Quant Research Guide
A practical study guide for aspiring quant researchers — research workflow and interview prep for QR / research-intern roles, and for self-study. Each topic is a short page, not a textbook chapter.
How to use this guide
- Each topic in the left nav is a standalone page you can read in ~10 minutes.
- Every page follows the same shape: why it matters, core concepts, a mental model, interview questions with brief answer keys, and a short watch list of verified YouTube videos.
- Topics are ordered as a research workflow: from the question, through data, alpha, and testing, to how you present the work. You can read them in order, or jump straight to the topic you need.
- Nothing here requires a backend, an API key, or a login — it’s just reading.
Roadmap
| # | Topic | Interview |
|---|---|---|
| 01 | Research question & hypothesis | Occasional |
| 02 | Data hygiene & survivorship | 🎯 Frequent |
| 03 | Exploratory analysis | Occasional |
| 04 | Factor models | 🎯 Frequent |
| 05 | Alpha construction | 🎯 Frequent |
| 06 | Backtest design | 🎯 Frequent |
| 07 | Backtest pitfalls | 🎯 Frequent |
| 08 | Statistical significance & multiple testing | 🎯 Frequent |
| 09 | Portfolio construction | Occasional |
| 10 | Risk models | Occasional |
| 11 | Execution & TCA | Background |
| 12 | Research notebooks & reproducibility | Occasional |
| 13 | Presenting research | Occasional |
| 14 | Interview case patterns | 🎯 Frequent |
Contributing
See CONTRIBUTING.md. Short version: keep topics tight, verify every link yourself, don’t invent scope.