Computational Mathematical Finance (MSc)

at University of Edinburgh

This programme involves two taught semesters of compulsory and optional courses followed by your dissertation project. There are three streams: the Financial stream, the Computational stream and the Machine Learning stream. Each stream features different sets of compulsory and optional courses.
 

There are three streams: the Financial stream, the Computational stream and the Machine Learning stream*. Each stream features different sets of compulsory and optional courses.
 

Compulsory courses (for all streams) have previously included:

• Stochastic Analysis in Finance
• Discrete-Time Finance
• Python Programming
• Numerical Probability and Monte Carlo
• Risk-Neutral Asset Pricing
• Stochastic Control and Dynamic Asset allocation
• Research Skills for Financial Mathematics
   

Financial stream compulsory courses have previously included:

• Financial Risk Theory
• Optimization Methods in Finance
   

Computational stream compulsory courses have previously included:

• Time Series
• Numerical Partial Differential Equations
   

Machine Learning stream compulsory courses have previously included:

• Machine Learning in Python
   

Optional courses have previously included:

• Blockchains and Distributed Ledgers*
• Programming Skills*
• Finance, Risk and Uncertainty
• Bayesian Theory
• Reinforcement Learning*
• Algorithmic Game Theory and its Applications*
• Financial Risk Theory
• Credit Scoring
• Optimization Methods in Finance
• Bayesian Data Analysis
• Integer and Combinatorial Optimization
• Time Series
• Numerical Partial Differential Equations