Stop Distance Test

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

This strategy trades the most liquid KXETH15M market on Kalshi and evaluates every 30 seconds, with a position limit of 53 contracts and YES prices confined to 0.05–0.95. Rules are checked top to bottom, and the first match fires and ends that tick. Rule 1: if YES position size is above zero, sell the selected fill's remaining YES quantity, but only when the executable bid on that side is at or below that fill's actual purchase price minus 0.1; gaps can fill lower, and it never flattens unrelated fills. Rule 2 applies the same per-fill stop logic to NO positions. Rule 3: between 3 and 1 minutes to expiry, with no YES or NO position, spread under 0.03, YES best ask under 0.6, and ETH price above its 12-period 1-minute EMA while 1-minute MACD is above its signal line, buy 50 YES immediately-or-cancel. Rule 4: same expiry window and flat conditions, spread under 0.03, NO best ask under 0.6, and ETH price below its EMA while MACD is below its signal line, buy 50 NO. Entry orders are capped at one entry per market and $50 notional per market; spent budget is not released by later sells.

Kalshi·Sep 12 to Oct 12 UTC·Created 15d ago

Net P&L

+$534

Return +1008.0% on Risk Capital

Sharpe

0.30

Return Sharpe

Win rate

33.0%

986 trades

Max drawdown

-$289

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.