Our Mission

The Princeton Quant Trading Conference seeks to bring together a unique cross-section of the leading experts from academia, industry, and government in a relaxed intellectual environment to catalyze discussions and strengthen ties across traditional boundaries. We will cover subjects ranging from high-frequency algorithmic trading and statistical arbitrage to model construction and validation. This event also provides a unique opportunity for leaders and students in quant trading related fields to directly interact.

The student and young alumni organizing committee is exclusively volunteer and 100% of all proceeds go to support education nonprofits fighting for economic mobility for underprivileged students. We’re building a legacy for the conference that extends beyond the ivory tower into the greater community.



Michael Li
Princeton University
Pablo Garcia
Columbia University '14
Raymond Perkins
Princeton University GS '17
Saikrishna Poddutur
University of Illinois - Urbana Champaign '15
Kaity Kratsios
Princeton University
Marius Constantin
Yale University GS '20
Katelyn Schoenberger
Loyola University '19
Zlata Chernyshenko
Rensselaer Polytechnic Institute '16
Neda Karami Mohammadi
Northeastern University '18
Jahanavi Gupta
Penn State University '19
Jia Yue Gao
Columbia University GS '16

Frequently Asked Questions

How technical is this conference going to be? Will there be lots of math I don’t understand?

The talks are geared towards students who are interested in trading but who don't necessarily know a lot about the topic. We usually have a variety of technical and non-technical talks for students of all backgrounds.

Is this event only for Princeton students?

We welcome students from all universities, as well as non-students.

Who is this event open to?

We welcome undergraduate, masters, MBA, PhDs, and Postdocs. In addition, a small number of tickets are made available for faculty and industry.

What is the appropriate dress code for this conference?

This conference is business casual.

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