MSc in Mathematical and Computational Finance

The MSc in Mathematical & Computational Finance provides graduates with the foundations in applied mathematics, machine learning, and computer science necessary for a successful career in modern finance. It is one of the most popular MSc programmes at the University of Oxford.

This highly interdisciplinary curriculum is designed to prepare students for finance roles, focusing on the mathematical and computational skills needed to develop and calibrate models for large-scale financial datasets. Topics covered include mathematical modelling (stochastic differential equations, stochastic control), computer science (C++ and Python), statistics, deep learning, numerical methods (such as Monte Carlo simulations, finite difference methods for PDEs, and optimisation), and financial applications (financial derivatives, fixed income, decentralised finance, and market microstructure).

The programme is taught by the Mathematical & Computational Finance faculty at the Mathematical Institute at Oxford. As one of the largest mathematical finance research groups globally, The Mathematical & Computational Finance Group has extensive industry ties with leading financial institutions such as banks, hedge funds, central banks, and exchanges. This expertise shapes the programme, ensuring students are well-prepared for careers in quantitative finance. Our MSc students have won the Natixis Prize for best MSc Thesis in Quantitative Finance in Europe for five consecutive years.

Term one

In the first week, you will take four introductory courses covering partial differential equations, probability and statistics, financial markets and instruments, and Python.

The rest of the term focuses on core material, with 64 hours of lectures and 24 hours of classes, in areas of Stochastic Calculus, Financial Derivatives, Numerical Methods and Statistics and Financial Data Analysis. You will also be required to do a required computing course with 16 hours of lectures.

Term two

The second term includes core material (48 hours of lectures and 18 hours of classes), focusing on Deep Learning, Quantitative Risk Management, Stochastic Control and Fixed Income.

This is complemented by four elective courses (48 hours), with options such as Advanced Volatility Modelling, Market Microstructure and Algorithmic Trading, and Financial Computing with C++, among others.

Term Three
The third term is focused on your dissertation project, which will be written on a topic agreed upon with your supervisor. This may also be undertaken alongside an industry internship.

For a detailed breakdown of the courses offered, please visit the MSc in Mathematical and Computational Finance Admissions pages. 

Applicants should have a strong foundation in probability, statistics, ordinary and partial differential equations, linear algebra, and analysis. Previous students typically ranked at the top of their cohort, often holding a First Class degree or equivalent GPA. Applicants must demonstrate their mathematical aptitude, especially in real analysis, through their performance in the admissions test and interview. Successful candidates come from a range of quantitative undergraduate degrees, though those without a purely mathematical background must still show sufficient knowledge to excel in the programme.

Applications should be submitted online. Detailed information on the practicalities of applying can be found on the University page about the MSc in Mathematical and Computational Finance. Prospective applicants are also encouraged to read the graduate application guide before applying.

If you are in doubt about whether your degree is in "mathematics or a related discipline", please see the answer to this FAQ.

GRE or GMAT test results are not a compulsory part of an application for the MSc Mathematical & Computational Finance, but if you feel a GRE or GMAT test result may help demonstrate your mathematical ability, you are welcome to include it with the supporting materials if you wish.

We charge successful applicants a deposit in order to secure their offer - for 2025/26 entry, this will be 15% of the University tuition fee (£7,296). Deposits are generally non-refundable, and more information about the terms and conditions of the deposit can be found here.  We will correspond in more detail about this with successful applicants. 

Course Contact: @email (admissions only) 

Course Director: Prof Justin Sirignano