Compulsory

Static and Dynamic Optimisation (15 credits)

The aim of this module is to gain familiarity with theory and techniques of static optimisation and dynamic optimisation.

Mathematical Modelling II (15 credits)

The aims of this module are:

  • To develop skills in the mathematical modelling of real life situations.
  • To develop the ability to work effectively in a group.

Optional

Nonlinear Waves (15 credits)

The aims of this module are to:

  • Introduce students to the main ideas and techniques of the modern theory of nonlinear waves.
  • Demonstrate how these ideas and techniques can be used in a wide range of applications.

Theory of PDEs (15 credits)

The aims of this module are to gain familiarity with modern qualitative theory of linear PDE's with particular emphasis on second-order equations as well as to study selected aspects of modern methods for simple nonlinear PDEs.

Spectral Theory (15 credits)

The aim of this module is to create awareness of the power and range of abstract mathematical concepts through a basic introduction to the methods of spectral theory.

Computational Methods in Finance (15 credits)

This module aims to:

  • Introduce numerical methods and associated theory for modelling of financial options.
  • Teach students how to implement such numerical methods on computers.
  • Gain experience in interpreting numerical results.

Statistical Methods and Data Analysis (15 credits)

This module introduces the use of statistical models for data summary and prediction using the R or Python programming language and R packages.