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This strategy trades Kalshi's KXZEC15M series, checking conditions every 10 seconds and capping positions at 100 contracts, with YES/NO ask prices limited to the 0.83–0.99 range. Rules run top to bottom and the first match ends that tick. Rule 1 cancels all resting orders when orders exist and no position is held. Rules 2 and 3 exit an existing YES or NO position respectively when that side's best bid falls to 0.50 or below. Rules 4 and 5 enter with 100 contracts only when flat, with 60 seconds or less to expiry, a spread of 0.03 or less, the ask within 0.83–0.99, and a full set of ZEC signals aligned: for YES, price above the 1-hour VWAP, the 12-period 1-minute EMA above the 20-period 1-minute SMA, and positive 1-hour, 15-minute, 5-minute changes and 1-minute velocity; for NO, all of these reversed. Rules 6 and 7 enter 100 contracts when flat, with 0 to 60 seconds to expiry, a tighter spread of 0.01 or less, the ask within 0.83–0.99, and only 1-minute velocity positive (buy YES) or negative (buy NO). Rule 8 cancels all orders once expiry is reached.
Over the Sep 22 to Oct 22 window, this custom strategy on Kalshi turned in +$517 of simulated profit (+517.2% on its configured risk capital), at a 0.98 Sharpe. It placed 154 simulated trades and won 98.7% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$78.
Under the hood it simulated 2665 prediction-market markets, closing 76 winning and 1 losing positions after $42 in modeled fees, an average of 5.1 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 prediction-market markets on Kalshi's short-horizon series across 30 days (Sep 22 to Oct 22). These are short-horizon contracts that open and settle on a fixed short-horizon cadence, so the strategy is measured across many independent events rather than one long trend. Rules are evaluated once per short-horizon 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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