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Position-Graded Profit Ratchet

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

On Kalshi's KXBTC15M market it picks the most liquid contract and checks conditions every 10 seconds, with a 500-contract cap and prices allowed from 0.01 to 0.99. Rules run top to bottom and the first match ends that tick: at 500 contracts it skips; otherwise it sells everything when unrealized profit exceeds 12 with size up to 100, exceeds 18 with size 101 to 300, or exceeds 50 with size 301 or more, and sells everything when losses go past 25, 40, or 60 for those same size bands. Entries use Coinbase BTC-USD data (price, 1-hour VWAP, 5-minute change, 1-minute EMA and SMA, 15-minute high and low, 1-minute velocity) refreshed every 5 seconds, all requiring size at or below 250. It buys 50 yes or no contracts on price versus VWAP and EMA moves, on 5-minute change past 0.0015 with matching velocity, near expiry within 5 minutes at mid prices, or near expiry at extremes above 0.88 or below 0.12 against the 15-minute high or low, each with its stated price and spread limits.

Kalshi·Sep 7 to Oct 7 UTC·Created 20d ago
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Turbine Studio

Your next trade is a sentence away.

Describe an idea, review the backtest, and start from the same workspace.

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Net P&L
+$7,180
Return +1436.0% on Risk Capital
Sharpe
0.40
Return Sharpe
Win rate
61.3%
9661 trades
Max drawdown
-$1,920
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.