Candidates for the MSc degree will submit a dissertation of around 45 pages on a selected topic in Statistics or Computational Finance. Support and advice will be provided by individual dissertation supervisors.
Students submitting a dissertation will be expected to demonstrate the ability to absorb and analyse current research literature in Statistics or Computational Finance and to apply their computational modelling skills in concrete situations arising in practice. Original contribution to research, while laudable, will not be required.
Module learning outcomes
By the end of this module students should
demonstrate an ability for in-depth independent research into a chosen topic in Statistics or Computational Finance;
provide evidence in their dissertation of their ability to read and understand current research literature in this field;
develop and/or apply the appropriate computer software to present a solution to the problem at hand;
present the outcome of their research and the background for the chosen topic in a self-consistent, clear, rigorous and accessible manner;
demonstrate the ability to locate and understand current literature in the selected area of their research;
present a critical approach emphasizing the strengths and limitations of the approaches, methods, and solutions studied.
Students will select a topic from a list provided, but will also be encouraged to design their own topic subject to approval by the potential supervisor.
Supervisory backup will be provided individually to each student by means of meetings with the dissertation supervisor when necessary.
% of module mark
Special assessment rules
% of module mark
Dissertation results will be made available shortly after the meeting of the MSc Board of Examiners in November.
Results on reassessment will be made available as soon as possible after the submission date.
Dependent on topic chosen.
Coronavirus (COVID-19): changes to courses
The 2020/21 academic year will start in September. We aim to deliver as much face-to-face teaching as we can, supported by high quality online alternatives where we must.
Find details of the measures we're planning to protect our community.