Course summary
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" and "Contagion in Financial Networks". Accreditation Accredited by the Royal Statistical Society Please see our University website for the most up-to-date course information.
How to apply
International applicants
English language requirements: IELTS 6.5 (with 6 in each component) or University equivalent
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. English language requirements: Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
University of Sheffield
Western Bank
Sheffield
S10 2TN