Quant finance, one nugget at a time
Complex quant concepts, broken into bite-size nuggets that are easy to digest. Whether you're a complete beginner or a practitioner filling in gaps, each lesson builds on the last, from what a stock is to the day-to-day work of a quant: generating factors, building strategies, managing risk, and constructing portfolios. 300+ lessons.
Start from zero: what a stock is, how to read its price, returns, risk, and your first portfolio — each idea built on the last.
7 nuggetsStocks & Prices
What a stock is, how its price is recorded (open, high, low, close, volume), and how to load and plot one over time.
3 nuggetsReturns
Turn prices into returns — daily, multi-day, and annual — and learn the difference between simple and log returns.
7 nuggetsRisk & Volatility
Measure how much a stock swings: variance, standard deviation, volatility, drawdown, and the worst peak-to-trough losses.
8 nuggetsDistributions
The shapes returns and prices actually take: the normal baseline every risk model assumes, the lognormal behind prices and options, the fat tails and skew that break the tidy models, and the tools (Student's t, the central limit theorem, bootstrapping) for handling them honestly.
6 nuggetsPortfolios
Combine stocks into a portfolio: covariance and correlation, weights, weighted returns, concentration, and the free lunch of diversification.
4 nuggetsRisk-Adjusted Returns
Compare strategies fairly: the risk-free rate, excess return, and the Sharpe, Sortino, Calmar and Information ratios.
5 nuggetsVectors & Linear Algebra: NumPy Basics
Scale portfolio math to many assets with vectors, NumPy, the dot product, and the covariance matrix.
Turn the building blocks into real machinery: factors, linear algebra, strategies, and risk models.
The professional edge: execution and costs, honest validation, and frontier methods like machine learning and alternative data.