university of leeds
Master of Science Course in Statistics with Applications to Finance
Faculty of Mathematics and Physical Sciences Year 2014/15 Qualification MSC Entry requirements A BSc 2.1 second-class honours degree or equivalent qualification with an emphasis on mathematical or statistical content. If English is not your first language, then you will need to satisfy the University's English language requirement, which requires a minimum IELTS score of 6.5 overall, with at least 6.0 in each section. Professional accreditations / details of any exemptions This programme is accredited by the Royal Statistical Society. Graduates qualify for Graduate Statistician Status: the first stage of becoming a Chartered Statistician. How to apply You can apply online or if you would prefer you can complete a paper application form. Fees Please see here for information about fees for Taught Postgraduate courses. Scholarships and bursaries Information about Scholarships can be found here. Modes of study and duration of the course 12 Months Full Time Why study? This course is a specialised masters degree programme enabling students from a wide range of backgrounds to both broaden their understanding of statistics and to develop an in-depth understanding of the financial applications of statistics. The programme provides training in a range of statistical techniques (and transferable skills) suitable for either careers in statistical finance and related professions, or for further academic research in statistics. The course consists of two semesters of taught modules, with the third semester devoted to a major dissertation. Modules within the course vary from mainstream topics in statistical methodology to more specialised topics in statistical finance reflecting specific research interests of academic staff within the department including stochastic financial modelling. It is also possible to take options to broaden your general statistics knowledge or branch out in to other specialisations. What you study Modules studied may include: Statistical Computing An introduction to methods of statistical computing. Essential for the applied statistician, with an emphasis on sampling-based methods, such as Markov chain Monte Carlo. Stochastic Financial Modelling Financial investments such as stocks and shares are risky: their value can go down as well as up. To compensate for the risk in a fair market, a discount is needed. This module will develop the necessary probablistic tools to enable investors to value such assets. Risk Management This module gives comprehensive coverage of mathematical and practical approaches to financial risk management. Avoiding the disastrous consequences of badly managed risk requires detailed mathematical knowledge of how to quantify financial risk and stress-test a hedge. Time Series and Spectral Analysis In time series, measurements are made at a succession of times, and it is the dependence between measurements taken at different times which is important. We concentrate on techniques for model identification, parameter estimation and forecasting future values of the time series. A range of other module choices is available, find out more here. Full details of the programme structure and module choices can be found in the Progamme Catalogue. If you would prefer a broader study of statistics, you may wish to consider our MSc Statistics programme. Learning and assessment Most modules are assessed by a mix of coursework and written examinations. The summer project is assessed by a written report and oral examination. What facilities are available The University has excellent facilities, including: one of the best academic libraries in the UK with over 2.8 million items; first class computing facilities which are accessible remotely, via wireless network, or in 24 hour computer clusters; a Language Centre with English Language programmes for international students; and the Edge, a new swimming pool and gym. The School of Mathematics has several spaces for students to work together and share ideas, including computer clusters. There are also dedicated quiet working areas, a Reading Room containing useful reference material, tutorial rooms, and the maths coffee bar, Dolce Vita. Career opportunities The emergence of data-mining and analysis means that demand for statisticians is growing and there are career opportunities in a wide range of professions, in particular, in actuarial companies, banking, the betting and gaming industries and other financial organisations. Alternatively this course provides an ideal basis for progression onto a programme of research as a PhD student. Contact for further information Miss Iwona Malinowska Taught Postgraduate Officer School of Mathematics University of Leeds Woodhouse Lane LEEDS LS2 9JT Phone: +44 (0) 113 343 5111 E-mail: I.Malinowska@leeds.ac.uk Other information To find out more about the MSc Statistics with Applications to Finance or any of our Postgraduate degrees please visit the School of Mathematics postgraduate website.