Course summary

To successfully complete the Financial Mathematics postgraduate course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate. Or you might have a bachelor’s degree in economics or science and in particular computer science, which, coupled with your interest in stochastics, could also qualify you for this programme. You should have a general interest in learning the more technical and mathematical techniques used in financial markets; but you don’t need to have a background in finance. Objectives The master's in Financial Mathematics focuses on stochastics and simulation techniques, but also covers some econometrics. You’ll study core modules covering asset pricing, risk management and an introduction to key financial securities such as equities, fixed income and derivatives. You’ll cover a wide range of elementary and advanced topics in stochastics, including Levy processes and different simulation techniques. You’ll be taught Matlab and VBA and you have the opportunity to learn other programming languages as part of our electives offering, such as Python or C++. There are three ways to complete the third term. Either you’ll choose five electives from around 40 optional modules in your final term. Or you can choose to complete a traditional dissertation, known as a ‘business research project’, which counts for four electives, or a shorter ‘applied research project’, which is the equivalent of two elective modules.