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The rising sophistication of the financial sector is bringing a great demand for experts with skills across mathematics, finance, statistics and computer science.
About this programme
As a student on the Computational Finance MSc, you will learn advanced quantitative, modelling and programming skills, which are essential for quant roles in trading, research, regulation, and risk. This applied-taught postgraduate programme is distinctive in that it provides a combination of finance, mathematics, statistics, and computer science.
Computational finance is at the intersection of mathematics, statistics, computer science, finance and economics. Elevating your skills in these disciplines is essential if you want to make your mark as a quant in a large bank, hedge fund or financial regulator, or in the world of fintech and innovative start-ups.
You will learn from our world-leading experts in this field. The syllabus is constantly reviewed to stay ahead of the trends; core modules span financial engineering and numerical methods for finance, to data science and machine learning for finance.
Compulsory modules
- Numerical Methods for Finance
- Data Science
- Financial Engineering
- Machine Learning with Applications in Finance
- MSc Computational Finance Project
Optional modules may include:
- Applied Computational Finance
- Operational Risk Measurement for Financial Institutions
- Probability Theory and Stochastic Processes
- Networks and Systemic Risk
- Market Microstructure
- Algorithmic Trading
- Financial Market Modelling and Analysis
- Financial Institutions and Markets
- Numerical Optimisation
- Advanced Machine Learning in Finance
- Blockchain Technologies
- Market Risk and Portfolio Theory
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment, and module content and availability are subject to change.
Who is the programme for?
Entry requirements
This programme is for you if:
- you have a minimum of an upper second-class UK Bachelor's degree (or an international qualification of an equivalent standard) in a relevant discipline (e.g. mathematics, statistics, physics, computer science, engineering, economics, or finance) with a strong quantitative component evidenced by good performance in mathematics and statistics examinations.
- you are looking for a successful career in the finance industry.
- you aim to work as a ‘quant’ in finance, you will need a desire to extend your skill set with an applied, computational focus.
Employability
The programme is designed to teach a blend of skills in mathematics, statistics, computer science and finance, which are highly sought after in the financial industry for a successful career as a quantitative analyst (or quant).
Career destinations
Graduates of this programme go on to work as quantitative analysts, quantitative traders or quantitative developers, plus a range of other jobs in asset allocation, risk management, fintech, regulation, or research for a large spectrum of employers.
They work for large banks such as Credit Suisse and JP Morgan, regulators such as the Bank of England and the Financial Conduct Authority, hedge funds and fintech companies, or they stay in academia to pursue a PhD. Altogether, the options for graduates of the Computational Finance MSc are exciting and varied.
Register below to receive further information about this programme.