Postgraduate Study

This course will equip you with the core concepts and mathematical principles of modern quantitative finance, along with the operational packages (mainly Matlab) for financial modelling. As well as traditional topics in derivatives and asset pricing, we emphasise risk management in non-Gaussian environments with extreme events.

You'll need a first degree in a quantitative subject such as computer science, mathematics, statistics, physics, economics or finance. However, no finance or computing background is assumed.

Algorithmic trading focuses on real-time trading activities in an electronic exchange system. Financial 'tick-by-tick' data sets provide deep insights into the price formation process at the microstructure level and have been used to study topics such as price discovery, order choice behaviour of market participants and optimal order placement strategy. This course will equip you with both the core concepts and quantitative methods in high-frequency finance and the operational skills to use state-of-the-art computational methods for financial modelling.

You'll need a first degree in a quantitative subject such as computer science, mathematics, statistics, physics, economics or finance.

Financial Technology (also known as FinTech) is increasingly important in financial and economic organisations. The impact of technology such as robo-advisors for personal investments, mobile banking apps, and cryptocurrency, cannot be underestimated.

As a result there is a growing need for financial institutions to recruit staff with expertise in FinTech. Our Masters course will give you the skills to apply advanced computing methods to the world of finance, covering areas including blockchain, artificial intelligence, and data analytics. Alongside the computer science side, you will explore economics and business aspects of Fintech.