Statistics with Financial Mathematics

Entry requirements

Minimum 2:1 undergraduate honours degree in a relevant subject with relevant modules.

Subject requirements

We accept degrees in the following subject areas:

• Applied / Financial Mathematics
• Data Science
• Economic Statistics
• Mathematics
• Statistics;

We may consider other related degree subjects

Module requirements

You should have studied at least one module from Area 1 and at least two modules from Area 2:

Area 1: Mathematics

• Complex analysis
• Complex variable function
• Functional analysis
• Measure theory
• Real analysis
• Real variable function
• Stochastic analysis

Area 2: Probability / Statistics

• Applied statistics
• Bayesian statistics
• Computational statistics
• Data mining/analysis
• Econometrics
• Linear models / generalised linear models
• Markov chains/processes
• Medical statistics
• Multivariate statistics / multivariable statistics
• Non-parametric statistics
• Probability theory/modelling
• Programming languages (e.g. R, Python)
• Sampling / survey design
• Statistical analysis/experiment/modelling
• Statistical software/computing
• Stochastic processes/models/modelling
• Time series

Months of entry

September

Course content

Develop your understanding of a variety of statistical techniques and explore the mathematical concepts, models and tools of the finance industry.

Course description

Our Statistics with Financial Mathematics MSc trains you to apply the probabilistic, statistical and mathematical techniques that are used in the finance industry.

In addition to a variety of statistical techniques, we’ll cover key financial topics such as the Capital Asset Pricing Model, the Black-Scholes option pricing formula and stochastic processes.

You’ll develop a detailed working knowledge of important 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. You’ll gain skills to help you stand out in the graduate job market, such as planning and researching a project, data acquisition, problem specification, analysis and reporting your findings.

External clients, such as pharmaceutical companies or sports modelling organisations, often provide dissertation topics. Distance learning students often come with projects designed by their employer.

Recent examples of dissertation topics include:

• Financial modelling with Lévy processes
• Contagion in Financial Networks

Accreditation

Accredited by the Royal Statistical Society

Please see our University website for the most up-to-date course information: https://www.sheffield.ac.uk/postgraduate/taught/courses

Information for international students

English language requirements

IELTS 6.5 (with 6 in each component) or University equivalent.

Fees and funding

https://www.sheffield.ac.uk/international/fees-and-funding/tuition-fees