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This bot posts two-sided limit orders on your chosen market to capture the bid-ask spread plus Kalshi's maker rebate.
Over the Mar 29 to Apr 20 window, this spread capture strategy on Kalshi turned in +$1,708 of simulated profit (+1708.4% on its configured risk capital), at a 0.05 Sharpe. It placed 116588 simulated trades and won 97.8% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$74.
Under the hood it simulated 2076 Bitcoin (BTC) markets, closing 575 winning and 13 losing positions after $951 in modeled fees, an average of 5299.5 trades a day. That trade-by-trade detail, the equity curve above, and the full rule set below are what separate this page from a one-line leaderboard entry.
Net PnL is the headline here; the Sharpe is unannualized over this short window, so read it as a within-sample texture of the equity curve rather than an industry-standard risk score. Because every figure comes from a single 22-day historical replay, it is best treated as a hypothesis to pressure-test rather than a forecast — the same rules can behave very differently once live fills, API latency, and shifting volatility enter the picture.
This backtest runs against Bitcoin (BTC) markets on Kalshi's 15-minute series across 22 days (Mar 29 to Apr 20). These are short-horizon contracts that open and settle on a fixed 15-minute cadence, so the strategy is measured across many independent events rather than one long trend. Rules are evaluated once per 15-minute candle, and a signal can fill no earlier than the next tradable candle at top-of-book prices, net of Kalshi-style taker fees.
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