Statistics with Financial Mathematics

Entry requirements

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

Months of entry

September

Course content

Complete your statistics training while studying the mathematical concepts, models and tools of the finance industry.

Course Description

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.

You’ll 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.

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

Around one-third of the course is devoted to your dissertation. This may focus on investigating a data set, or a more theoretical or methodological topic. The aim is to give you skills to include on your CV, such as planning and researching a project, data acquisition, problem specification, analysis and reporting your findings.

Dissertation topics are often provided by external clients – for example, pharmaceutical companies or sports modelling organisations. Distance learning students often come with projects designed by their employer.

Accreditation

Accredited by the Royal Statistical Society

Information for international students

English language requirements

Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.

For more information about entry requirements for international students, please visit our website.