Computational Finance MSc

This degree comprises advanced modules on quantitative and modelling skills, which are essential for 'quant' roles in trading research, regulation and risk. This applied MSc programme is distinctive in that it provides a solid mathematical and statistical foundation together with an education in advanced-level programming.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a dissertation (60 credits).

• Financial Data and Statistics (15 credits)
• Financial Market Modelling and Analysis (15 credits)
• Market Risk Measures and Portfolio Theory (15 credits)
• Numerical Analysis for Finance (15 credits)

Students select 60 credits from optional modules.

• Algorithmics (15 credits)
• Applied Computational Finance (15 credits)
• Database Systems (15 credits)
• Financial Engineering (15 credits)
• Financial Institutions and Markets (15 credits)
• Machine Learning with Applications in Finance (15 credits)
• Market Microstructure (15 credits)
• Networks and Systemic Risk (15 credits)
• Operational Risk Measurement for Financial Institutions (15 credits)
• Software Engineering (15 credits)
• Stochastic Processes for Finance (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

With permission, a student may substitute up to two optional modules with electives.

All students undertake an independent research project which culminates in a dissertation of about 10,000 words or 50 pages. Usually this will be undertaken during a summer placement in an industry environment arranged by the department.

The programme is delivered through a combination of lectures, tutorials, seminars, and project work. It comprises two terms of teaching, followed by examinations and a dissertation. Assessment is through coursework, unseen examinations and a dissertation.