Resource Guides
Everything you need to explore quant — from your first 30 days to TAMU course maps, firm research, and what AggieQuant actually looks for. Start here. Go deep when ready.
If you're new to quant, use these in order. Start with the first 30 days, build a realistic quant plan for this semester, map the TAMU classes that fit your track, use the firm and role database to narrow what kind of work you actually want, then read what AggieQuant looks for before you stress about polish.
Start Here
The core onboarding sequence
Roadmaps & Downloads
More resources
Track-Based Reading Lists
Resources by role
Curated books, interview prep material, and reference resources for each track. These are the things that compound — start early and come back often.
Build trading infrastructure, wrangle data, and turn strategy ideas into dependable systems.
See full track- Effective Modern C++ Modern C++ habits, ownership patterns, and performance-minded coding style.
- Designing Data-Intensive Applications Systems thinking, data flow, and reliability under scale.
- Python for Data Analysis A practical bridge between engineering work and quant research tooling.
- Green Book (Ch. 2, 4, 5) Ch. 2 for brainteasers, Ch. 4 for probability, Ch. 5 for stochastic vocab.
- Data Structures & Algorithms in C++ Arrays, maps, heaps, graphs, and complexity tradeoffs should feel automatic.
- Multithreading & Memory Concurrency, race conditions, cache behavior, and latency bottlenecks.
- Linux, SQL & Scripting A lot of quant engineering work lives in the shell and in data pipelines.
- cppreference + C++ Core Guidelines Keep these close when tightening up language fundamentals.
- System Design Primer Architecture, service boundaries, and production tradeoffs.
- NumPy / pandas Docs The fastest way to sharpen data engineering instincts for quant workflows.
Fast decision-making, probability, game theory, and developing intuition under pressure.
See full track- Trading and Exchanges Market microstructure, the order book, liquidity, and how trading venues really work.
- Heard on the Street Classic quant-style problems with a strong fit for trader interviews.
- Thinking in Bets Separating decision quality from short-run outcomes.
- Green Book (Ch. 2, 4, 5) Ch. 2 for brainteasers, Ch. 4 for EV and conditional probability, Ch. 5 for option intuition.
- Mental Math & Fast Arithmetic Percent changes, fractions, expected values, and approximations must be second nature.
- Probability & Game Theory Conditional probability, Bayes, EV, and strategic reasoning problems.
- Market-Making Conversations Be ready to explain how you'd price, size, hedge, and react under uncertainty.
- Trading Competitions Guide Build trading intuition and signal focused interest to recruiters.
- Daily Mental Math Drills A few minutes of repetition every day beats occasional marathon prep sessions.
- Mock Quoting Games Practice making two-sided markets and defending your logic out loud.
Build models, test ideas, and turn noisy data into repeatable signals.
See full track- Introduction to Statistical Learning Practical foundation for modeling, validation, and statistical intuition.
- The Elements of Statistical Learning A deeper reference once you want more theory behind the tools.
- Advances in Financial ML Best treated as a source of research ideas and pitfalls, not a first textbook.
- Green Book (Ch. 2, 4, 5) Ch. 2 for problem-solving, Ch. 4 for distributions, Ch. 5 for stochastic modeling.
- Statistics, Linear Algebra & Optimization Regression, matrix intuition, estimators, and bias-variance tradeoffs come up constantly.
- Time Series Thinking Autocorrelation, stationarity, overfitting, and regime changes matter more than flashy models.
- Research Communication Explain a hypothesis, an experiment, and why the result might be lying to you.
- pandas, NumPy, scikit-learn, statsmodels Default toolkit for early-stage quant research work.
- Replication Projects Rebuild a paper or strategy from scratch to sharpen both rigor and skepticism.
- Research Notebooks with Clear Writeups Your edge grows faster when experiments are reproducible and easy to critique.
Quant Dictionary
Industry jargon, translated
Start with , , , , , , and for plain-English explanations.
No terms match that search yet. Try alpha, latency, or market making.
Have programs or updates to share? Shoot an email to bago2007@tamu.edu.