TurbineMangrove
POWERED BY TURBINEFI
All StrategiesResearchCommunity
Pricing
Kalshi TradingPolymarketAI Strategy BuilderBacktesting EngineSandbox RuntimeEdge Data FeedsStrategy LibraryBacktested StrategiesLive Performance
BlogXDiscord
AffiliatesMerchDocs
Pricing
← Strategies
← Strategies

VWAP-Anchored Consensus Entry

Starter is $19/month with 10 deploys per week. Upgrade as you grow.

On Kalshi's most-liquid 15-minute SOL market, the strategy checks every 10 seconds. It sells an existing YES or NO position if that side's best bid falls to 0.25 or below, and otherwise buys 10 contracts of YES or NO only when flat, within 10 minutes of expiry, that side's ask is between 0.45 and 0.55, and SOL, BTC, and ETH five-minute changes plus SOL trend and price-versus-average conditions all agree in that direction; with no position it cancels all orders. Risk caps size at 10 contracts and prices between 0.05 and 0.95.

Kalshi·Aug 11 to Sep 9·Created 8d ago
Share to XShare to Reddit
Turbine Studio

Your next trade is a sentence away.

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

Build a bot
Net P&L
+$32
Return +317.5% on risk capital
Sharpe
0.17
Return Sharpe
Win rate
42.9%
280 trades
Max drawdown
-$49
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.