|Study location||United Kingdom, Colchester Campus|
|Type||Master courses, full-time|
|Nominal duration||1 year|
|Tuition fee||£14,500 per year|
Undergraduate diploma (or higher)
A degree with an overall high 2:2.
The entry qualification documents are accepted in any language
IELTS: 6.0 overall (with a minimum component score of 5.5)
At least 1 reference(s) must be provided.
Reference should be written on official letterhead, signed and dated. Please upload it in the Documents section.
In recent years, finance has been one of the areas where high-calibre mathematicians have been in great demand. With the advent of powerful and yet economically accessible computing, online trading has become a common activity, but many have realised that a certain amount of mathematics is necessary to be successful in such fields.
One of our most popular courses, MSc Mathematics and Finance allows those with a background in mathematics to study finance. Since finance routinely involves modelling and evaluating risk, asset pricing and price forecasting, mathematics has become an indispensable tool for this study.
You explore topics including:
- Models and mathematics in portfolio management
- Risk management in modern banking
- Financial modelling
- Actuarial modelling
- Applied statistics
Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.
Mathematics of Portfolios
Research Methods in Finance: Empirical Methods in Finance
Applied Statistics (optional)
Bank Strategy and Risk (optional)
Bayesian Computational Statistics (optional)
Combinatorial Optimisation (optional)
Derivative Securities (optional)
Economics of Financial Markets (optional)
Financial Derivatives (optional)
Ordinary Differential Equations (optional)
Partial Differential Equations (optional)
Statistical Methods (optional)
Metric Spaces (optional)
Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.