MSc in Mathematical Finance Teaching and Learning Strategies

The intended learning outcomes are achieved using the following teaching and learning strategies.

Lectures:

  • present and explore core ideas in the subject of mathematical finance in a form allowing students to appreciate the taxonomy of models and methods;
  • demonstrate solution strategies using leading models through practical examples, and
  • review critically the experience of applications in the finance domain.

Practical Sessions:

  • provide a structured opportunity for students to practice techniques and methods in mathematical analysis of problems in mathematical finance using analytical and computational tools;
  • promote discussion and sharing of ideas in the practice of mathematical analysis in a finance setting, and
  • provide a structured opportunity to develop computational and numerical solutions to problems with guidance from tutors.

Guided reading:

  • recommended texts, key articles and other materials in advance of, or following, lecture classes for the purposes of discussion.

 Course assignments:

  • enable students to tackle practical problems in mathematical finance and abstract analysis relevant to the analysis of finance, and
  • provide an opportunity to demonstrate, and test,  the selection of appropriate analytical and computational tools.

Expert (guest) lectures:

  • provide illustrative cases of the practical application of tools and techniques in mathematical finance from corporate, bank, bond or securities finance in industry, and
  • relate the mathematical and analytical purposes of analysis to the management and organisational context of the financial firm.

Dissertation:

  • enables students to practice the application of mathematical research techniques in an industrial context and/or academic context, and
  • provides an opportunity for students to study in depth a mathematical problem in a financial firm.