ETH Kalshi Mean Reversion

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.