Forecast Breakout

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This strategy trades Kalshi markets in the KXHIGHNY series and re-evaluates every 60 seconds, with a maximum position of 30 contracts and a permitted YES price range of 0.1 to 0.9; other runtime checks may also block orders. Rules are checked in order and the first matching one fires, ending that tick. Rule 1 buys 6 YES contracts when the NWS forecast high for New York (station KLGA) is above 77, the price is below 0.42, and the spread is under 0.08. Rule 2 sells the entire position when price is above 0.6 and a position exists. Rule 3 sells the entire position when the forecast high drops below 73 and a position exists. Rule 4 sells the entire position when less than 30 minutes remain to expiry and a position exists. Rule 5 sells the entire position when unrealized profit/loss falls below negative 25.

Kalshi·Oct 1 to Oct 31 UTC·Created 3d ago

Net P&L

-$19

Return -62.8% on Risk Capital

Sharpe

-0.28

Return Sharpe

Win rate

16.7%

36 trades

Max drawdown

-$33

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.