One of the Institute's two study paths
The practitioner path
How to become a quantitative trader who builds systems that trade. For engineers, traders and analysts; every course on the path ends in a project built on market data.
The path, stage by stage
Start with an Open course
Free, two to three hours, no assessment. Check that the subject is what you expected before paying for anything.
Fix the foundations
Probability, statistics and Python for Finance. Skip any course whose outcomes you can already meet.
Take a specialist certificate
Algorithmic trading, high-frequency trading, statistical arbitrage, systematic investing, portfolio management, risk or machine learning.
Complete the Professional Diploma
The top practitioner credential. Eight courses across research, validation, sizing, execution, statistical arbitrage and risk, ending in a 40-hour capstone. Specialist certificate courses count toward it.
The practitioner path is for people whose job is to make systems work: write the strategy, test it honestly, size it, execute it and report on it. It favours code, data and assessed projects over proofs. Mathematics is taught as far as the work needs it and no further. If you are asking how to become a quantitative trader, this is the route.
Credentials on this path
- Foundation Certificate in Computational FinanceThe entry quantitative finance certificate. Four Foundation courses that fix the probability, statistics and Python every later course assumes, and a first look at how trading systems are built.
- Certificate in Algorithmic TradingSix courses and a capstone that take a strategy from idea to a costed, sized and validated system, with performance reported the way a trading desk would read it.
- Certificate in High-Frequency Trading and Market MicrostructureFive courses and a capstone on how orders meet: the limit order book, execution algorithms, venue routing, market making and the systems that run them.
- Certificate in Statistical ArbitrageFive courses and a capstone on market-neutral trading: time series foundations, pairs and baskets, cointegration and the validation that keeps spread strategies honest.
- Certificate in Systematic InvestingSix courses and a capstone on rule-based investing over months and years: asset pricing, trend following, factors and the portfolio construction that holds them together.
- Certificate in Quantitative Portfolio ManagementSix courses and a capstone on building portfolios with numbers: mean-variance and its failures, robust optimisation, Black-Litterman views, factors, attribution and risk.
- Certificate in Quantitative Risk ManagementA financial risk management certification in five courses and a capstone on measuring and governing market risk: VaR and expected shortfall, volatility models, stress tests and the validation of the models themselves.
- Certificate in Machine Learning for TradingFive courses and a capstone on applying machine learning to markets without fooling yourself: labelling, features, purged validation, overfitting tests and reinforcement learning.
- Professional Diploma in Algorithmic TradingThe top credential on the practitioner path. Eight courses and a 40-hour capstone covering everything between a trading idea and a book you could defend to a risk committee.
Questions applicants ask
How long does the practitioner path take?
It depends on where you start and how many hours a week you study. The Foundation Certificate in Computational Finance is 92 hours of study and the Professional Diploma is 238, so at eight hours a week the two together take about ten months.
Can I move to the researcher path later?
Yes. Courses count wherever they appear, and several Foundation and Researcher courses are shared by both paths.