Open to students, researchers, engineers and independent builders, the competition asks participants to develop AI systems that respond to live earnings announcements.
Learning through an evolving problem
Over the course of a quarter, entrants will build their systems and see how they perform as earnings are released. Each result provides evidence they can use to revisit their approach and refine their solutions.
“Earnings announcements are a genuinely hard prediction problem, with real uncertainty, rich data and a clear outcome that shows whether you were right. That feedback loop is one of the best teachers there is. It also reflects what we value in our own people: not who has the cleverest first idea, but who keeps learning and updating when the data disagrees.”
By the end of the competition, they will have gained hands-on experience on a project that documents how their thinking developed. Anyone with basic Python skills and an interest in AI can take part, giving a wider group the opportunity to engage with an active area of research.
Supporting open AI research
Explaining Markets takes on an ambitious question about how AI can help explain the relationship between new information and market outcomes. By bringing a range of technical and academic perspectives to the same problem, the platform creates a shared foundation for advancing meaningful research progress.
We’re proud to support the competition and look forward to seeing what participants build.
