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MSc Statistics and Computational Finance

MSc Statistics and Computational Finance

Different course options

Study mode

Full time


1 year

Start date


Key information

Qualification type

MSc - Master of Science

Subject areas

Modelling / Simulation Systems Computational Mathematics / Cybernetics Financial Modelling Statistics Finance / Accounting (General)

Course type


Course Summary

Train to work as a professional statistician and gain skills and experience working at the interface between statistics and finance.

Our course emphasises data analysis and will provide you with contemporary statistical ideas and methodologies that are attractive to prospective employers. The skills you gain are useful for a wide range of financial data analysis and in a range of other sectors where data analysis is required, for example sociology, health science, medical science or biology. This experience is also an ideal foundation for further academic study; many of our students choose to progress to PhD.

Our Statistics and Probability Group has a thriving research culture. Our group works with mainstream statistics to develop new methodology and apply it to real-world problems. The team produces world-class research, publishing in top journals. Our graduate students have full access to this expertise, as well as being exposed to forefront research carried out across the globe through our regular seminars and working groups.

This course will equip you with the necessary skills to:

  • translate problems from the workplace into contemporary statistical ideas and methodologies
  • solve problems using your advanced knowledge in statistical modelling and computational finance
  • interpret and communicate your results.

Careers and skills

The big data analysis skills you develop on this course provide attractive employment opportunities in a growing number of industries where such skills are in high demand. The course is also a good foundation for continuing your studies at PhD level.


This module provides essential skills for self-reliantly carrying out statistical data analyses of real data, from the thorough formulation of the question to be investigated up to the presentation of the analysis' results. It is a mainly project-oriented module, where the participants first receive a general introduction to statistical modelling and practical data analysis including an overview of a selected range of statistical methods, then learn how to implement these in the statistical software environment R, before they each carry out and present two statistical analysis projects based on real data sets. The latter constitutes the most significant part of the module. The first and smaller statistical data analysis is carried out in groups of 2 or 3 participants, whereas the second and larger coursework project is to be completed individually. Each of the projects involves the theoretical analysis of the studied problem, the conception of the data analysis, its realization in R, summarizing the analysis in a written report, and the professional presentation of the analysis' results in front of the fellow participants.

Tuition fees

UK fees
Course fees for UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


International fees
Course fees for non-UK / EU students

For this course (per year)


Average for all Postgrad courses (per year)


Entry requirements

2:1 or equivalent in Mathematics or in a subject with a substantial mathematics component. We may accept a 2:2 undergraduate degree supported by relevant professional qualifications.