Forecast Breakout

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

This Kalshi strategy trades the KXHIGHNY series and checks conditions every 60 seconds. Its position limit is 5 contracts, with a YES price floor of 0.1 and ceiling of 0.9; other runtime checks may also block orders. Rules are evaluated top to bottom and the first match ends that tick. Rule 1 buys 5 YES contracts when the NYC forecast high is above 77, price is below 0.42, and spread is below 0.08. Rule 2 sells all when price is above 0.6 and a position exists. Rule 3 sells all when the forecast high is below 73 and a position exists. Rule 4 sells all when time to expiry is under 30 minutes and a position exists. Rule 5 sells all when unrealized loss is below -25.

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

Net P&L

-$2

Return -39.2% on Risk Capital

Sharpe

-0.12

Return Sharpe

Win rate

28.6%

14 trades

Max drawdown

-$6

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.