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The Computational Finance MSc will introduce students to the computational methods that are widely used by practitioners and financial institutions in today’s markets. This course will provide students with 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 students will have the opportunity to apply their learning to real-world data and case studies in hands-on laboratory sessions.

Key benefits

  • Located in central London, giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS) and the Institution of Engineering and Technology (IET).
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.
  • 92 per cent of research outputs ranked as world leading or internationally excellent – confirming the department’s position as a world-class institution for research in Computer Science (REF 2014).

Description

This course provides an understanding of modern financial technology (FinTech) including electronic trading and distributed-ledger technology. You will gain practical hands-on techniques for working with and analysing financial data, which draw on modern developments in Artificial Intelligence and Big Data technology. There will be opportunity to understand the practical aspects of quantitative finance and FinTech from Industry experts located in the heart of one of the World’s financial centres.

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the course. You will also be expected to undertake a significant amount of independent study.

You are expected to spend approximately 10 hours work per credit for each module you attend in your degree, e.g. 150 hours work for a 15-credit module. These hours cover every aspect of the module.

Assessment

The primary method of assessment for this course is a combination of written examinations, coursework, in-class tests, individual projects and oral presentations. The individual project will be assessed through a dissertation.

Career prospects

The Careers Service and the Department of Informatics run a careers programme for Informatics students, which includes skills sessions and visits from top employers.

Some graduates work in cyber security companies, general software consultancy companies, specialised software development businesses and the IT departments of large institutions (financial, telecommunications, and public sector). Recent employers include Hang Seng Bank, Lloyds Banking Group and Merrill Corporation.

Other graduates have entered into the field of academic and industrial research in areas such as machine learning, software engineering, algorithms and computer networks.

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Visit the Computational Finance MSc page on the King’s College London website for more details!

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