A UK 2:1 degree, or its international equivalent, in mathematics or a mathematical subject such as statistics, physics or engineering. You must also have relevant programming experience (at least one semester undergraduate programming course, in any language e.g. C, C++, Java, Python, passed at 2:1 level).
For 2020 entry we accept the following English language qualifications at the grades specified*:
IELTS Academic: total 6.5 with at least 6.0 in each component.
TOEFL-iBT (including Special Home Edition): total 92 with at least 20 in each section. We do not accept TOEFL MyBest Score to meet our English language requirements.
PTE Academic: total 61 with at least 56 in each of the Communicative Skills scores.
CAE and CPE: total 176 with at least 169 in each paper.
Trinity ISE: ISE II with distinctions in all four components.
For 2021 entry we will accept the following English language qualifications at the grades specified*:
IELTS Academic: total 6.5 with at least 6.0 in each component.
TOEFL-iBT (including Special Home Edition): total 92 with at least 20 in each section.We do not accept TOEFL MyBest Score to meet our English language requirements.
CAE and CPE: total 176 with at least 169 in each paper.
Trinity ISE: ISE II with distinctions in all four components.
*(Revised 21 February 2020 to remove PTE Academic from 2021 entry requirements. Revised 21 April 2020 to include TOEFL-iBT Special Home Edition in 2020 and 2021 entry requirements.)
Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.
The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods.
Currently graduates in this field are expected to have a working knowledge of advanced computational finance (including construction of algorithms and programming skills) as well as a sound knowledge of the theory of Probability and Stochastic Analysis. These are the core theories needed in the modern valuation of complex financial instruments.
This MSc programme delivers:
a flexible programme of study relevant to the needs of employers such as: top investment banks, hedge funds and asset management firms
a solid knowledge in financial derivative pricing, risk management and portfolio management
the transferable computational skills required by the modern quantitative finance world
More info: Click here
You must obtain a total of 180 credits to be awarded the MSc. Over semesters 1 and 2, you will take compulsory courses worth a total of 85 credits and optional courses worth a further 35 credits. Successful performance in these courses (assessed through coursework or examinations or both) allows you to start work on a three-month dissertation project, worth 60 credits, for the award of the MSc degree.
There are two streams: the Financial stream and the Computational stream.
Compulsory courses previously offered include (both streams):
Stochastic Analysis in Finance (20 credits, semester 1)
Discrete-Time Finance (10 credits, semester 1)
Finance, Risk and Uncertainty (10 credits, semester 1)
Object-Oriented Programming with Applications (10 credits, semester 1)
Risk-Neutral Asset Pricing (10 credits, semester 2)
Stochastic Control and Dynamic Asset allocation (10 credits, semester 2)
Numerical Probability and Monte Carlo (10 points, S2)
Research-Linked Topics (10 credits, semesters 1 and 2)
Find out more about compulsory and optional courses
We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.
Optional courses previously offered include:
Numerical Partial Differential Equations (10 credits, semester 2) Time Series (10 credits, semester 2) Financial Risk Theory (10 credits, semester 2) Optimization Methods in Finance (10 credits, semester 2) Integer and Combinatorial Optimization (10 credits, semester 2) Bayesian Theory (10 credits, semester 1) Credit Scoring (10 credits, semester 2) Python Programming (10 credits, semester 1) Scientific Computing (10 credits, semester 1) Programming Skills - HPC MSc (10 credits, semester 1) Parallel Numerical Algorithms - HPC MSc (10 credits, semester 1) Applied Databases (10 credits)
Additional compulsory courses for Financial stream previously offered include:
Financial Risk Theory (10 credits, semester 2) Optimization Methods in Finance (10 credits, semester 2) Numerical Partial Differential Equations (10 credits, semester 2) Time Series (10 credits, semester 2)
Additional compulsory courses for Computational Stream previously offered include:
Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.
