Gator Quant Hacks

MAIN DESCRIPTION Gator Quant Hacks 2026Gator Quant Hacks is a national quantitative finance competition hosted by QuantED and the AlgoGators Investment Fund at the University of Florida. From October 2 to 4, 2026, students from universities across the country will spend 48 hours doing the work quants actually do: forming a hypothesis, testing it against real market data, and defending the result in front of people who do this for a living.You do not need a finance background. One of our three tracks requires no dataset and no prior markets knowledge at all. If you can write code or reason through a hard math problem, there is a place for you here.Who should competeStudents curious about quant research, trading, or systematic investing, with no prior experience neededCS, math, statistics, physics, and engineering students who like hard problemsFinance and economics students who want to test ideas with data instead of slidesAnyone who has read about quant finance and wanted a real reason to try itOpen to currently enrolled students at any U.S. university, undergraduate and graduate.TracksTrack 01: Research and Alpha DiscoveryPick a question about markets and answer it properly. Teams form a hypothesis, test it against data, and submit a written analysis alongside a live presentation to judges. Judged on the quality of the question, the rigor of the testing, honesty about what the data does and does not support, and clarity of communication. Best fit for finance, economics, and statistics students.Track 02: Quantitative Puzzles and BrainteasersA continuous point ladder running the full 48 hours. Problems in probability, combinatorics, expected value, market making, and algorithmic reasoning unlock progressively, and teams climb the leaderboard by solving them. No dataset, no setup, no finance background required. Jump in at hour one or hour thirty. Best fit for CS and math students, and the easiest way to try quant for the first time.Track 03: Systematic TradingBuild a trading strategy and backtest it on historical data provided by our data partners. Submissions are evaluated on risk-adjusted performance, including Sharpe ratio, maximum drawdown, and turnover, rather than raw return. Overfitting is the thing to beat here, and the judges will look for it. Best fit for anyone who wants to know whether their idea survives contact with out-of-sample data.Teams may enter one track. Pick the one that fits how you think.Registration and event details: gqhacks.com Join the participant Discord:https://discord.gg/PhEnUQXCp