The Quant Roadmap

Every topic, in the right order

Nearly every subject across five disciplines, structured into three levels of mastery — each with clear, actionable goals so you always know when you're ready to level up.

5Disciplines
3Levels
3Career tracks
The Path

Five disciplines, three levels of depth

Pick a target role to see exactly how deep you need to go.

Target role
Computer Science Lowest barrier to entry — start here
  1. L1 Target Programming fundamentals, data types & structures, control flow, functions, the command line, version control, basic web (HTML/CSS/JS). Read & write code — build anything from scratch.
  2. L2 Target Data structures & algorithms, Big-O, sorting/searching, dynamic programming, OOP, databases & password hashing. Crush the quant-dev knowledge round (LeetCode-style).
  3. L3 Target Low-latency architecture, numerical optimization, concurrency & threading, distributed systems, market-data & execution pipelines. Ship high-performance production systems.
Mathematics The axe you must keep sharp
  1. L1 Target Algebra & geometry, functions, polynomials, exponents & logs, coordinate geometry, basic proofs. Model & solve deterministic problems.
  2. L2 Target Calculus I–IV, optimization, multivariable calculus, gradients, linear algebra, matrix decompositions (eigen/SVD/PCA). Set up & solve optimization problems.
  3. L3 Target Stochastic calculus, ODEs/PDEs (Black–Scholes), Brownian motion, Itô's lemma, Monte Carlo, finite differences. Price derivatives & model random dynamics.
Probability & Statistics The trader's edge in uncertainty
  1. L1 Target Mean/variance/std, set theory, sample spaces, conditional probability, combinatorics, independence & mutual exclusion. Model fixed distributions (a coin, a die).
  2. L2 Target Random variables, common distributions, the CLT & law of large numbers, hypothesis testing, confidence intervals, regression. Know when distributions converge — and when they don't.
  3. L3 Target Stochastic processes, time series (ARMA/ARIMA/GARCH), Bayesian inference, non-parametric & robust stats, non-stationarity. Handle dependent, non-stationary real-world data.
Finance & Economics Theory vs. what markets actually do
  1. L1 Target Micro/macro, supply & demand, stocks/bonds/funds, time value of money, inflation & rates, GDP, monetary vs. fiscal policy. Understand the news & its hidden assumptions.
  2. L2 Target Instruments, modern portfolio theory, derivatives (options/futures/swaps), fixed income, FX, CAPM, EMH, alpha, VaR, DCF. Take every model with a grain of salt — alpha exists.
  3. L3 Target Behavioral finance, advanced risk (VaR/CVaR), cognitive biases, market anomalies, tail risk & black-swan events. Turn market intuition into modeled, calculated risk.
Machine Learning Enters at Level 2 — needs the prerequisites
  1. L2 Target The full model pipeline (question → data → features → model → deploy), supervised/unsupervised/RL, bias–variance, cross-validation, trees, ensembles, SVMs, kNN, neural nets. Understand the entire development pipeline.
  2. L3 Target ML for time series, walk-forward validation, RL (Q-learning/policy search), RNN/LSTM/transformers, generative models, causal inference, alpha combination. Build rigorous, bias-free trading models.