Computational Mathematical Finance

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

Links with Industry

The School of Mathematics has connections with a wide number of industrial partners, organisations, charities and government departments. As an MSc student in the School you will have opportunities to engage with these external organisations through regular employability events, careers workshops, and our annual analytics challenge (whose recent partners have included Edinburgh Airport and the Data and Marketing Association). There is also the opportunity to undertake a dissertation project with an external partner.

Recent partners for industry-based dissertations in the Computational Mathematical Finance MSc include:

* Moody's Analytics

* Barclays

* Directorate-General for Economic and Financial Affairs – European Commission (ECFIN)

* Predictiva

* Vega Protocol