MSc Statistics with Applications to Finance

Year 1

(Award available for year: Master of Science)

Learning outcomes

On completion of the year/programme students should have provided evidence of being able to:
- demonstrate thorough understanding of the theory and application of key statistical methods
- demonstrate thorough understanding of some specialised topics in statistical finance
- appreciate the specialised nature of data which evolve sequentially in time
- apply statistical methods in well-defined contexts, showing judgement in the selection and application of tools and techniques
- understand complex statistical inferences, identifying the assumptions and conclusions made
- demonstrate by the writing of a project appropriate transferable skills and the ability to work under guidance
- apply key programming skills, both in data analysis and mathematical typesetting
- operate as a statistician for a range of careers in the financial industry
- express mathematical concepts and statistical analysis in both written and verbal form.

Transferable (key) skills

Masters (Taught), Postgraduate Diploma students will have had the opportunity to acquire the following abilities as defined in the modules specified for the programme:
- the skills necessary to undertake a higher research degree and/or for employment in Statistical Finance
- evaluating their own achievement and that of others
- self direction and effective decision making in complex and unpredictable situations
- independent learning and the ability to work in a way which ensures continuing professional development
- critically to engage in the development of professional/disciplinary boundaries.

Assessment

Achievement for the degree of Master (taught programme) will be assessed by a variety of methods in accordance with the learning outcomes of the modules specified for the programme and will involve the achievement of the students in:
- evidencing an ability to conduct independent in-depth enquiry within a specialist topic in Statistical Finance
- demonstrating the ability to apply breadth and/or depth of knowledge to Statistical Finance
- drawing on a range of perspectives on particular topics in Statistical Finance
- evaluating and criticising received opinion
- make reasoned judgements whilst understanding the limitations on judgements made in the absence of complete data.