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Computational Mathematical Finance MSc

Computational Mathematical Finance MSc

Key information

Qualification type

MSc - Master of Science

Subject areas

Financial Management Computational Mathematics / Cybernetics

Course type


Course Summary

The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods. Currently graduates in this field are expected to have a working knowledge of advanced computational finance (including construction of algorithms and programming skills) as well as a sound knowledge of the theory of Probability and Stochastic Analysis. These are the core theories needed in the modern valuation of complex financial instruments.

This MSc programme delivers: a flexible programme of study relevant to the needs of employers such as: top investment banks, hedge funds and asset management firms; a solid knowledge in financial derivative pricing, risk management and portfolio management; the transferable computational skills required by the modern quantitative finance world.

At the end of this programme you will have developed personal communications skills, initiative, and professionalism within a mathematical context; developed transferable skills that maximise your prospects for future employment, including writing, oral presentation, team-working, numerical and logical problem-solving, planning and time-management; improved your ability to convey ideas in an articulate fashion, to build upon previous mathematical training and further develop logic and deductive skills; mastered standard and advanced mathematical tools used to solve applied problems relevant to the mathematical finance industry; developed quantitative and computational skills for the proficient fulfilment of tasks in the financial sector. Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.

Different course options

Full time | The University of Edinburgh | 1 year | SEP

Study mode

Full time


1 year

Start date



This course aims to provide a good and rigorous understanding of the mathematics used in derivative pricing and to enable students to understand where the assumptions in the models break down.

Tuition fees

UK fees
Course fees for UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


International fees
Course fees for non-UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


Entry requirements

Students need to have a UK 2:1 degree, or its international equivalent, in mathematics or a mathematical subject such as statistics, physics or engineering. Students must also have relevant programming experience (at least one semester undergraduate programming course, in any language e.g. C, C++, Java, Python, passed at 2:1 level).

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