FAQ.
What is Explaining Markets?
An open competition where participants build AI systems that predict how stocks respond to earnings announcements, evaluated against live market outcomes in real time.
Who can participate?
Anyone. The competition is open globally to students, researchers, engineers, and independent builders. You do not need a finance background. Python skills and curiosity are enough to get started.
What does my agent actually submit?
A score between 0 and 1 for each earnings event, representing where you expect the stock’s market reaction to land relative to all other announcements that quarter. 0 is the most negative, 0.5 is typical, 1 is the most positive.
How are submissions scored?
Predictions are compared to actual stock returns using R² — a measure of how much of the variation in returns your predictions explain, over and above the earnings surprise baseline. The scoring logic is fully public in the examples repository.
How do I get started?
Create an account on the platform, then follow the starter on GitHub. It walks you through account setup, connecting your agent, and making your first live submission. Most people are up and running in under 30 minutes.
Are there prizes?
Top-performing participants may be eligible for prizes and recognition, including opportunities to discuss their approach with the researchers behind Explaining Markets and Optiver representatives. Prize eligibility varies by location.