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This strategy trades Kalshi's fifteen-minute DOGE market, evaluating every 10 seconds against Coinbase DOGE-USD data refreshed every 5 seconds, with a 50-contract position cap and YES prices bounded 0.01 to 0.99. Rules are checked top to bottom and the first match ends that tick: rule 1 cancels all orders when position size is zero but orders exist; rules 2 and 3 sell each individual YES or NO fill when its bid falls to that fill's purchase price minus 0.20, and rules 4 and 5 sell each fill when its bid reaches that fill's purchase price plus 0.15 before fees, with gaps able to fill lower or higher and only the selected fill's remaining quantity sold. Rules 6 through 13 buy 25 contracts, each only when the opposite side is flat, no orders are working, and expiry is within 5 minutes, using DOGE price versus its one-hour VWAP and one-minute averages, five-minute change bands (0 to 0.005, 0.005 to 0.0075, above 0.0075, and mirrored negatives), one-minute velocity direction, price ranges, and spread caps of 0.075 or, for rules 12 and 13, 0.15. Entry orders are capped at 10 per market.
Over the Sep 19 to Oct 19 window, this custom strategy on Kalshi turned in +$737 of simulated profit (+1475.0% on its configured risk capital), at a 0.45 Sharpe. It placed 2993 simulated trades and won 67.1% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$129.
Under the hood it simulated 2642 Dogecoin (DOGE) markets, closing 754 winning and 370 losing positions after $279 in modeled fees, an average of 99.8 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 Dogecoin (DOGE) markets on Kalshi's 15-minute series across 30 days (Sep 19 to Oct 19). 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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