This is a custom rule-based bot tuned to specific entry and exit conditions.
Kalshi·Mar 21 to Apr 19·Created 1d ago
Total PnL
+$4,305
Simulated P&L
Sharpe
8.03
Risk-adjusted return
Win rate
39.7%
4290 trades
Max drawdown
-$1,767
Peak to trough
A few notes on these numbers
Methodology
Backtests replay a 30-day window of Kalshi orderbook data at minute resolution, routing each order through the same matching logic that runs live. Fees are modeled at the venue's published taker rate. Simulated P&L is the sum of realized trade P&L over the window.
Starting capital
Kalshi strategies size positions directly in contracts, so ROI as a percentage of capital is not defined on the backtest summary. That's why P&L is shown in dollars rather than a percentage.
Past performance
Backtested results are hypothetical. They are derived from historical data and do not reflect live execution risks like slippage beyond the orderbook, partial fills, API latency, or venue outages. Past performance does not guarantee future results.
Not financial advice
Nothing on this page is investment, legal, or tax advice. Prediction markets carry real risk of loss. Only trade with money you can afford to lose, and do your own research before deploying any strategy live.