Ten specialties, two 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. Two study paths run across the tracks: one for practitioners who build systems, one for researchers who derive models.
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.
10 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.
4 courses publishedAlgorithmic Trading
Strategy design, backtesting, position sizing and performance measurement, from the first rule-based system to a costed, validated strategy.
8 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.
5 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.
3 courses publishedSystematic Investing
Systematic trading over months and years: factors, trend following and the evidence behind them.
4 courses publishedPortfolio Management
From mean-variance theory to optimisers that survive estimation error: how quantitative portfolios are constructed and rebalanced.
3 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.
5 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 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.
- FoundationShort courses that fix the mathematics, statistics and code 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.