Oxford Brookes University

What you'll study

The programme integrates traditional finance subjects with modern analytics methods. Typical taught modules cover corporate finance and valuation, investment and portfolio management, derivatives and risk management, and applied financial econometrics. Parallel analytics modules introduce statistical inference, time series analysis, programming for data analysis (often using Python or R), machine learning for finance, and database/Big Data techniques for handling financial datasets.

Teaching blends lectures, seminars and practical labs. You will work on case studies and hands‑on projects that use real or simulated market data to build forecasting, trading and risk assessment models. The course culminates in a research dissertation or a consultancy project where you apply finance and analytics tools to an industry problem, producing a written report and oral presentation.

Core and typical optional modules

• Financial Markets and Instruments — foundations of asset pricing, market microstructure and instruments.
• Corporate Finance and Valuation — capital structure, investment appraisal and valuation techniques.
• Financial Econometrics — time series methods, volatility modelling and forecasting.
• Programming for Finance — practical coding for data manipulation, back‑testing and model implementation.
• Machine Learning in Finance — supervised and unsupervised methods applied to credit scoring, algorithmic trading and fraud detection.
• Risk Management and Derivatives — measurement and mitigation of market, credit and operational risk; derivative pricing basics.
• Dissertation or Consultancy Project — independent applied research or industry project using quantitative methods.

Entry requirements

Applicants are typically expected to hold a good honours degree in finance, economics, mathematics, statistics, engineering or a related quantitative discipline. Candidates with a lower classification but with relevant professional experience in finance, analytics or programming may also be considered. Admissions assessors look for demonstrable numeracy, familiarity with quantitative methods and an interest in financial applications of data science.

Non‑native English speakers must meet the University's postgraduate English language requirements; evidence of a recognised English language qualification or equivalent is required before enrolment. Applicants may also be invited to provide a personal statement outlining motivation and relevant experience, and shortlisted applicants can be contacted for an interview.

Career prospects

Graduates move into roles that combine finance and data analysis across financial services and industry. Typical career paths include investment analyst, quantitative analyst, risk analyst, financial data scientist, pricing analyst, credit analyst, and roles in fintech and consultancy. The programme prepares students for technical roles that require programming, statistical modelling and financial domain knowledge, and can also provide a foundation for doctoral study in finance or economics for those pursuing research careers.

Oxford Brookes' career services and employer links support job search activities through CV workshops, employer events and networking opportunities with local and national financial firms, fintech startups and consultancy groups.

Why study at Oxford Brookes University

Oxford Brookes offers a city‑centre campus environment within Oxford with access to a strong regional business network and a faculty that combines academic research with industry experience. The Business School places emphasis on applied learning: coursework and projects are designed to reflect the demands of employers in finance and analytics, with opportunities to use professional software and datasets.

Smaller class sizes encourage close interaction with staff and peers, and the University provides career support, elective workshops in programming and analytics, and facilities for collaborative project work. Studying at Oxford Brookes also gives proximity to the broader Oxford innovation ecosystem, which can be useful for students interested in fintech, startups and consultancy opportunities.