This programme is designed for graduates in mathematics, engineering, computer science and finance/economics wishing to pursue careers in the financial services and banking industry. The structure is of an interdisciplinary nature in which graduates coming from different disciplines collaborate to address the computational aspects of market risk. Our core philosophy is to equip our students with the appropriate knowledge in mathematical finance, focusing on a strong development of associated computational methods.

Our Royal Maritime (Heritage) London based campus, close to the financial district of Canary Wharf, enables the department to build ties with market practitioners permitting our students to become part of a wider financial group. Our seminar series, inviting both academics and practitioners, allows you to interact with our external links creating an advantageous learning experience. We provide the knowledge for you to build up your profile of understanding of current research practice in finance.

You will be trained and equipped with the skills for derivatives pricing and make use of non-linear methods for quantitative analysis (programming in Matlab, R and VBA). Our classes include interactive applications that enhance your learning experience through innovative teaching. By utilising research expertise within the department you will graduate with a strong understanding of numerical methods.

You will also develop an understanding for further applicability in relevant fields as in energy commodity markets, where part of our current research focuses on by combining the world leading Agent-Based research team with our Computational Finance applications for crude oil price modelling.

The programme welcomes both recent graduates as well as experienced professional practitioners who wish to further their skills. Programme assessments are all 100% coursework with problems relating to current market practice. A supervised dissertation project takes place after the end of the last teaching term during the summer months. Projects are allocated in March and students are encouraged to work on projects that provide genuine insight into financial markets analysis.

The programme is also available on a part-time basis. For those already at employment the flexible part-time mode of study, two years typically but can be flexible, allows students to be committed to both the MSc programme and employment.

Course Contents

  • English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences) Financial Markets (Dual Award) (15 credits)
  • Masters Project (Maths) (60 credits)
  • Advanced Finite Difference Methods for Derivatives Pricing (15 credits)
  • Computational Methods (15 credits)
  • Mathematical Approaches to Risk Management (15 credits)
  • Mathematical Finance (30 credits)

Entry requirements

Applicants should have:

  • Those who have substantial commercial or industrial experience in a relevant field can be accepted, subject to interview, references, and recommendation from the programme committee.

  • For applicants whose first language is not English, the minimum level of English is an IELTS score of 6.
Program taught in:
  • English (US)

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Last updated February 11, 2019
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