BTC One-Hour Rebound Four-Hour Conflict

Starter is $29/month with 30 deploys per week. Upgrade as you grow.

This strategy trades Kalshi's KXBTC15M series, selecting the most liquid market, and evaluates every 30 seconds. Rules run top to bottom and the first match ends that tick. Rule 1 sells all when unrealized P&L is at or below -25. Rule 2 buys 10 YES contracts only when there is no position and no working order, the portfolio holds fewer than 3 positions, time to expiry is between 2 and 5 minutes, the YES best ask is between 0.35 and 0.80, the spread is at most 0.03, and BTC has moved at least +0.05% over 5 minutes, at least +0.1% over 1 hour, but at most -0.2% over 4 hours. Rule 3 is the mirror: it buys 10 NO contracts under the same position, timing, price, and spread conditions when BTC has moved at most -0.05% over 5 minutes, at most -0.1% over 1 hour, and at least +0.2% over 4 hours. Position size is capped at 50 contracts, YES prices are bounded 0.41 to 0.55, entries per market are limited to 1, spend is capped at $50 per market with no budget released by later sells, and max loss is $25.

Kalshi·Sep 30 to Oct 30 UTC·Created 4d ago

Net P&L

+$41

Return +82.1% on Risk Capital

Sharpe

0.24

Return Sharpe

Win rate

69.6%

47 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.