Statistics with Applications to Finance MSc

Data is integral to our society and there’s an ongoing demand for numerate specialists in a broad range of industries. From finance to governmental departments, the emergency services to gaming – the career opportunities that’ll open up to you with a Statistics MSc could be far-reaching.

Our Statistics with Applications to Finance MSc is a focused degree programme which enables you to broaden and deepen your understanding of statistics and financial applications. It combines in-depth training in mainstream advanced statistical modelling with a specialisation in financial mathematics.

As well as the statistics expertise from within the School of Mathematics, the MSc also draws on experience in financial mathematics from Leeds University Business School.

Both the School of Mathematics and the Leeds University Business School are home to specialist facilities and passionate academics who are experts in their fields. These Schools are also responsible for delivering internationally excellent research and have strong links with industry and a whole range of research institutions.

This means, once you’ve graduated, you’ll be fully equipped with the most up-to-date practices and techniques, alongside the technical skill set you’ll need to pursue an exciting career in a variety of job roles.

Why study at Leeds:

• This Masters degree is accredited by the Royal Statistical Society.
• Our globally-renowned research conducted right here on campus in the School of Mathematics and Leeds University Business School feeds directly into the course, shaping your learning with the latest thinking in areas such as probability and financial mathematics, modern applied statistics and analysis.
• Benefit from our School’s close links with organisations like Leeds Institute for Data Analytics, Leeds Institute for Fluid Dynamics and the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.
• Advance your knowledge and skills in key areas of statistics, risk management and time finance.
• Tailor the degree to suit your specific interests with a large selection of optional modules to choose from, with everything from programming to statistical computing, mixed models to linear regression – plus many more.
• Put theory into practice by conducting a project which focuses on a topic that matches your interests, giving you the chance to apply the knowledge acquired throughout the course and demonstrate independent research skills necessary for a professional or academic career.
• Access excellent teaching facilities and computing equipment throughout the school, complemented by social areas and communal problem-solving spaces.
• Experience expert theoretical and practical teaching delivered by a programme team made up of academics who specialise in a wide range of areas in mathematics and statistics.
• Be part of a diverse and supportive community of mathematicians from all over the world.

Accreditation

Accreditation is the assurance that a university course meets the quality standards established by the profession for which it prepares its students.

This course is accredited by the Royal Statistical Society

The first two semesters of your course will consist of taught modules and in the third semester you'll devote your time to a major dissertation. Within each semester you'll take compulsory modules, with some optional modules available to suit your individual needs to broaden your knowledge in statistics.

In the first two semesters you’ll be introduced to forecasting future values within a time series and explore financial investments such as stocks and shares and develop the necessary probabilistic tools to evaluate risks within the market.

You’ll also look at risk assessment in detail, gaining comprehensive knowledge of mathematical and practical approaches to financial risk management. Avoiding the disastrous consequences of badly managed financial risk requires detailed mathematical knowledge of how to quantify that risk. The course also covers the pricing of financial assets.

Project work

Your third semester will be taken up by a dissertation in statistics. This will consist of a three-month research project undertaken in the summer on a topic chosen in conjunction with project supervisors, culminating in a dissertation on that project.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Statistics with Applications to Finance MSc in the course catalogue

Year 1 compulsory modules

Discrete Time Finance – 15 credits

In this module, you will develop a general methodology for the pricing of financial assets in risky financial markets based on discrete-time models. You will learn what the main instruments in financial markets are; apply the concepts of no-arbitrage and mean-variance to calculate fair prices of assets in one-period models; learn about the Capital Asset Pricing Model and apply the Arbitrage Pricing Theory.

Continuous Time Finance – 15 credits

You will learn about the pricing of financial assets in risky financial markets based on
continuous-time models. You will understand continuous-time stochastic processes and how to interpret a stochastic differential equation and its solution.

Risk Management – 15 credits

This module covers the different sorts of risk to which financial investments are exposed, basic and sophisticated derivates commonly used for hedging, expected utility theory, models of incomplete markets, Value-at-Risk and other risk measures, credit risks and credit derivatives, methods to determine the effectiveness of a hedge, stress-testing of risky investment portfolios. On completion of this module you will be familiar with the fundamentals of risk management and you will be able to apply the concepts and models to analyse actual investments.

Time Series and Spectral Analysis – 15 credits

The module will concentrate on techniques for model identification, parameter estimation, diagnostic checking and forecasting within the autoregressive moving average family of models and their extensions. You will learn about transformations and differencing to deal with non-stationarity, the incorporation of seasonal dependence into the model to deal.

Dissertation in Statistics – 60 credits

You’ll be required to complete a research project over the summer. This is an opportunity for you to pursue a particular topic in-depth. Your supervisor will help you to find a project that matches your interests and motivations for studying this degree.

Optional modules

Please note: The modules listed below are indicative of typical options.

• Mixed Models – 10 credits
• Bayesian Statistics – 10 credits
• Generalized Linear Models – 10 credits
• Mixed Models with Medical Applications – 15 credits
• Introduction to Programming – 5 credits
• Computations in Finance – 15 credits
• Linear Regression, Robustness and Smoothing – 20 credits
• Multivariate and Cluster Analysis – 15 credits
• Bayesian Statistics and Causality – 15 credits
• Generalised Linear and Additive Models – 15 credits
• Independent Learning and Skills Project – 15 credits
• Statistical Computing – 15 credits

Learning and teaching

This programme is taught jointly between the School of Mathematics and the Leeds University Business School. You'll study a mixture of modules taught by specialists in each school though a combination of lectures and small group workshops.

Extensive use is made of IT and a wide range of materials are available to enhance and extend the material taught formally.

On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester 3 project is assessed by a written dissertation and a short oral presentation.

Entry requirements

A bachelor degree with a 2:1 (hons) in a subject containing a substantial mathematical and statistical component.

You’ll have a foundation in statistics including strong grades in statistical modules (no key marks below 2:2). We may ask for further detailed module information if these are not clear on your transcript.

We do not normally accept degrees in Accountancy or Finance.

International

We accept a range of international equivalent qualifications. For more information, please contact the Admissions Team.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.

Improve your English

International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.

This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks). 

We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

How to apply

Application deadlines

Please read our How to Apply page for full details, including application deadlines and what to include with your application.

Applicants are encouraged to apply as early as possible.

30 June 2025 – International applicants

12 September 2025 – UK applicants

Click below to access the University’s online application system and find out more about the application process.

If you're still unsure about the application process, contact the admissions team for help.

Apply

Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

Admissions policy

University of Leeds Admissions Policy 2025

Fees

• UK: £14,500 (Total)
• International: £31,750 (Total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

There is a shortage of well-qualified statisticians globally. Numeracy, in general, is an attribute keenly sought after by employers. The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of sectors, including:

• Actuarial, betting and gaming industries
• Charitable organisations
• Commercial, environmental and financial organisations
• Forensic and police investigation
• Government departments
• Market research
• Medical and pharmaceutical organisations

The course is designed specifically to meet this demand.

Plus, University of Leeds students are among the top 5 most targeted by top employers according to The Graduate Market 2024, High Fliers Research.

Many statistical careers require people educated to Masters degree level. This course is designed to build on existing mathematical skills and deepen knowledge of statistics in order for you to access a variety of professions or pursue further research as a PhD student.

Here’s an insight into some of the job positions and organisations previous statistics graduates have secured:

• Statistical Specialist, Osmunda Group
• Statistical Consultant, University of Sheffield
• Statistician, Unilever
• Statistician, CSS
• Risk Analyst, Albourne Cyprus Limited
• Bio Statistician, King Khaled Eye Specialist Hospital
• Data Scientist, City Football Group
• Programme Analyst, Journey Further
• Actuary, Xafinity Consulting Ltd
• Data Scientist, IBM
• Assistant Professor-Biostatistics, University of South Florida
• Chief Planning Officer, Health Department-KP

Careers support

At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability Team who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide guidance and support, ensuring you are prepared to take your next steps after graduation and get you where you want to be.

• Employability events — we run a full range of events including careers fairs in specialist areas and across broader industries — all with employers who are actively recruiting for roles.
• MyCareer system — on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
• Qualified careers consultants — gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, write your CV and cover letter, research before interviews and brush up on your interview skills.
• Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.

Explore more about your employability opportunities at the University of Leeds:

Find out more about career support.