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Our Computational Finance MSc will introduce you to the computational methods that are widely used by practitioners and financial institutions in today’s markets. You will get a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics and agent-based modelling. These techniques will be used to understand financial markets from a post-crisis perspective which incorporates findings from the study of financial markets at high-frequency time scales, modern approaches to understanding systematic risk and financial contagion, and disruptive technologies such as distributed-ledgers and crypto-currencies. The course is highly practical, and you'll
A Bachelor's degree with a high (minimum of 65%) 2:1 honours (or international equivalent) in Computer Science or another relevant quantitative discipline (such as Mathematics, Statistics, Physics, Natural Science, Electronic Engineering, General Engineering, Operations Research, or a joint degree in two such subjects). Applicants should also have a sound background in basic mathematics, in particular familiarity with standard concepts of calculus, trigonometry, linear algebra, vectors and matrix mathematics. In addition, applicants should be competent in computer programming, close to the level expected at the end of the first year of a BSc honours degree in computer science.
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Computational Mathematical Finance MSc
University of Edinburgh