Rutgers Quantitative Finance Club
Bridging the gap between academic theory and industry practice for the next generation of Rutgers quants
Bridging the gap between academic theory and industry practice for the next generation of Rutgers quants
Our goal is to bring quant lessons and opportunities to Rutgers students. This includes workshops on core quantitative skills spanning mathematics, finance, and computer science, as well as recruiting/speaker events and competitions to show off your own skills.
Through our wide range of events, we hope to expose club members to the exciting world of quant, while preparing them to break in. Sounds good? Check out our contact page to get in touch!
"Quant" isn't one skill, it's three disciplines working together. Everything we do at the club builds toward one of these three pillars.
Computer Science
Turning models into working software: building backtesting engines, trading bots, and the infrastructure that runs them. This is the muscle behind projects like our RL Trading and CNN limit-order-book research teams, and the custom Rust exchange powering Trade the Knight.
Finance
Understanding markets well enough to trade them: pricing risk, managing a portfolio, and reading order flow under pressure. This is what Trade the Knight tests directly, and what our RTQF program builds toward from the ground up.
Mathematics
The theory underneath it all: stochastic calculus, statistics, and the models that describe how markets actually behave. This is where our Research Teams live, tackling papers on volatility surfaces, options pricing, and statistical arbitrage.
New Semester, New Lineup
We're just getting rolling this semester. Here's what we're building toward — exact dates drop on Discord and GroupMe first.
Round Two
After 250+ applicants and $5,000+ in prizes last year, we're building an even bigger algorithmic trading competition for this year.
Forming Now
New teams are forming to tackle fresh papers across ML pricing, RL trading, volatility modeling, and more. No experience required.
Coming Soon
Our RTQF curriculum returns this year with a stronger scaffolded timeline, taking members from fundamentals to industry-ready concepts.
In the Works
We're reaching out early to companies and alumni to line up recruiting sessions, workshops, and networking nights for the year ahead.
Weekly
Workshops, competitions, and destressers covering the math, finance, and code behind quant — kicking off soon.
Stay in the Loop
Every date and announcement lands on Discord and GroupMe before anywhere else.
Year One Recap
The Inaugural Rutgers Algorithmic Trading Competition — and we're just getting started.
250+
Applicants
80+
Participants
$5,000+
In Prizes
Trade the Knight is the Rutgers Quantitative Finance Club's premier, high-stakes algorithmic trading competition. Designed to simulate the fast-paced environment of modern financial markets, this day-long event challenged the brightest minds at Rutgers to develop, backtest, and deploy automated trading strategies in a live, competitive setting.
Teams competed to optimize PnL and risk-adjusted returns by uploading custom bots. From 250+ applicants, 80+ traders made it to the floor to compete for over $5,000 in prizes. This was just our first year — we're already working to make the next one bigger.
Date
April 18th, 2026
Location
Rutgers Business School
Duration
8 hours of intensive coding, strategy, and execution
Capacity
80 Traders
Unlike standard competitions, Trade the Knight runs on a proprietary, high-performance exchange and brokerage platform built from scratch in Rust. The platform features low-latency order matching and realistic latency simulation to mimic professional-grade trading infrastructure.
Trade the Knight aims to bridge the gap between academic theory and industry practice, providing Rutgers students with a platform to showcase their skills in stochastic modeling, software engineering, and financial intuition.
Registration for this year's competition isn't open yet. Join our Discord or GroupMe to be the first to know when applications launch.
Learn to translate academic papers into working code
Research Teams are small groups of 2-3 members who work together to explore, understand, and implement quantitative finance papers. Each team will:
The Goal
The primary focus is learning. We want to help members develop the skill of translating academic research into practical, working code. It is a crucial ability for anyone pursuing a career in quantitative finance.
Replicates empirical asset-pricing ML research, comparing OLS, neural network, and tree-based models to predict stock returns via expanding-window backtests scored on portfolio Sharpe ratio.
Team Members
Builds a custom Gym trading environment for a 30-stock portfolio and trains A2C and DDPG reinforcement-learning agents to manage it under transaction costs.
Team Members
A staged, week-by-week implementation of Longstaff-Schwartz least-squares Monte Carlo for pricing American put options, building from a GBM simulation engine up through the full regression-based exercise-boundary pipeline.
Team Members
Implementing the Heston stochastic volatility model for option pricing, starting from a Black-Scholes baseline to benchmark pricing accuracy before layering in stochastic vol.
Team Members
Calibrating the Hagan et al. SABR volatility model to live SPX/SPY options data, fitting smile curves and building a full 3D implied-volatility surface.
Team Members
Simulates quantum-refereed trading games (Prisoner's Dilemma, Chicken) in Qiskit, showing how quantum entanglement can unlock trading equilibria unreachable by classical strategies.
Team Members
Applying convolutional neural networks to limit order book data for short-term price prediction. Currently in the literature-review and scoping stage.
Team Members
Implements and backtests Avellaneda & Lee's (2010) PCA-based statistical arbitrage strategy: extracting idiosyncratic residuals via factor regression, modeling them as mean-reverting OU processes, and trading market-neutral reversion bets hedged against SPY.
Team Members
Estimates the Hurst exponent of realized volatility from Oxford-Man Institute realized-variance data to test the rough volatility hypothesis.
Team Members
Sign up below to be placed on a team. No prior research experience required: just curiosity and willingness to learn!
Signups reviewed on a rolling basis
We're grateful for the support of our incredible sponsors who make our events and initiatives possible.
Merch provided by Optiver
Interested in sponsoring our club or events? We offer various partnership opportunities including event sponsorships, merchandise partnerships, and more.
Want to join the club? Join the GroupMe and Discord for primary contact and follow the Insta for reminders and updates. Feel free to reach out to our email with any questions!
Email: rutgersqfc@gmail.com
