The course trains students to apply the probabilistic, statistical and mathematical techniques that are used in the finance industry. It is based on Sheffield's 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. Students will 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. Students will learn how to analyse and draw meaningful conclusions from data, and develop their programming skills using the statistical computing software R.
Around one-third of the course is devoted to the dissertation. This may focus on investigating a data set, or a more theoretical or methodological topic. The aim is to give students skills to include on their CV, such as planning and researching a project, data acquisition, problem specification, analysis and reporting their 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.
| Level | Masters |
| Discipline | Mathematics |
| Duration | 12 months |
| Intakes | Jan, Sep |
| Application Fees | GBP 0 |
| Tuition Fees | GBP 23250 |
| Campus | Main |
| Language proficiency (minimum) | |
| IELTS | 6.5 |
|---|---|
| TOEFL | 88 |
| PTE | 61 |
| Duolingo | Not Required / Waiver |
| Exam proficiency (minimum) | |
| SAT | Not Required / Waiver |
|---|---|
| ACT | Not Required / Waiver |
| GRE | Not Required / Waiver |
| GMAT | Not Required / Waiver |
Minimum GPA - 73%
105
105
151-200
129
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