This MSc teaches a mix of mathematics, statistics, computer science and finance aimed to provide the quantitative and modelling skills for 'quant' roles in trading, risk, research and regulation.
To find out core information about this degree, such as entry requirements, programme length and cost, visit the UCL prospectus site.
Students undertake modules to the value of 180 credits, which comprises four core modules (60 credits), four optional modules (60 credits), and a research project/ dissertation (60 credits).
Students take 60 credits of compulsory modules.
- Data Science (COMP0047) (15 credits)
- Financial Engineering (COMP0048) (15 credits)
- Machine Learning with Applications in Finance (COMP0050, Term 2) (15 credits)
- Numerical Methods for Finance (COMP0043) (15 credits)
Students select a 60 credits from the programme's optional modules
- Algorithmic Trading (COMP0051) (15 credits)
- Applied Computational Finance (COMP0041) (15 credits)
- Blockchain Technologies (COMP0163) (15 credits)
- Digital Finance (COMP0164) (15 credits)
- Financial Institutions and Markets (COMP0105) (15 credits)
- Financial Market Modelling and Analysis (COMP0075) (15 credits)
- Market Microstructure (COMP0049) (15 credits)
- Market Risk and Portfolio Theory (MATH0094) (15 credits)
- Networks and Systemic Risk (COMP0046) (15 credits)
- Numerical Optimisation (COMP0120) (15 credits)
- Operational Risk Measurement for Financial Institutions (COMP0044) (15 credits)
- Probability Theory and Stochastic Processes (COMP0045) (15 credits)
Research project/ dissertation
Students undertake an independent research project worth 60 credits. The project will be related to a problem of industrial interest or a topic near the leading edge of research, and culminates in a dissertation.
- MSc Computational Finance Project (COMP0077) (60 credits)