ETH Entry Band

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

This strategy trades Kalshi's KXETH15M market, checking conditions every 10 seconds. Rules are evaluated in order and the first match acts alone. It exits when 10 seconds or less remain before expiry (sell everything), when a held YES position's best bid falls to 0.25 or below (sell the YES side), when a held NO position's best bid falls to 0.25 or below (sell the NO side), or when unrealized loss drops below -7 dollars (sell everything). It enters only when flat, within 12 minutes of expiry, and during the Monday–Friday 9:00–17:00 Pacific entry window; exits are not restricted to that window. A YES buy of 50 contracts requires ETH, BTC, and SOL five-minute changes each above 0.001, ETH price above both its one-hour VWAP and 12-period one-minute EMA, a positive one-minute MACD histogram, market price between 0.30 and 0.70, and spread at or below 0.015. A NO buy of 50 mirrors this with changes below -0.001, ETH price below both references, a negative histogram, and the same price band and spread cap. Position limit is 60 contracts, with prices bounded from 0.01 to 0.99.

Kalshi·Sep 14 to Oct 14 UTC·Created 13d ago

Net P&L

+$411

Return +685.7% on Risk Capital

Sharpe

0.59

Return Sharpe

Win rate

48.4%

182 trades

Max drawdown

-$73

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.