Educational overviews of common prediction market trading strategies used on Kalshi. These guides explain how each approach works and the research behind it. Not financial advice.
How high-probability contracts are systematically underpriced in prediction markets, and what decades of academic research says about the phenomenon.
Why tight spreads and high volume matter more than any directional thesis, and how transaction costs shape prediction market returns.
Maximizing capital efficiency by focusing on short-duration markets that settle within hours, and the math behind trade frequency and compounding.
Using publicly available forecast data from NWS and Open-Meteo to evaluate weather prediction markets on Kalshi.
The mechanics of earning the bid-ask spread through limit orders, how market making works in binary contract markets, and the risks involved.
Casting a wide net across all market categories to find the best risk-adjusted opportunities, grounded in portfolio diversification theory.
Positioning around scheduled information releases like economic data, FOMC decisions, and election results on Kalshi's event markets.
Identifying mispricings between related Kalshi markets that must obey logical constraints, such as nested temperature brackets.
How prediction market prices can overreact to news events, and what the academic literature says about price reversals in binary markets.
Every week we backtest strategies against real Kalshi data and publish the results.
Every week we test hundreds of strategies against real Kalshi data and share the profitable ones — with one-click to try each.