Size-Bucketed Exit Gates

Starter is $49/month with 30 deploys per week. Upgrade as you grow.

This strategy trades Kalshi KXBTC15M markets, evaluating every 10 seconds with a position cap of 999 contracts and YES prices bounded from 0.01 to 0.99. Rules are checked top to bottom and the first match ends that tick. Rules 1–3 sell the entire position when unrealized profit exceeds 12 (at 200 contracts or fewer, with price between 0.10 and 0.90), 18 (201–600 contracts, same price band), or 50 (601 or more contracts). Rules 4–6 sell everything when unrealized loss falls below -40 (200 or fewer), -60 (201–600), or -150 (601 or more). Rules 7–14 only act when time to expiry is 7 minutes or less and enter 25 contracts: buy YES or NO on price-versus-moving-average momentum with 5-minute change and velocity thresholds and spread caps of 0.015, or on faster acceleration with wider price bands, or on tighter 0.40–0.60 directional setups, or on extreme prices (0.88+ YES, 0.12 or less NO) with a 0.03 spread cap. Entry spending is capped at 25,000 dollars per market, and later sells do not release spent budget; a 100-dollar max loss can halt and liquidate only this strategy's attributed Kalshi inventory.

Kalshi·Sep 27 to Oct 27 UTC·Created 16h ago

Net P&L

+$22,014

Return +2203.6% on Risk Capital

Sharpe

1.11

Return Sharpe

Win rate

80.2%

28839 trades

Max drawdown

-$972

Peak to Trough

A few notes on these numbers

Methodology: Backtests replay supported historical market data, usually a 30-day Studio window, and evaluate strategy rules on the available cadence. Signals can fill no earlier than the next tradable step. Taker fills use top-of-book prices or available L2 depth, with Kalshi-style fees where modeled. Queue position, latency, and future liquidity are not fully modeled. Simulated P&L is net of modeled fees over the window.
Starting Capital: Kalshi backtests use the strategy's configured max position as the risk-capital denominator. Return is computed from that configured capital, while total P&L is still shown in dollars.
Past Performance: Backtested results are hypothetical. They are derived from historical data and do not reflect live execution risks like slippage beyond the orderbook, partial fills, API latency, or venue outages. Past performance does not guarantee future results.
Not Financial Advice: Nothing on this page is investment, legal, or tax advice. Prediction markets carry real risk of loss. Only trade with money you can afford to lose, and do your own research before deploying any strategy live.