How one event moves another.
Most forecasts price one question at a time. Consequitur maps the relationships between them—a directed graph of conditional probabilities across event outcomes, with an AI baseline you can correct.
For this beta, the graph covers a focused set of macro events—the Fed's 2026 rate path and the data that moves it. More domains to follow.
If a CPI print runs hot, does the Fed still get rates down to 3.50%? If the US–Iran ceasefire holds, does Brent stay below $100? Those are conditional questions, and nothing prices them directly. Consequitur does: each link between two events carries a conditional probability—seeded by a model, refined as readers register their own.
How it works
1. Trace the network.
Start from any event and follow its catalysts and the events it influences. Each connection shows the probability shift it implies.
2. Register your read.
Disagree with a link? Submit your estimate. The consensus updates as readings accumulate—no account, no signup.
3. Run a scenario.
Set an event's outcome and watch the projection ripple through everything connected to it.
If you hold event contracts, the graph is your catalyst map: an event's upstream table is the calendar of prints and decisions that can reprice it, and each dependency is the size of the repricing to expect if one resolved YES today.
Free to explore. Free to share by link. Built by Quantcha.
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