MSc in Mathematical and Computational Finance

10 Months On Campus Masters Program

University of Oxford

Program Overview

The MSc in Mathematical and Computational Finance at the University of Oxford equips you with rigorous mathematical, computational, and statistical tools to model and analyse problems in modern quantitative finance. It is ideal for students with a strong mathematical background who want careers as quantitative analysts, model developers, or researchers in top financial institutions, hedge funds, investment banks, or for those pursuing doctoral research.

Curriculum Structure

Year 1
This intensive 10-month full-time MSc begins with an introductory course covering partial differential equations, probability, statistics, financial markets and instruments, and Python, providing a foundation for advanced study.

In the first term, you will study Stochastic Calculus, Financial Derivatives, Numerical Methods, Statistics and Financial Data Analysis, and Financial Computing with C++, developing the skills to construct and evaluate quantitative financial models.

During the second term, the curriculum offers both core material and optional modules such as Deep Learning, Quantitative Risk Management, Stochastic Control, Fixed Income, Advanced Volatility Modelling, Monte Carlo Methods, Asset Pricing, Market Microstructure and Algorithmic Trading, or Decentralised Finance, allowing you to tailor your studies to your interests.

In the third term, you complete an independent dissertation, chosen with guidance from a supervisor, which may incorporate industry insights or research questions, demonstrating your ability to carry out original quantitative work.

Focus Areas

Stochastic calculus, numerical methods, financial computing (C++ and Python), financial derivatives, quantitative risk management, deep learning in finance, fixed income, and advanced topics in computational finance such as volatility modelling and algorithmic trading.

Learning Outcomes

Graduates will be able to apply advanced mathematical frameworks to model financial markets, construct and calibrate quantitative models, use computational tools for large-scale data analysis, carry out independent research projects, and communicate complex quantitative insights effectively.

Professional Alignment (Accreditation)

The MSc is delivered by the Mathematical Institute at Oxford, one of the world’s leading centres for mathematical sciences, ensuring highly respected analytical training that aligns with industry expectations for quantitative finance professionals.

Reputation (Employability Rankings)

The University of Oxford is consistently ranked among the world’s top universities. This MSc is highly regarded in the quantitative finance industry, and graduates are frequently recruited by leading investment banks, hedge funds, financial institutions, or pursue competitive PhD programmes worldwide.

Experiential Learning (Research, Projects, Internships etc.)

Choosing the MSc in Mathematical and Computational Finance at the University of Oxford means enrolling in one of the most quantitatively rigorous and professionally respected finance master’s programmes in the world. This course blends mathematical modelling, numerical methods, financial computing, and data science to give you the analytical and computational skills that top banks, hedge funds, investment firms, and financial engineering teams actively recruit for. You’ll be trained to build, calibrate, and evaluate models for real financial data — whether it’s derivatives pricing, risk analysis, machine learning, or simulation — so you graduate with practical, high-value expertise that’s directly applicable in quantitative finance roles.

Here’s how your experiential learning will unfold:

Intensive Quantitative and Computing Training:

Immersive learning in advanced stochastic calculus, numerical methods, machine learning, and deep learning, all tailored to solving real problems in modern finance.
Financial computing courses with hands-on practice in programming languages such as C++ and Python, allowing you to implement algorithms and build computational models used in industry-standard quantitative roles.
Coursework includes practical examinations and computing projects, where you use code to analyse data, solve complex equations, and create tools that mirror work done by quantitative analysts in financial firms.

Applied Mathematical Finance Content:

Core modules cover areas such as financial derivatives, fixed income, quantitative risk management, and statistics for financial data, giving you deep insight into financial instrument behaviour and modelling.
Elective options let you explore advanced topics like volatility modelling, Monte Carlo simulation, market microstructure, algorithmic trading, and decentralised finance, allowing you to tailor your expertise toward specific industry interests.

Dissertation & Optional Internship Integration:

In your third term, you complete a dissertation project, a major piece of work where you research, model, and analyse a topic agreed with your supervisor. Many students combine this with an industry internship or professional placement, providing real-world exposure and an opportunity to apply your knowledge.
This project allows you to showcase your ability to tackle extended quantitative problems — a skill highly prized by recruiters in quantitative finance.

Facilities, Academic Environment & Learning Community:

Study within the Mathematical Institute, which offers purpose-built teaching spaces, computing resources, a dedicated graduate library, and shared study rooms with desktop machines to support your modelling and computing needs.
Access to the Bodleian Libraries and digital resources, one of the largest academic collections in the UK, supports in-depth study, literature research, and technical reference.
Regular seminars and workshops with academics and industry speakers give insight into cutting-edge research and allow you to build your professional network.

Professional Development & Career Orientation:

Learn from a world-leading faculty with strong research credentials and industry links, ensuring your education reflects both theoretical advances and the practical needs of quantitative finance teams.
Graduates often move into quantitative analyst roles, risk and derivative modelling, algorithmic trading desks, and advanced research positions at major banks and hedge funds, and many pursue top-tier PhD programmes.

Progression & Future Opportunities

Graduates of the University of Oxford MSc in Mathematical and Computational Finance go on to build highly competitive careers in quantitative finance, financial engineering, and advanced analytics. Common roles include Quantitative Analyst, Financial Engineer, Risk Analyst, and Data Scientist in Finance, placing you at the forefront of fast-moving international finance and technology-driven trading and risk teams.

University services that support employment: You’ll have access to Oxford’s extensive graduate career support, including personalised coaching, interview preparation, networking events, and career fairs. The Mathematical & Computational Finance community also runs specialist career and industry events, connecting students directly with finance professionals and recruiters.
Employment stats and salary figures: Alumni of this programme are recruited into top banks, hedge funds, and quantitative teams, with early‑career alumni reporting average annual compensation (salary plus bonus) around £100,950, reflecting both the high demand for technical skills and Oxford’s global reputation in quantitative finance.
University–industry partnerships: The programme maintains strong industry engagement, offering seminars, guest presentations, and networking opportunities with major investment banks, trading firms, and tech-driven finance teams. This direct exposure helps students build professional contacts while studying.
Long-term accreditation value: Studied within Oxford’s Mathematical Institute — one of the world’s most respected mathematics departments — this MSc combines mathematics, computing, and finance. The prestige and depth of the training signal exceptional quality to employers worldwide, giving graduates long-term recognition in the competitive quantitative finance market.
Graduation outcomes: Graduates work in mathematics- and computation-intensive financial roles at firms such as Barclays, Citigroup, Deutsche Bank, Goldman Sachs, J.P. Morgan, Nomura, Morgan Stanley, and UBS, as well as hedge funds and quantitative trading groups. Many also pursue PhD study at top research universities for academic or research-focused careers.

Further Academic Progression:
After completing the MSc, students can pursue PhD research in mathematical finance, quantitative finance, financial mathematics, computational methods, or related STEM fields, extending careers into advanced research or specialised industry roles. The strong technical foundation also supports professional certifications and specialised finance credentials for those aiming for senior or specialised positions in finance.