Strategy labs & research ideas.

As a new club, these are planned tracks — not things we’ve already run. They’re meant to give you a sense of what we’ll explore once we have a cohort.

Track A • Market making

Limit order book simulator

Build a simple LOB simulator and experiment with quoting strategies: inventory control, spread management, and adverse selection. Everything based on reproducible toy data, not live trading.

Track B • Stat arb

Pairs & cross-sectional signals

Explore mean reversion and relative value strategies on equities or ETFs using free or student-accessible datasets. Emphasis on clean code and careful assumptions.

Track C • Vol & derivatives

Surface analysis & simple vol trades

Analyze implied vol surfaces, skew, and term structure using public examples and small datasets. Implement basic volatility strategies and scenario analysis — purely on paper/backtests.

Sample project timeline (planned).

A rough sketch of what an 8–10 week project might look like once the club is running.

Week 1–2 · Scoping & data
Define the problem, pick a universe, and set basic success metrics. Get data into Python notebooks; clean & explore.
Week 3–4 · First pass model
Implement a baseline strategy and run basic backtests. Focus on correctness and robustness over performance.
Week 5–6 · Refinement
Add risk controls, performance attribution, and visualization. Introduce transaction costs and simple execution assumptions.
Week 7–8 · Polish & presentation
Prepare slides/dashboards, stress-test assumptions, and present to the club or invited mentors for feedback.