’s treatment of the data. Reconstructed fills should be understood through those assumptions, rather than treated as a record of what your account would necessarily have earned.
Check the model
- Confirm the replay window.
- Inspect fees and spread handling.
- Read how missing data and available depth affect modeled fills.
- Find raw inputs in Historical data and forward simulations in Paper trading.
20 tools · 13–20 shown
Replay historical Polymarket data in NautilusTrader, compare parameters and inspect portfolio and execution reports.
- Language Python · Rust
Develop prediction-market rules with explicit costs, risk limits, historical replay and a paper stage.
- Trading mode Paper · Live automation
- Access Web
Move from trader research to rules, historical tests and paper bots, with venue-specific live activation.
- Trading mode Paper
- Access Web · Telegram · API · MCP
Develop agent strategies with research, paper trading, replay and supported live integrations.
- Language Python
- Access CLI
Move from a strategy description through backtesting and paper trading to a hosted bot.
- Trading mode Paper · Live automation
- Access Web · MCP
A Rust framework reference for strategies, paper execution, replay and monitoring, with a material configuration caveat.
- Access Rust · Self-hosted
Normalized prediction-market data, matched contracts, replay and paper trading for multi-venue research.
- Access Web · API · MCP