MSc in Mathematical and Computational Finance (MCF)
A 10-month Mathematical Institute degree combining stochastic calculus, derivatives, numerical methods, deep learning and risk, with two C++ computing courses and a supervised dissertation. Teaches C++, Python and PyTorch.
What you’ll study
Core
- Introductory courses (PDEs, probability, statistics, financial markets and instruments, Python)
- Stochastic calculus
- Financial derivatives
- Numerical methods
- Statistics and financial data analysis
- C++ financial computing I
- Deep learning
- Quantitative risk management
- Stochastic control
- Fixed income
- C++ financial computing II
- Dissertation
Electives
- Advanced volatility modelling
- Market microstructure and algorithmic trading
- Asset pricing
Source: maths.ox.ac.uk ↗
Before you apply
- Background
- Typically a First Class degree or equivalent in mathematics or a related discipline
- Maths
- probability; statistics; ordinary and partial differential equations; linear algebra; analysis
- Tests
- GRE/GMAT not compulsory; may be submitted
- English
- Higher level per University proficiency page
Source: maths.ox.ac.uk ↗
After graduation
The programme doesn’t publish an employment report.
QuantNet’s 2025 ranking reports 52% at graduation, 87% within three months employment and a GBP 85,000 median base starting salary. See the ranking ↗
Want to see what employers ask for? Browse open quant roles.
What students and graduates say
Threads from QuantNet and other forums where applicants, students and graduates discuss this programme. They’re personal views and may be out of date.
- University of Oxford - MSc in Mathematical and Computational Finance (QuantNet) (QuantNet)
- Oxford MSc Mathematical and Computational Finance reviews (QuantNet) (QuantNet)
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.