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Financial Mathematics and Computation with Industry MSc

Financial Mathematics and Computation with Industry MSc

Different course options

Study mode

Full time


2 years

Start date


Key information

Qualification type

MSc - Master of Science

Subject areas

Mathematics For Specific Applications Financial Modelling

Course type


Course Summary

Course description

Quantitative finance is widely recognised as a rapidly expanding market for mathematical and scientific skills. Financial Mathematics is an application of mathematical methods to financial markets and risk management, using advanced computer technology to predict the behaviour of the markets and suggest strategies for investment. The focus of this MSc is on computational techniques for finance, on mathematical modelling and on mathematical and economic theories of finance.

On this course you will learn how to formulate problems from finance in mathematical terms, select and develop an appropriate numerical method, use programming skills to implement the method and compute results, and finally to present and interpret these results for a potential client.

What's the difference?

If you complete the modules but not the project, you will qualify for a Postgraduate Diploma (PGDip). If you complete only some of the modules, you may qualify for a Postgraduate Certificate (PGCert).

Teaching and learning

Teaching methods include lectures, seminars and computer practicals. Assessment is a mixture of coursework assignments, oral presentations and written exams.

Careers and employability

Our Career Development Service is here to support you, with advice on interviews, CVs, work experience, volunteering and more. From Freshers’ Week to Graduation and beyond, they are here to help you reach your professional goals.


This module together with Financial Mathematics 2 will develop probabilistic tools to enable investors to value financial derivatives. Since there are no strict prerequisites on previous knowledge in probability and stochastics, the module contains mathematical preliminaries (probability space, random variables, distributions, independence, conditional expectation, random processes, simple random walks, Markovian property, martingales, stopping times). Stochastics will be taught together with financial models, and the last part of this module starts building the background needed for continuous financial models considered mainly in Financial Mathematics 2. A transition from the binomial model of financial market to a continuous one, Wiener process and its properties, and Stochastic differential equations and geometric Brownian motion will be examined.
Practical Programming - Core
Individual Project (Financial Maths) - Core

Tuition fees

UK fees
Course fees for UK students

For this course (overall cost)


International fees
Course fees for EU and international students

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Entry requirements

Students need to have 2:1 degree (or equivalent) in Maths, Sciences, or Engineering. We will consider a 2:1 degree in a social science (e.g. Economics) on an individual basis, depending on the amount of mathematical subjects you have covered. You will need a fairly solid background in maths including an understanding of calculus, linear algebra, ordinary differential equations, probability and statistics.

University information

For a century, the University of Leicester has been home to great minds; academics, researchers and students who aren’t afraid to challenge the status quo, advance new practices, and develop a fresh way of thinking. Through the ground-breaking work of the university’s expert research groups, postgraduate students will tackle the emerging social, economic, political, and scientific issues head-on and set the agenda where others simply follow....more

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