I'd pull the compulsory modules for two programmes and compare what students must actually produce. An options course assessed with proofs develops a different skill from one assessed with an independently checked pricing library. Look for one project that ends with a decision you can defend, such as choosing a hedge, rejecting a forecast, or demonstrating convergence against a known solution. The programme name alone won't tell you how much time you'll spend on any of those tasks.
Compare the required courses and assessments
Compare programmes by the kinds of problems their core work prepares you to solve.
| Goal | What to look for | Example of relevant assessed work |
|---|---|---|
| Research a trading signal | Statistics, time series, market microstructure, rigorous validation | Test a hypothesis on dated data with a benchmark and costs |
| Price and hedge derivatives | No-arbitrage, stochastic calculus, fixed income, hedging | Price an option and explain how the hedge behaves when markets move |
| Implement financial models | Numerical analysis, optimisation, Monte Carlo, software design | Compare methods by accuracy, stability, and runtime |
| Work in portfolio or risk research | Asset pricing, econometrics, covariance estimation, optimisation | Build and stress-test a portfolio under realistic constraints |
Check which units are compulsory, which electives run regularly, and how much time you will spend on research or implementation. A curriculum with an appropriate capstone can give you a concrete piece of work to discuss when applying for roles.
Now consider an applicant who enjoys comparing numerical errors and designing fast algorithms. A programme with numerical methods, programming, and a substantial simulation project fits those interests, regardless of its name. An applicant interested in empirical asset pricing should put more weight on statistics, research design, and access to usable datasets.