This is a custom rule-based bot tuned to specific entry and exit conditions.
Kalshi·Mar 24 to Apr 23·Created 2h ago
Total PnL
+$21
Simulated P&L
Sharpe
7.04
Risk-adjusted return
Win rate
100.0%
16 trades
Max drawdown
-$6
Peak to trough
A few notes on these numbers
Methodology
Backtests replay a 30-day window of Kalshi 1-minute OHLC candles, evaluating strategy rules once per minute and filling simulated orders against the candle's price range. Fills are frictionless: fees, slippage, partial fills, and queue position are not modeled, so realized live P&L will be lower than the simulation. 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.