Double Dose of Datathons
What’s better than one Datathon? How about two?!
On Friday April 19, Quantbot was thrilled to participate in Schonfeld’s Early Engagement Summit PhD Datathon. Using Code Willing’s dynamic data processing and modeling platform, PhDs from around the country worked in competing groups to find and model alpha signals from pre-determined datasets. This event gave PhD candidates, whose disciplines ranged from Mathematics and Statistics to Economics, the opportunity to test quantitative methods on real financial data, and to encourage their future engagement in the Quant space.
Ashar welcomes PhD candidates before the Schonfeld Datathon
Quantbot employee, Greg, mentors his team through the Schonfeld Datathon
The winning Schonfeld Datathon team
Since everything comes better in pairs, the very next day Quantbot sponsored a separate Datathon at Carnegie Mellon, also powered by Code Willing’s platform. Participating students came from either CMU’s Computational Finance Master’s program (MSCF) or their undergraduate Math program. It was a victory for MSCF since a group of their students took home the top prize, but the 2nd-place undergraduates were equally competitive. After introducing the students to each competition, Ashar Mahoob, Quantbot’s CIO, handed out the prizes on both days to the winning teams. We were thrilled to foster an interest in Quant Finance in all the students, from PhD to undergrad, and we hope they will consider it as a viable career option. We are excited to repeat our success in future!
Quantbot mentor, Rui, celebrates with her winning team at the CMU Datathon
The official victory photo of the CMU Datathon-winning team
Some thoughts from the Quantbot mentors:
Mentoring cwiq-team-central was extremely rewarding. They are a bright and enthusiastic group of students who worked together quite well and sought my guidance regularly. I think the most important lessons I hope the team took away are how rich the field of alpha research is in terms of the breadth of both datasets and the machine learning techniques that can be applied, and how powerful Quantbot’s platform is for quickly developing new ideas and evaluating their performance. – Greg Sternberg
It was a rewarding experience mentoring the winning team, cwiq-team-code. They were a group of motivated young professionals who were highly collaborative and eager to learn. I was amazed by the abundance of brilliant ideas they tested in such a short time. The Quantbot platform proved indispensable in handling these computationally heavy and data-intensive tasks. I hope this victory will inspire them to take on even more interesting and critical challenges that impact global markets – Rui Xiong, Datathon winning team mentor
And an afterword from our CIO, Ashar:
Quantbot Hackathon 2024 provided CMU’s Masters and Undergrad students a first-hand opportunity to work on a real-life alpha research project, under tight time and budget constraints, using real world datasets. I wish I had had an opportunity to participate in such a project when I was completing the MSCF program at CMU years ago. The students had a fun day of learning and competing. Additionally, all the mentors were very impressed by how well the students coordinated the research process and were able to come up with out-of-sample model performance that was in-line with observed performance in-sample.
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