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Trades the KXETH15M market on Kalshi, evaluating every 10 seconds. It enters buy-yes or buy-no positions of 50 contracts when Ethereum price and momentum signals align with VWAP, moving averages, and tight spreads, also considering time remaining. It exits entirely at tiered take-profit or stop-loss levels based on position size, and limits total position to 100 contracts.
Over the May 14 to Jun 11 window, this custom strategy on Kalshi turned in +$20,231 of simulated profit (+20230.7% on its configured risk capital), at a 2.23 Sharpe. It placed 3565 simulated trades and won 69.5% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$182.
Under the hood it simulated 1653 Ethereum (ETH) markets, closing 988 winning and 433 losing positions after $1,747 in modeled fees, an average of 118.8 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 Ethereum (ETH) 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 Ethereum (ETH) 15-minute strategies backtested on Turbine: