SQA Agenthon
More Information Coming Soon

Get Involved

Compete in Agenthon 2026

For industry professionals, graduate students, and academics.

Apply your skills against real quantitative-finance problems, in teams of one to three. If successful, present at the in-person final in Manhattan.

Agenthon 2026 logo
Submission Docker agent
Admissibility g0-g3 gates
Ranking Track metrics

Who it's for

Sharpen your quant skills and get seen by the industry.

Agenthon 2026 is designed for individuals eager to enhance their skills in quantitative finance and to engage with the latest advances in technology and data analysis in the financial sector. Winners gain substantial industry visibility, including with the Question sponsors, SQA member investment firms and in NeurIPS.

You compete in teams of one to three people. Only people registered here can form teams, and only these teams can feature in the leader boards.

Compete

Apply your learning and compete in Agenthon 2026. We equip you with the knowledge, tools, and data.

Question Partners

Real problems from real desks.

Agenthon Questions and Tasks are of real relevance to hedge funds and asset managers, spanning alpha forecasting, portfolio optimization, computational statistics, machine learning, and AI. Questions are provided jointly by the SQA, CEWIT and our Question Partners.

See Questions 2025 for last year's questions and a feel for Agenthon priorities.

Our Supporters

Sponsor Agenthon 2026.

A number of sponsorship tiers and opportunities are available, including monetary and awards sponsorship, event space, data, infrastructure, and compute.

Organizing Committee

Thank you from the organizers.

Lead Organizers

Christos Koutsoyannis

Chief Investment Officer, Atlas Ridge Capital
Adjunct Professor, NYU Courant
Executive Advisory Board, Columbia Business School, Program for Financial Studies

Website · LinkedIn

Pawel Polak

Assistant Professor, Department of Applied Mathematics and Statistics, Stony Brook University
Vice President, Society of Quantitative Analysts

Website · LinkedIn

Industry Co-Organizers

David Rosenberg

Head of Machine Learning Strategy, CTO Office
Bloomberg, Toronto, Canada

LinkedIn

Gary Kazantsev

Head of Quant Technology Strategy, Office of the CTO
Bloomberg, New York, USA

LinkedIn

Ioana Boier

Global Head of Capital Markets Strategy
NVIDIA Corporation, USA

LinkedIn

Track Leads

T1 · Coding

Quant-finance coding agents

Zhikang Dong
Track Lead T1
Independent Researcher

LinkedIn · GitHub

T2 · Forecasting

Reasoning-augmented time series

Ruolan Sun
Track Lead T2
Ph.D. Student, Stony Brook University

LinkedIn · GitHub

T3 · Simulation

Accelerated market simulation

Haohan Xu
Track Lead T3
Ph.D. Student, Stony Brook University

LinkedIn · GitHub

T4 · Tabular

Evidence-grounded prediction

Mathew Thiel
Track Lead T4
Quant Research Analyst, validityBase

LinkedIn · GitHub