13 specialties, three paths, one ladder
Specialist tracks
Quantitative finance, one specialty at a time. Each track covers one specialty of the trade, with courses at each level and a credential program at the top. Three study paths run across the tracks: one for practitioners who build systems, one for researchers who derive models, and one for traders who never write code.
Quantitative Foundations
The mathematical finance every later course assumes: probability, statistics, linear algebra, time series and stochastic calculus, taught with market data rather than textbook urns.
9 courses publishedProgramming for Quantitative Finance
Python for trading research and backtesting, C++ for systems where microseconds matter. Code you can run, review and put into production.
3 courses publishedAlgorithmic Trading
Strategy design, backtesting, position sizing and performance measurement, from the first rule-based system to a costed, validated strategy.
4 courses publishedHigh-Frequency Trading and Market Microstructure
High-frequency trading (HFT) courses on how orders meet: limit order books, execution algorithms, smart order routing and the economics of trading at microsecond scale.
3 courses publishedStatistical Arbitrage and Medium-Frequency Trading
Mean reversion trading over hours to weeks: pairs, baskets, cointegration and the risk of spreads that stop converging.
1 course publishedSystematic Investing
Systematic trading over months and years: factors, trend following and the evidence behind them.
2 courses publishedPortfolio Management
From mean-variance theory to optimizers that survive estimation error: how quantitative portfolios are constructed and rebalanced.
2 courses publishedFinancial Risk Management
Financial risk management in practice: measuring, testing and governing market risk with VaR, expected shortfall, stress tests and the controls around the models themselves.
3 courses publishedDerivatives and Rates
Option pricing from Black-Scholes to stochastic volatility, with the hedging and calibration that make the models useful.
4 courses publishedMachine Learning for Finance
Machine learning in finance, applied with the controls that markets demand: purged validation, leakage checks and honest costs.
4 courses publishedFixed Income and Credit
Fixed income and credit for quants: how bonds, mortgage pools and credit derivatives are priced, how rate and credit risk are measured and hedged, and the models banks use to value both.
3 courses publishedDiscretionary Trading
Trading courses for people who place their own trades: how markets and orders work, how to read a chart and test what it says, what each trade costs, and how professionals run day, swing, futures, options and macro books. No programming at any point.
8 courses publishedTrader Judgment
Trading discipline as something you can learn and measure: how to size a position, how to tell an edge from luck, how to stop trading like a gambler, and how to write and keep a plan.
6 courses published
The study ladder
Every course sits on one rung. Each rung assumes the one below it.
- OpenFree primers. Read, watch and work the exercises before you spend anything.
- FoundationThe mathematics, statistics, data and market knowledge every later course assumes.
- PractitionerLab-based courses. You build, test and cost real strategies and systems on market data.
- ResearcherProof-level courses. Stochastic models, estimation theory and the literature behind each method.
- Credential programMulti-course programs, most ending in an assessed capstone, that lead to a named Institute credential.
Practitioner path
For engineers, traders and analysts who need working systems: labs, code reviews and assessed projects.
Researcher path
For quantitative researchers and graduate students: derivations, estimation and a written research capstone.
Trader path
For discretionary, manual and prop traders, and for anyone starting from nothing: three certificates of trading, risk and evidence, with no programming at any point.