MSc Statistics with Financial Mathematics

Complete your statistics training while studying the mathematical concepts, models and tools of the finance industry.
The course trains you to apply the probabilistic, statistical and mathematical techniques that are used in the finance industry.

It's based on our Statistics MSc course, but also includes key financial topics such as the Capital Asset Pricing Model, the Black-Scholes option pricing formula and stochastic processes.

Youll also develop a detailed working knowledge of more general statistical techniques and concepts, including linear and generalised linear modelling, Bayesian statistics, time series and machine learning.

Youll learn how to analyse and draw meaningful conclusions from data, and develop your programming skills using the statistical computing software R.

Your career
This course is great preparation for roles in the finance sector such as banking, actuarial work, pensions and insurance. Employers that have hired graduates from our School of Mathematics and Statistics in finance roles include Goldman Sachs, Lloyds, Aviva, AXA, Amazon, BAE Systems, Deloitte, PwC and the NHS.
This degree satisfies the eligibility criteria for the Royal Statistical Society's Graduate Statistician award a stepping-stone to full professional membership of the RSS and Chartered Statistician status.

Minimum 2:1 undergraduate honours degree, with substantial mathematical and statistical components. In particular, you should have studied the following topics and performed well in assessments on them (for example, a score of at least 60 per cent).
Mathematical Methods for Statistics: ideas and techniques from real analysis and linear algebra, including multiple integration, differentiation, matrix algebra, the theory of quadratic forms.
Probability and Probability Distributions: the laws of probability and of conditional probability, the concepts of random variables and random vectors and their distributions, the methodology for calculating with them, laws of large numbers and central limit phenomena.
Basic Statistics: statistical inference, rational decision-making under uncertainty, and how they may be applied in a wide range of practical circumstances, relevant software, for example, R.

Real analysis and stochastic processes: limits of sequences and series, convergence tests, continuity and differentiability, stochastic processes and the Markov property.
IELTS - Overall score of 6.5 with a minimum of 6.0 in each component,
TOEFL - Overall score of 88 with a minimum of 19 in Listening, 20 in Reading, 22 in Speaking and 19 in Writing,