Map The whole journey
Sixteen units in five phases. Each phase ends with something you can show — a data lake, a strategy report that survives overfitting statistics, a risk-managed portfolio, a live paper-trading system, and a capstone.
The order is deliberate. Markets, data and statistics come first because every later mistake starts there. Research discipline — backtesting, validation and overfitting statistics — comes before factors, strategies and machine learning, because those are exactly the places where untrained researchers fool themselves. Derivatives, rates and microstructure run as their own tracks on top of that foundation.
How How every session works
One hundred sessions, one rhythm: understand it, see it, derive it, run it, test yourself, then use it.
Every session page links its companion lab — a Python notebook you can open in Colab with one click, or run locally from the repository. The labs use a small teaching package, quantnb, and seeded synthetic data by default, so they run anywhere, offline, in minutes, and always give the numbers the page quotes.
Tracks Pick your route
The spine — Units 1 to 6 and Unit 9 — is for everyone. Beyond it, weight your time by the job you want.
QR Quant Researcher · QT Quant Trader · QD Quant Developer · IND Independent Trader. ● = core for that track, ○ = useful context.
| Unit | Name | QR | QT | QD | IND |
|---|---|---|---|---|---|
U1 | The Quant Landscape | ● | ● | ● | ● |
U2 | Markets & Instruments | ● | ● | ● | ● |
U3 | The Quant Math Toolkit | ● | ● | ● | ● |
U4 | Financial Data Engineering | ● | ○ | ● | ● |
U5 | Statistics & Time Series of Returns | ● | ● | ○ | ● |
U6 | Backtesting & Research Discipline | ● | ● | ● | ● |
U7 | Asset Pricing & Factor Investing | ● | ○ | ○ | ● |
U8 | Strategy Families | ● | ● | ○ | ● |
U9 | Portfolio Construction & Risk | ● | ● | ○ | ● |
U10 | Derivatives & Volatility | ● | ● | ○ | ○ |
U11 | Rates, Credit & Macro | ● | ● | ○ | ○ |
U12 | Machine Learning for Trading | ● | ○ | ● | ○ |
U13 | NLP, LLMs & Alternative Data | ● | ○ | ● | ○ |
U14 | Microstructure, Execution & Market Making | ○ | ● | ● | ○ |
U15 | Production Trading Systems | ○ | ● | ● | ● |
U16 | Career, Interviews & Your Own Book | ● | ● | ● | ● |
Unit 1 The Quant Landscape
Phase 1 · Foundations — 5 sessions · Foundations · tracks QR · QT · QD · IND
What Quants Actually Do
Map the roles, the firms and how each one actually makes money — so you know which game you are training for.
→ session01-what-quants-do.html Unit 1 · Session 2Where Returns Come From
The five honest sources of edge — risk premia, behavioural anomalies, liquidity provision, information and speed — and why most apparent edges are none of them.
→ session02-where-returns-come-from.html Unit 1 · Session 3The Quant Research Lifecycle
The master workflow of the whole course — hypothesis to data to signal to validation to sizing to paper to live to decay — and the gates between the stages.
→ session03-research-lifecycle.html Unit 1 · Session 4The Engineer's Edge, Blind Spots & Honest Odds
What transfers from software and ML, what breaks in markets, and the evidence on who actually makes money.
→ session04-engineers-edge-and-odds.html Unit 1 · Session 5Set Up Your Quant Lab
A reproducible workbench — uv, Python 3.12, Jupyter, DuckDB, the quantnb package, a research repo layout and a data cache.
→ session05-quant-lab-setup.htmlQuant finance is engineering for decisions under uncertainty with money on the line — and the job is mostly not fooling yourself.
Unit 2 Markets & Instruments
Phase 1 · Foundations — 7 sessions · Foundations · tracks QR · QT · QD · IND
Market Anatomy & the Life of an Order
Follow one order from your code through broker, venue, clearing house and custodian — and see where every fee and risk sits.
→ session01-market-anatomy.html Unit 2 · Session 2Equities, Indices & ETFs
Shares, dividends, splits, index construction, ETF creation/redemption, and the mechanics and costs of shorting.
→ session02-equities-indices-etfs.html Unit 2 · Session 3Returns, P&L, Compounding & Leverage
The arithmetic every later session relies on — simple vs log returns, compounding, annualisation, volatility drag, Sharpe, drawdown and leverage.
→ session03-returns-pnl-leverage.html Unit 2 · Session 4Futures: Carry, Basis, Roll & Margin
How futures are priced from cost of carry, why curves slope, what roll yield really is, and how margin creates leverage and liquidation risk.
→ session04-futures.html Unit 2 · Session 5FX & Commodities
Currency quoting, forwards and covered interest parity; commodity term structures, storage and convenience yield.
→ session05-fx-commodities.html Unit 2 · Session 6Crypto Market Structure
Centralised vs decentralised venues, AMMs, perpetual futures and funding, basis trades, and the custody and counterparty risks that traditional markets hide from you.
→ session06-crypto-market-structure.html Unit 2 · Session 7Options Primer
Calls, puts, payoffs, put-call parity, intrinsic vs time value, and a first look at implied volatility — enough to read any options discussion.
→ session07-options-primer.htmlEvery instrument is a contract with a cash-flow profile — learn the plumbing and the P&L arithmetic before you model anything.
Unit 3 The Quant Math Toolkit
Phase 1 · Foundations — 6 sessions · Foundations · tracks QR · QT · QD · IND
Probability & Expected Value
Random variables, expectation, variance, conditioning and Bayes — the language of every bet and every interview question.
→ session01-probability-expected-value.html Unit 3 · Session 2Distributions & Fat Tails
Normal, lognormal and Student-t; skewness, kurtosis and tail indices — and why the normal distribution will eventually lie to you.
→ session02-distributions-fat-tails.html Unit 3 · Session 3Linear Algebra for Portfolios
Weights as vectors, risk as a quadratic form, PCA as the hidden structure of a market — linear algebra through the portfolio lens.
→ session03-linear-algebra-portfolios.html Unit 3 · Session 4Convex Optimization
Objectives, constraints, convexity, quadratic programs and Lagrange multipliers — and how to state a portfolio problem so cvxpy can solve it.
→ session04-convex-optimization.html Unit 3 · Session 5Simulation & Monte Carlo
Simulate prices, strategies and uncertainty with seeded Monte Carlo — random walks, GBM, bootstraps and variance reduction.
→ session05-simulation-monte-carlo.html Unit 3 · Session 6Bet Sizing, Kelly & Ruin
Why the size of a bet matters as much as its edge — Kelly growth, the cost of over-betting, fractional Kelly and risk of ruin.
→ session06-kelly-bet-sizing.htmlThe math is a toolkit, not a hurdle — every tool here earns its place by answering a trading question.
Unit 4 Financial Data Engineering
Phase 1 · Foundations — 6 sessions · Foundations · tracks QR · QD · IND
The Data Landscape, Vendors & Licensing
Bars, ticks, quotes, books, fundamentals and macro — who sells what, what it costs, and what the licence lets you do with it.
coming soonPoint-in-Time Data & Data Biases
Look-ahead, survivorship, restatements, vintages and delistings — the data biases that manufacture fake alpha, and how to engineer them out.
coming soonCorporate Actions, Security Master & Continuous Futures
Adjust prices correctly, keep identifiers straight through ticker changes, and stitch futures into continuous series without inventing returns.
coming soonTime, Calendars, As-of Joins & Bars
Timestamps and time zones, exchange calendars, as-of joins that never peek, and information-driven bars (volume, dollar, imbalance).
coming soonThe Research Storage Stack
Parquet, Arrow, DuckDB and polars — a fast, local, columnar research stack — plus when kdb+ and managed warehouses earn their cost.
coming soonLab: Build Your Research Data Lake
Build an idempotent, tested, point-in-time data pipeline with quality checks and lineage — the foundation for every later lab.
coming soonYour backtest can only be as honest as your data — point-in-time, or it didn't happen.
Unit 5 Statistics & Time Series of Returns
Phase 2 · Research Craft — 7 sessions · Intermediate · tracks QR · QT · IND
Stylized Facts of Returns
The empirical regularities every model must respect — fat tails, volatility clustering, the leverage effect, and near-zero autocorrelation.
coming soonRegression & Inference That Doesn't Lie
OLS alpha and beta, HAC standard errors, overlapping observations, the standard error of a Sharpe ratio, bootstraps and multiple testing.
coming soonBayesian Thinking: Priors, Shrinkage & Updating
Priors, posteriors and shrinkage — the machinery behind Ledoit-Wolf, Black-Litterman and Kalman filters, and the honest answer to "is my Sharpe real?"
coming soonStationarity & ARMA Models
Unit roots, ADF and KPSS, AR/MA/ARMA, ACF and PACF — and why returns are close to unpredictable while prices are not stationary.
coming soonModeling Volatility
Realized-volatility estimators from OHLC data, EWMA and GARCH forecasts — volatility is the one thing you can forecast well.
coming soonCointegration & Mean Reversion
Engle-Granger and Johansen tests, hedge ratios, spreads, the Ornstein-Uhlenbeck process as a continuous AR(1), and half-lives.
coming soonKalman Filters & Regime Models
State-space models, the Kalman filter for time-varying hedge ratios, hidden Markov regimes and structural breaks.
coming soonReturns are noisy, fat-tailed and barely predictable — good statistics tells you exactly how little you know.
Unit 6 Backtesting & Research Discipline
Phase 2 · Research Craft — 8 sessions · Intermediate · tracks QR · QT · QD · IND
What a Backtest Is (and Isn't)
A backtest is a historical simulation under assumptions, not a research tool — what it can prove, what it cannot, and why the gap to live trading exists.
coming soonBuild a Vectorized Backtester
Signals to positions to returns in a few lines of pandas/polars — and the shift discipline that keeps the future out.
coming soonBuild an Event-Driven Backtester
An event loop with orders, fills and portfolio state — slower, but realistic, and the same shape as a live trading system.
coming soonThe Bias Hall of Fame
Live demos of every classic way a backtest lies — look-ahead, survivorship, data snooping, selection, stale and untradable prices.
coming soonTransaction Costs & Capacity
Spread, commission, slippage, market impact, borrow and funding — and how costs cap how much capital a strategy can ever run.
coming soonValidation: Walk-Forward, Purged K-Fold & CPCV
Walk-forward analysis, purging and embargo, and combinatorial purged cross-validation — train/test splits that respect time.
coming soonOverfitting Statistics: PSR, DSR, MinTRL & PBO
The probabilistic and deflated Sharpe ratios, minimum track record length, and the probability of backtest overfitting — how to price in the number of things you tried.
coming soonLab: The Research Protocol
Pre-register a hypothesis, log every trial, sweep parameters, score them with PBO and DSR, and write the go/no-go memo.
coming soonA backtest is a unit test that can lie — the discipline is designing it so that it can't.
Unit 7 Asset Pricing & Factor Investing
Phase 2 · Research Craft — 5 sessions · Intermediate · tracks QR · IND
Efficient Markets & the Limits to Arbitrage
What market efficiency really claims, where it bends, and why mispricings can persist even when smart money sees them.
coming soonCAPM, APT & Factor Regressions
From one factor to many — CAPM, APT and time-series factor regressions that separate alpha from exposure.
coming soonBuilding Factors: Sorts & Fama-MacBeth
Portfolio sorts, long-short factor construction, Fama-French methodology and Fama-MacBeth cross-sectional regressions — done without look-ahead.
coming soonThe Factor Zoo & the Replication Debate
Hundreds of published factors, the t > 3 hurdle, post-publication decay, and the two sides of the replication debate — risk vs mispricing.
coming soonCausal Factor Investing
Causal graphs, confounders and colliders — why a factor model can be statistically significant and still causally wrong.
coming soonFactors are the vocabulary of returns — but most of the dictionary is fake.
Unit 8 Strategy Families
Phase 2 · Research Craft — 7 sessions · Intermediate · tracks QR · QT · IND
Time-Series Momentum & Trend Following
Trend following across futures with volatility-scaled EWMA crossovers — the most robust systematic strategy family, built properly.
coming soonCross-Sectional Momentum & Reversal
Ranking winners against losers, short-term reversal, and the momentum crashes that make position sizing matter.
coming soonPairs Trading & Statistical Arbitrage
Distance, cointegration and PCA-residual stat arb — entries, exits, hedge ratios and why the edge has shrunk.
coming soonCarry Across Asset Classes
FX carry, futures roll yield, bond carry and roll-down — one unifying definition of carry and its crash risk.
coming soonValue, Quality & Fundamental Quant
Point-in-time fundamentals from EDGAR XBRL, value and quality signals, accruals — and why value has been so painful.
coming soonEvent-Driven Strategies
Event studies, post-earnings-announcement drift, index rebalances — trading around information with precise timestamps.
coming soonCombining Signals
Information coefficient, the fundamental law of active management, forecast scaling and combination — many weak signals into one strong book.
coming soonA handful of economically motivated ideas explain most systematic returns — the craft is in the implementation.
Unit 9 Portfolio Construction & Risk
Phase 3 · Portfolio, Risk & Derivatives — 9 sessions · Intermediate · tracks QR · QT · IND
Mean-Variance & Why It Breaks
Markowitz, the efficient frontier and the tangency portfolio — and why naive mean-variance is an error-maximiser.
coming soonCovariance Estimation
Sample covariance and its failure modes, Ledoit-Wolf and OAS shrinkage, random-matrix denoising and EWMA covariance.
coming soonRisk Parity & HRP
Risk contributions, inverse-vol and equal-risk-contribution portfolios, hierarchical risk parity and HERC — allocation without return forecasts.
coming soonFactor Risk Models
Build a mini Barra-style model — exposures, factor covariance and specific risk — and use it to decompose where your risk comes from.
coming soonSizing, Vol Targeting & Allocating Across Strategies
Carver-style volatility targeting, position buffering, diversification multipliers and allocating capital across strategies with fractional Kelly.
coming soonOptimization with Constraints & Costs
Real portfolio optimisation — turnover penalties, cost-aware objectives, leverage and exposure constraints, and Black-Litterman views.
coming soonVaR, ES, EVT & VaR Backtests
Value at risk and expected shortfall — historical, parametric and filtered — extreme value theory for the tail, and testing whether your VaR is honest.
coming soonDrawdowns, Copulas, Tail Risk & Stress Tests
Drawdown statistics, tail dependence and copulas, and stress tests from 2008, March 2020 and 2022 — with LTCM and the 2007 quant quake as cautionary tales.
coming soonPerformance, Attribution & When to Switch Off
Measure performance honestly, attribute it to factors and skill, monitor live decay, and decide in advance when a strategy is retired.
coming soonReturns are forecast, risk is measured; the portfolio is where the two meet — under costs and constraints.
Unit 10 Derivatives & Volatility
Phase 3 · Portfolio, Risk & Derivatives — 7 sessions · Advanced · tracks QR · QT
No-Arbitrage & Binomial Trees
Replication and the law of one price, risk-neutral probabilities, and pricing European and American options on a binomial tree.
coming soonStochastic Calculus for Engineers
Brownian motion, quadratic variation, SDEs and Itô's lemma — built by simulation first, formalism second.
coming soonBlack-Scholes-Merton
Derive BSM two ways (PDE and risk-neutral expectation), implement it, and list precisely which assumptions markets violate.
coming soonThe Greeks & Hedging P&L
Delta, gamma, vega and theta; delta hedging in simulation; and the P&L identity that links hedging to realized minus implied variance.
coming soonThe Implied Volatility Surface
Smiles, skews and term structures; fitting SVI and SSVI; and checking the surface for static arbitrage.
coming soonStochastic Volatility & Numerical Methods
Local vol vs stochastic vol, the Heston model, Monte Carlo and finite-difference pricing, calibration — with QuantLib as the reference.
coming soonTrading Volatility
The volatility risk premium, straddles and variance swaps, dispersion, the VIX complex — and the crash risk that pays for all of it.
coming soonPrice by replication, hedge by the Greeks, and trade the gap between implied and realized.
Unit 11 Rates, Credit & Macro
Phase 3 · Portfolio, Risk & Derivatives — 5 sessions · Advanced · tracks QR · QT
Yield Curves & Bootstrapping
Discount factors, zero, forward and par rates, day counts, and bootstrapping a curve from market instruments.
coming soonDuration, Convexity & Curve PCA
DV01, duration, convexity and key-rate risk — and the three PCA factors (level, slope, curvature) that drive almost every curve.
coming soonShort-Rate Models & Swaps
Interest-rate swaps and SOFR, Vasicek, CIR and Hull-White short-rate models, and what a swaption is.
coming soonCredit: Spreads, CDS & Merton
Credit spreads, default intensities and recovery, credit default swaps, and the Merton structural model of default.
coming soonFX & Macro Regimes
Uncovered interest parity and the forward-premium puzzle, nowcasting with point-in-time macro data, and growth-inflation regimes across assets.
coming soonMoney has a price that changes with time and with trust — curves encode both.
Unit 12 Machine Learning for Trading
Phase 4 · Machines & Markets — 6 sessions · Advanced · tracks QR · QD
Why Finance ML Is Different
Non-IID samples, concept drift, adversarial markets and tiny signal-to-noise — why ML habits from vision and NLP backfire here.
coming soonLabeling: Triple Barrier & Meta-Labeling
Fixed-horizon labels and their flaws, the triple-barrier method, and meta-labeling to size bets from a primary model.
coming soonFeatures & Sample Weights
Stationary features that keep memory (fractional differentiation), sample uniqueness, the sequential bootstrap and time-decay weights.
coming soonGradient Boosting for Cross-Sectional Alpha
Predict cross-sectional returns with LightGBM on point-in-time features, validated with purged CV and scored on IC after costs.
coming soonFeature Importance & Interpretability
MDI, MDA, single-feature importance and SHAP — and clustered importance to survive correlated features.
coming soonDeep Learning, RL & the Complexity Debate
Sequence models, reinforcement learning and the "virtue of complexity" debate — where deep models help, and where they are hype.
coming soonIn markets, machine learning is a low signal-to-noise game where validation — not model capacity — decides who wins.
Unit 13 NLP, LLMs & Alternative Data
Phase 4 · Machines & Markets — 4 sessions · Advanced · tracks QR · QD
Alternative Data
A taxonomy of alternative data, how to evaluate a dataset before buying it, and the legal lines (MNPI, scraping, privacy) you must not cross.
coming soonText as Data
From dictionaries (Loughran-McDonald) to TF-IDF to embeddings — turning filings, calls and news into point-in-time features.
coming soonLLMs for Return Prediction — and the Look-Ahead Trap
What the evidence says about LLM signals, and how training-data leakage fakes their performance — with a lab that tests only after the model's cutoff.
coming soonLLM Agents as Research Assistants
Using LLM agents to speed up research without letting them inflate your trial count — guardrails, logging and mandatory deflation.
coming soonText and alternative data are new sources of information — and new ways to leak the future into your backtest.
Unit 14 Microstructure, Execution & Market Making
Phase 4 · Machines & Markets — 6 sessions · Advanced · tracks QT · QD
The Limit Order Book
Price-time priority, queues, tick size, maker-taker fees and auctions — how a modern electronic order book actually matches trades.
coming soonMicrostructure Models
The Roll, Kyle and Glosten-Milgrom models — spreads as the price of adverse selection, and how informed traders move prices.
coming soonMarket Impact & the Square-Root Law
Temporary vs permanent impact, the square-root law and its evidence, and measuring impact from your own fills.
coming soonOptimal Execution & TCA
TWAP, VWAP and implementation shortfall; the Almgren-Chriss trade-off; and transaction cost analysis against the arrival price.
coming soonMarket Making
Inventory risk and adverse selection, the Avellaneda-Stoikov model, and a queue-aware market-making backtest in hftbacktest.
coming soonLatency & Performance Engineering
Profiling Python, numba and Rust/C++ hot paths, tick-to-trade latency — and an honest map of what speed buys a non-HFT trader.
coming soonEvery trade has a counterparty who may know more than you — the order book is where you pay for that.
Unit 15 Production Trading Systems
Phase 4 · Machines & Markets — 7 sessions · Advanced · tracks QT · QD · IND
Architecture of a Live Trading System
Feed, strategy, portfolio, OMS, EMS and broker — the components, their contracts, and the state machine at the heart of an order.
coming soonBacktest-to-Live with NautilusTrader
One strategy class that runs in a backtest, on a simulated exchange and against a paper account — with NautilusTrader.
coming soonBroker APIs & FIX
alpaca-py and ib_async against paper accounts, the FIX protocol's core messages, rate limits and idempotent order submission.
coming soonPre-Trade Risk & Kill Switches
Fat-finger checks, price collars, position and loss limits, and the kill switch — with Knight Capital as the case study.
coming soonOperations & MLOps
Reconciliation, monitoring, alerting, runbooks and restarts — plus model registries, retraining and drift detection for live models.
coming soonMarket Conduct & Compliance
Insider trading and MNPI, spoofing and layering, wash trading, front-running and best execution — the rules under SEC/FINRA and MiFID II/MAR.
coming soonLab: Deploy a Paper-Trading Bot
Deploy an end-to-end paper-trading system — scheduled, monitored, reconciled and protected by a kill switch.
coming soonA live trading system is a distributed system that loses money when it is wrong — build it like one.
Unit 16 Career, Interviews & Your Own Book
Phase 5 · The Professional — 5 sessions · Advanced · tracks QR · QT · QD · IND
Career Paths & the Quant Job Market
Roles, firms, pay structures and hiring pipelines in 2026 — and the portfolio of evidence that gets an engineer hired.
coming soonInterview Drills: Probability, Mental Math & Market-Making Games
The probability, expected-value, mental-math and market-making-game rounds — with drills and the reasoning interviewers want to hear.
coming soonStats, ML, Coding & Research-Case Interviews
The statistics, ML and coding rounds, trading-system design, and the multi-hour research case — and how to write the report.
coming soonRunning Your Own Capital
Capital, costs, brokers, taxes and rules by jurisdiction, psychology and discipline, and how to build a verifiable track record.
coming soonCapstone: Brief & Rubric
The capstone — research, validate, size, paper-trade and report one strategy end to end — with the rubric professionals would use.
coming soonSkill compounds when it is visible — build the evidence, rehearse the interviews, respect the odds.
Status Every unit
The course is published in waves. Legend: ✅ published 🟡 in progress ⬜ planned
| Unit | Name | Sessions | Phase | Status |
|---|---|---|---|---|
U1 | The Quant Landscape | 5 of 5 | Phase 1 | ✅ published |
U2 | Markets & Instruments | 7 of 7 | Phase 1 | ✅ published |
U3 | The Quant Math Toolkit | 6 of 6 | Phase 1 | ✅ published |
U4 | Financial Data Engineering | 0 of 6 | Phase 1 | 🟡 in progress |
U5 | Statistics & Time Series of Returns | 0 of 7 | Phase 2 | 🟡 in progress |
U6 | Backtesting & Research Discipline | 0 of 8 | Phase 2 | 🟡 in progress |
U7 | Asset Pricing & Factor Investing | 0 of 5 | Phase 2 | 🟡 in progress |
U8 | Strategy Families | 0 of 7 | Phase 2 | 🟡 in progress |
U9 | Portfolio Construction & Risk | 0 of 9 | Phase 3 | ⬜ planned |
U10 | Derivatives & Volatility | 0 of 7 | Phase 3 | ⬜ planned |
U11 | Rates, Credit & Macro | 0 of 5 | Phase 3 | ⬜ planned |
U12 | Machine Learning for Trading | 0 of 6 | Phase 4 | ⬜ planned |
U13 | NLP, LLMs & Alternative Data | 0 of 4 | Phase 4 | ⬜ planned |
U14 | Microstructure, Execution & Market Making | 0 of 6 | Phase 4 | ⬜ planned |
U15 | Production Trading Systems | 0 of 7 | Phase 4 | ⬜ planned |
U16 | Career, Interviews & Your Own Book | 0 of 5 | Phase 5 | ⬜ planned |
18 of 100 sessions published.
Found a mistake? Every page is open source — report an erratum and it gets fixed.
Educational material only — not investment, legal or tax advice. Backtests and simulations are hypothetical. Disclaimer · Text CC BY 4.0 · Code MIT.