The Quant Prep is a comprehensive, open-source curriculum designed to bridge the gap between academic theory and the rigorous demands of top-tier financial firms like Jane Street, Citadel, Hudson River Trading, Optiver, and Two Sigma.
Whether you are aiming for a Quantitative Researcher role (heavy math/stats/ML) or a Quantitative Developer role (low-latency C++/systems), this repository provides the code, theory, and interview preparation you need.
| Stage | Module | Focus Area | Key Topics |
|---|---|---|---|
| 01 | Foundations | Core Skills | Linear Algebra, Probability, Algorithms, Python for Finance |
| 02 | Quant Data Analysis | Data Science | Time Series (ARIMA/GARCH), Econometrics, Exploratory Analysis |
| 03 | Financial Engineering | Mathematics | Derivatives Pricing, Black-Scholes, Stochastic Calculus, Monte Carlo |
| 04 | Machine Learning | AI/Alpha | Classical ML, Deep Learning (LSTM), NLP, Reinforcement Learning |
| 05 | Algorithmic Trading | Strategy | Backtesting, Market Microstructure, Risk Management, Stat Arb |
| 06 | Quant Development | Production | C++ Low Latency, System Design, HFT Architecture, Performance |
| 07 | Interview Prep | Cracking It | Coding Puzzles, Quant Math, Brain Teasers, Company Guides |
| 08 | Research & Resources | Deep Dives | Seminal Papers, Datasets, External Tools |
We have curated specialized resources that target the specific requirements of HFT and Prop Trading interviews.
- C++ Mastery: Order Matching Engine, Lock-Free Queue, & Memory Pool.
- Networking: UDP Market Data Receiver (Multicast & Non-blocking).
- Optimization: Microbenchmark Utils.
- Concurrency: Multithreaded Monte Carlo.
- The Roadmap: 8-Week Study Plan.
- Portfolio Construction: Black-Litterman Model (Advanced optimization).
- Stochastic Calculus: SDE Solver (Euler-Maruyama).
- Quant Strategies: Avellaneda-Stoikov MM & Pairs Trading.
- Visual Intuition: Options Greeks Dashboard.
- Jane Street Guide: Probability & Betting.
Ensure you have conda installed.
-
Clone the Repository
git clone https://github.com/shreejitverma/The-Quant-Prep.git cd The-Quant-Prep -
Set Up Environment
conda env create -f environment.yml conda activate quant_prep_env
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Run a Backtest Navigate to
05_algorithmic_tradingand try running a sample strategy to verify your setup.
This is a community-driven project. We welcome contributions! Please read our Contributing Guidelines before submitting a Pull Request.
- Bug Reports: Open an issue if you find a mistake.
- New Content: Have a unique trading strategy or a better explanation of Ito's Lemma? Submit it!
Maintained by: Shreejit Verma