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On Kalshi's KXBTC15M market, it evaluates every 10 seconds. It buys 500 yes or no contracts when Bitcoin momentum and price versus moving averages align, with contract price 0.20-0.80 and tight spread, or near expiry under certain conditions. It exits using tiered take-profit or stop-loss based on unrealized PnL and position size; total position never exceeds 2000.
Over the May 14 to Jun 11 window, this custom strategy on Kalshi turned in +$518,758 of simulated profit (+25937.9% on its configured risk capital), at a 2.15 Sharpe. It placed 5381 simulated trades and won 67.6% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$2,051.
Under the hood it simulated 1653 Bitcoin (BTC) markets, closing 1129 winning and 542 losing positions after $33,660 in modeled fees, an average of 179.4 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 30-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 30 days (May 14 to Jun 11). 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.
Compare other Bitcoin (BTC) 15-minute strategies backtested on Turbine: