Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
Study Details: 1 year full time, 2 years part time
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:
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.
A UK 2:1 degree, or its international equivalent, in mathematics or a mathematical subject such as statistics, physics or engineering. You 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).
Please see our website
Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.
This programme involves two taught semesters of compulsory and optional courses followed by your dissertation project. There are three streams: the Financial stream, the Computational stream and the Machine Learning stream. Each stream features different sets of compulsory and optional courses.
There are three streams: the Financial stream, the Computational stream and the Machine Learning stream*. Each stream features different sets of compulsory and optional courses.
Compulsory courses (for all streams) have previously included:
Financial stream compulsory courses have previously included:
Computational stream compulsory courses have previously included:
Machine Learning stream compulsory courses have previously included:
Optional courses have previously included:
*delivered by the School of Informatics
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