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Midprice Breakout Tiered Exit

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This Kalshi strategy trades the 15-minute SOL market and evaluates every 10 seconds, with a maximum position of 500 contracts and prices bounded between 0.01 and 0.99. Rules are checked top to bottom and the first match ends that tick: if position size is at least 500 it skips. Exit rules then sell the entire position based on position size and unrealized profit or loss tiers: at 100 contracts or fewer it exits on profit above 12 or loss below -12 (profit only when price is between 0.10 and 0.90); between 101 and 300 contracts it exits on profit above 18 or loss below -18 (profit again price-bounded); at 301 or more it exits on profit above 50 or loss below -50. Entry rules require position size at 250 or fewer and buy 100 contracts each: buy YES when the SOL price is at or above its 15-minute high with market price between 0.35 and 0.65 and spread at or under 0.01, buy NO when SOL is at or below its 15-minute low under the same price and spread conditions, and near expiry (5 minutes or less) buy YES at price 0.88 or higher or buy NO at 0.12 or lower when SOL is at its high or low respectively with velocity confirming direction and spread at or under 0.03.

Kalshi·Sep 20 to Oct 20 UTC·Created 7d ago
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Net P&L
+$3,246
Return +649.2% on Risk Capital
Sharpe
0.71
Return Sharpe
Win rate
75.4%
1443 trades
Max drawdown
-$503
Peak to Trough

What This Backtest Shows

Over the Sep 20 to Oct 20 window, this custom strategy on Kalshi turned in +$3,246 of simulated profit (+649.2% on its configured risk capital), at a 0.71 Sharpe. It placed 1443 simulated trades and won 75.4% of them — a high hit rate — against shallow worst peak-to-trough drawdown of -$503.

Under the hood it simulated 2717 Solana (SOL) markets, closing 306 winning and 100 losing positions after $998 in modeled fees, an average of 48.1 trades a day. That trade-by-trade detail, the equity curve above, and the full rule set below are what separate this page from a one-line leaderboard entry.

Net PnL is the headline here; the Sharpe is unannualized over this short window, so read it as a within-sample texture of the equity curve rather than an industry-standard risk score. Because every figure comes from a single 30-day historical replay, it is best treated as a hypothesis to pressure-test rather than a forecast — the same rules can behave very differently once live fills, API latency, and shifting volatility enter the picture.

Market and Data Window

This backtest runs against Solana (SOL) markets on Kalshi's 15-minute series across 30 days (Sep 20 to Oct 20). These are short-horizon contracts that open and settle on a fixed 15-minute cadence, so the strategy is measured across many independent events rather than one long trend. Rules are evaluated once per 15-minute candle, and a signal can fill no earlier than the next tradable candle at top-of-book prices, net of Kalshi-style taker fees.

Related Backtests

Compare other Solana (SOL) 15-minute strategies backtested on Turbine:

  • The Best One (SOL) — 0.10 Sharpe, +$5,278 simulated PnL
  • The Best One (SOL) — 0.51 Sharpe, +$3,675 simulated PnL
  • The Best One (SOL) — 0.20 Sharpe, +$3,020 simulated PnL

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.