Predictions with published reasoning
We combine quantitative probability models with transparent trade write-ups. Read the latest theses below or dig into the methodology that drives every position.
How we generate edge
A repeatable process for turning market prices, public data, and probabilistic thinking into actionable Kalshi trades.
01. Scan the market
We continuously monitor Kalshi markets and cross-reference implied probabilities with news flow, structural conditions, and alternative data sources.
02. Model the probability
Each thesis combines base rates, scenario analysis, and public data to build an independent probability estimate we can compare against the market.
03. Structure the trade
When our model diverges from the market, we size positions across YES and NO legs and maturities to maximize risk-adjusted edge.
04. Publish the reasoning
Every active trade is published with entry logic, live P&L, and a clear resolution condition. Closed trades get a full post-mortem.
From the desk
Will the Strait of Hormuz normalize by August 1, 2026?
The Hormuz Curve: A Persistent Front-Loading Anomaly
Near-term Hormuz normalization contracts have implied a 4-5x higher monthly probability than far-dated ones for over three months, and the gap hasn't closed. Forward-rate methodology, the data, and three candidate explanations.
Term Structure Trading: Rolling short-dated vs single-leg long-dated contracts
Rolling resolved short legs returned +134.8% vs +118.3% for one long-dated leg. The rolling math, the volatility term structure, exit risk, and where the edge really comes from.
Why we're short the Hormuz Traffic Normalization Markets
Insurance premiums, ongoing reroutes, Iran toll fees, and a non-finalized MOU leave the 52% normalization implied probability looking too low.