Late Favorite Hard Stop

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

This Kalshi strategy trades the KXHYPE15M market, checking conditions every 10 seconds with a maximum position of 10 contracts and a YES price band of 0.91 to 0.99. Rules run in order and the first match ends that tick. Rule 1 sells YES when a YES position exists and the YES best bid is at or below 0.55; Rule 2 sells NO when a NO position exists and the NO best bid is at or below 0.55. Rules 3 and 4 enter only when position size is zero, time to expiry is between 0 and 30 seconds, spread is at most 0.03, and the relevant best ask (YES for Rule 3, NO for Rule 4) is between 0.91 and 0.99, buying 10 contracts of that side. Rule 5 cancels all orders once time to expiry is zero or less. Other runtime checks may prevent orders.

Kalshi·Sep 18 to Oct 18 UTC·Created 9d ago

Net P&L

-$14

Return -141.6% on Risk Capital

Sharpe

-0.20

Return Sharpe

Win rate

86.0%

86 trades

Max drawdown

-$21

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.