Master of Computational Finance

 

This degree comprises advanced modules on quantitative and modelling skills, which are essential for 'quant' roles in trading research, regulation and risk. This applied MSc programme is distinctive in that it provides a solid mathematical and statistical foundation together with an education in advanced-level programming.Students undertake modules to the value of 180 credits.The programme consists of four core modules (60 credits), four optional modules (60 credits) and a dissertation (60 credits).


Compulsory modules

  • Financial Data and Statistics (15 credits)
  • Financial Engineering (15 credits)
  • Financial Market Modelling and Analysis (15 credits)
  • Numerical Methods for Finance (15 credits)

Optional modules

Students select 60 credits from the optional group.
  • Algorithmic Trading (15 credits)
  • Applied Computational Finance (15 credits)
  • Database and Information Management Systems (15 credits)
  • Financial Institutions and Markets (15 credits)
  • Machine Learning with Applications in Finance (15 credits)
  • Market Micro structure (15 credits)
  • Market Risk Measures and Portfolio Theory (15 credits)
  • Networks and Systemic Risk (15 credits)
  • Numerical Optimization (15 credits)
  • Operational Risk Measurement for Financial Institutions (15 credits)
  • Probability Theory and Stochastic Processes (15 credits)

Optional modules

Students select 60 credits from the optional group.
  • Algorithmic Trading (15 credits)
  • Applied Computational Finance (15 credits)
  • Database and Information Management Systems (15 credits)
  • Financial Institutions and Markets (15 credits)
  • Machine Learning with Applications in Finance (15 credits)
  • Market Micro structure (15 credits)
  • Market Risk Measures and Portfolio Theory (15 credits)
  • Networks and Systemic Risk (15 credits)
  • Numerical Optimization (15 credits)
  • Operational Risk Measurement for Financial Institutions (15 credits)
  • Probability Theory and Stochastic Processes (15 credits)