How it works

How Q forecasts, selects Signals, and learns from every resolved outcome.

Resolved markets

Every market Q forecast that has since resolved, with Q’s probability, the venue price it was scored against, and how the market settled.

Download CSVLast 60 days · 1,009 forecasts · 173 markets

Q turns any question into a calibrated probability.

  1. 01Classify the questionResolution rule, horizon, and question type.
  2. 02Map the landscapeActors, assets, linked markets, and related questions.
  3. 03Research the evidenceCheck the sources behind each claim.
  4. 04Build scenariosBase rates, pathways, dependencies, and disconfirming evidence.
  5. 05Produce the forecastA calibrated probability with uncertainty and cited analysis.

Signal selection

Q generates many forecasts. The best ones become Signals. Q curates markets where it sees a large spread and short-term catalysts that it believes will move the market in its direction.

  1. 500forecasts / day
  2. 100spread > 10pp
  3. 50meaningful liquidity
  4. 10resolve within a week

Q gets better over time.

Learning loop

Score each outcome

Compare Q and the forecast-time market price with the resolved result.

Diagnose the error

Trace the evidence, expert weights, and missing inputs behind the miss.

Feed the next model

Turn repeatable findings into fine-tuning and data changes.

Resolve · score · fine-tune · forecast again