Mathematical and Computational Finance

The Mathematical and Computational Finance MSc at the University of Oxford is a distinguished postgraduate programme designed to provide students with a rigorous foundation in quantitative finance, combining advanced mathematical techniques, computational skills, and financial theory. This programme is ideal for individuals aspiring to excel in the finance industry, academia, or research roles that require a deep understanding of the mathematical models and computational methods used in modern finance.

Throughout the course, students will engage with a comprehensive curriculum covering areas such as stochastic calculus, financial modeling, derivatives pricing, risk management, algorithmic trading, and statistical analysis. The programme is structured to balance theoretical foundations with practical applications, equipping graduates with the ability to develop and implement sophisticated financial models, analyze large datasets, and deploy algorithms for real-world financial problems.

The MSc in Mathematical and Computational Finance emphasizes the development of quantitative and programming skills, with modules dedicated to programming languages such as Python, R, and MATLAB, enabling students to efficiently analyze financial data and build complex models. In addition, students will have the opportunity to participate in research projects, seminars, and internships, fostering an environment of collaborative learning and professional development.

Students will benefit from the expertise of world-renowned faculty members who are leading scholars in quantitative finance, as well as state-of-the-art facilities and resources. The programme also offers opportunities for networking with industry professionals through workshops, guest lectures, and career events, preparing graduates for roles in investment banking, asset management, hedge funds, financial consulting, and risk management.

Admission to the MSc in Mathematical and Computational Finance is highly competitive, requiring a strong academic background in mathematics, statistics, computer science, or related fields. Successful applicants demonstrate analytical thinking, problem-solving abilities, and motivation to apply mathematical techniques to solving complex financial problems.

Graduates of this programme will possess the quantitative expertise, computational skills, and industry awareness necessary to thrive in highly dynamic and competitive financial markets. The University of Oxford’s rigorous approach ensures that students leave with not only advanced knowledge and technical skills but also a critical understanding of the ethical and societal considerations related to finance.

This MSc programme is a stepping stone to a successful career in financial institutions, consultancy firms, or to further research in academia, contributing to the development of innovative solutions in the finance industry. With its blend of theoretical insights and practical training, the Mathematical and Computational Finance MSc at Oxford prepares students to become leaders in the ever-evolving world of quantitative finance.

The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.

You will take three introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics and MATLAB.

The first term focuses on compulsory core material, offering 80 hours of lectures and 40 hours of classes/practical. The core courses are as follows:

• Stochastic Calculus
• Financial Derivatives
• Numerical methods I - Monte-Carlo
• Numerical methods I - Finite Differences
• Statistics and financial data analysis
• Financial Programming with C++ 1

In the second term, three streams are offered; each stream consists of 32 hours of lectures and 16 hours of classes/practical. The Tools stream is mandatory and you will also take either the Modelling stream or the Data-driven stream.

Modelling stream

• Exotic derivatives
• Stochastic volatility, jump diffusions
• Commodities
• Fixed income
• Credit derivatives

Data-driven stream

• Asset pricing and inefficiency of markets
• Market microstructure and trading
• Algorithmic trading
• Advanced financial data analysis
• Econometrics of volatility
• Machine learning

Tools stream

• Numerical methods 2 - Monte Carlo methods
• Numerical methods 2 - Finite differences
• Calibration
• Optimisation
• Introduction to stochastic control

As well as the streams, the course includes a compulsory one-week (24 hours of lectures) intensive module on quantitative risk management which is to be held in/around the week before the third term.

The third term is dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor.

The second component of the financial computing course, Financial Computing with C++ 2 (24 hours of lectures and practicals in total), is held shortly after the third term.

The examination will consist of the following elements:

• two written examinations and one take-home project, each of two hours' duration - the written examinations will cover the core courses in mathematical methods and numerical analysis
• a written examination on the Modelling stream or a written examination and a computer-based practical examination on the Data-driven stream
• a written examination assessing the Tools stream
• a take-home project assessing the course in quantitative risk management
• two practical examinations assessing two courses in financial computing with C++.

Applicants are normally expected to be predicted or have achieved a first-class or strong upper second-class undergraduate degree with honours (or equivalent international qualifications), as a minimum, in mathematics or a related discipline. 

Applicants should have a background in probability, statistics, ordinary and partial differential equations, linear algebra and analysis. They must demonstrate their aptitude for, and knowledge of, mathematics, particularly in the area of real analysis, through their performances in the admissions test and at interview. Applicants with undergraduate degrees that are not purely mathematical will still be expected to demonstrate they have sufficient knowledge to perform well on the course.

For applicants with a degree from the USA, the minimum GPA sought is 3.6 out of 4.0.

If you hold non-UK qualifications and wish to check how your qualifications match these requirements, you can contact the National Recognition Information Centre for the United Kingdom (UK NARIC).

No Graduate Record Examination (GRE) or GMAT scores are sought.

• Official transcript(s)
• CV/résumé
• Statement of purpose/personal statement: Up to three pages
• Admissions exercise: MSc in MCF admissions exercise answers with signed disclaimer
• References/letters of recommendation:Three overall, generally academic

ENGLISH LANGUAGE REQUIREMENTS

Higher level

The University of Oxford offers a comprehensive range of financing options to support students enrolled in the Mathematical and Computational Finance program. Tuition fees for the MSc in Mathematical and Computational Finance vary depending on the student's residency status, with international students typically paying a higher fee than UK residents. For the most accurate and up-to-date fee information, prospective students should consult the university’s official website. In addition to tuition fees, students should consider living expenses, including accommodation, food, study materials, and personal expenses, which can significantly vary depending on lifestyle choices and accommodation preferences.

Oxford University provides a variety of scholarships, bursaries, and grants specifically targeted at postgraduate students in the mathematical sciences and related fields. These include university-wide awards, college-specific scholarships, and external funding opportunities sourced from government bodies, private foundations, and industry partners. Notable scholarships for international students include the Rhodes Scholarship, the Clarendon Fund, and the Weidenfeld-Hoffmann Scholarships. In some cases, students may also be eligible for financing through national loan schemes, such as UK government loans, or through partnerships with private lenders offering postgraduate student loans.

Furthermore, the university encourages students to explore external funding sources, including industry sponsorships, research council grants, and crowdfunding options. Many students also consider part-time work opportunities both within the university and in the surrounding Oxford community to help offset living costs. The university’s dedicated financial aid office provides guidance and support throughout the application process, helping students identify suitable funding options and navigate the complex landscape of postgraduate finance.

International students should pay special attention to visa requirements and policies related to funding declarations, as proof of financial support is often a mandatory aspect of the visa application process. The university also offers financial planning seminars and resources to assist students in budgeting their expenses effectively throughout their studies. Overall, Oxford University is committed to ensuring that financial considerations do not hinder talented students from pursuing their academic goals in Mathematical and Computational Finance, offering a robust framework of financial aid and support systems tailored to diverse student needs.

The Mathematical and Computational Finance program at the University of Oxford is a highly specialized postgraduate course designed to develop advanced understanding and skills in the application of mathematics and computational techniques to finance. This program integrates theoretical foundations with practical applications, preparing students for careers in quantitative finance, risk management, and financial technology sectors. The course duration typically spans one year for full-time students, with part-time options available for certain pathways.

Students enrolled in this program engage with a comprehensive curriculum that covers core topics such as stochastic processes, quantitative methods, financial derivatives, risk modeling, and computational algorithms. The program emphasizes the development of mathematical modeling capabilities, proficiency in programming languages like Python, C++, and R, and familiarity with financial markets and instruments. Through a combination of lectures, tutorials, workshops, and practical projects, students gain hands-on experience in implementing financial models and analyzing real-world data.

The program is designed for individuals with a strong background in mathematics, statistics, or computer science who seek to deepen their expertise in financial applications. Admission requirements typically include a good honours degree in a relevant discipline, strong quantitative skills, and some prior experience in programming or financial mathematics. The University of Oxford provides excellent academic resources, including access to cutting-edge research, expert faculty members, and state-of-the-art computational facilities.

Graduates of this program often pursue careers as quantitative analysts, financial engineers, risk managers, or data scientists within both the finance industry and academia. Oxford’s reputation for rigorous academic standards and its strong connections with the financial sector enable students to network effectively and access diverse career opportunities. The program also offers a pathway into further research, including the possibility of proceeding to doctoral studies in related fields.

Overall, the Mathematical and Computational Finance program at Oxford is regarded as one of the leading courses globally, blending academic excellence with practical relevance, and equipping students with the skills necessary for the evolving landscape of modern finance.