This course focuses on the mathematical modelling and computational techniques used in the financial industry, and on the required background in finance.
- Year of entry: 2020
- Duration: 1 year full-time
- Mode of study: Full-time
- 2:1 (or international equivalent) in mathematics, physics or engineering; a strong mathematics background is essential.
- In exceptional cases, applicants holding a 2.2 (or international equivalent) with substantial mathematical content may be considered.
- IELTS: 6.5 (no less than 6.0 in any element)
- UK/EU fees: £12060
- International fees: £24390
- Start date: September
- Course location: University Park
- School/Department: Science, Mathematical Sciences
- The course is aimed to equip graduates with the skills and knowledge required to work in the financial sector
- The degree has its own advisory board consisting of leading experts from the financial industry and academia to ensure the course stays relevant
- Taught by experts from the School of Mathematical Sciences and the School of Economics
- You will benefit from an industry-engaged course, with regular talks and workshops from industry partners and academics from the University of Nottingham
- Choose optional modules that reflect your future career ambitions
Financial mathematics is a branch of mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Its main aims are to quantify and hedge risks in the financial marketplace.
Effective computational methods are crucial for the successful use of mathematical modelling in finance. This course is designed to reflect this combination of knowledge and skills so that graduates are well equipped to enter the competitive job markets of quantitative finance and related fields. Optional modules equip graduates with foundations of data analytics.
Applicants should have a solid background in mathematics including calculus, linear algebra, ordinary differential equations and probability and statistics at degree level.
Research in the School of Mathematical Sciences
This course is linked to the research undertook in the school. The research groups most closely related are:
- Statistics and Probability
- Scientific Computation
We are ranked top 10 in the UK for research power in our area of assessment in the Research Excellence Framework 2014.
- Advanced Financial Mathematics
- Computational Applied Mathematics
- Financial mathematics
- Financial and Computational Mathematics Dissertation
- Scientific Computing and C++
The structure of the MSc is modular, with individual modules having either 20, 15 or 10 credits.
The MSc degree requires the successful completion of 180 credits, 120 of which are taught modules, and 60 credits of a financial mathematics dissertation.
Students must also take 40 credits restricted to one of the three streams below:
Optional steam one - Mathematics/Statistics and Computing
- Statistical Foundations
- Statistical Machine Learning
- Time Series and Forecasting
The modules Time Series and Forecasting and Statistical Machine Learning provide you with a solid statistical background required in data analytics.
Optional stream two A
- Econometric Theory
- Financial and Macroeconometrics
- Game Theory
- Mathematics for Engineering Management
- Time Series Econometrics
Optional stream two B
- Economics of Corporate Finance
- Game Theory
- Mathematics for Engineering Management
- Microeconomics: Consumer and Firm Behaviour
- Macroeconomics: Economic Cycles, Frictions and Policy
- Monetary Theory and Practice
The above is a sample of the typical modules that we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. This course page may be updated over the duration of the course, as modules may change due to developments in the curriculum or in the research interests of staff.
Teaching methods and assessment
Classes are in the form of teaching/learning sessions, including computer practical sessions.
As future graduates, you will gain experience of the types of problems encountered by academics and quantitative practitioners, both via taught courses and project work in an individual and group environment. Written and oral presentations will also be undertaken at various stages of the course.
The course also includes a substantial individual project, which develops your ability to engage in independent learning. The project will form the basis of your written dissertation.
Other skills that you should develop include the ability to think logically and critically, problem-solving expertise, competent use of relevant software, and effective communication of results.
Advisory board and expert support
To continuously keep the course in touch with changes in the area of quantitative finance, we work with an advisory board comprising experts from financial firms and academia:
- Darren Carlile (Capital One)
- Mike Giles (Oxford University)
- Pat Hagan (Gorilla Science, Florida)
- Phil Harrold (ex PwC)
- Phil McCabe (Bloomberg)
- Tim Sharp (Credit Suisse)
The programme also benefits from expert support by:
- Stefan Hunt (Financial Conduct Authority)
The financial industry operates in a rapidly changing environment and to keep the degree in line with changes happening in the industry, we involve senior experts from financial firms and academia in various aspects of the MSc. For instance, the course director sends an annual report to the board members about the MSc performance and changes, and they will be invited to comment. Members of the board and experts from financial firms are invited to give guest lectures.
To unlock your full potential, we run a number of extracurricular activities, which are an integral part of the course. Activities include talks and workshops by our industrial partners as well as in-house training and talks by leading academics in the school.
We also offer two additional free modules via the Nottingham Advantage Award that are in collaboration with Capital One and Experian.
Meet the academic
Dr Andrea Cangiani, Course Director
I have extensive world-class research expertise in mathematical modelling and numerical analysis of Partial Differential Equations. My research is both fundamental (design and numerical analysis of new approaches) and applied with impact cases being developed through interdisciplinary funded projects.
I have long-standing experience in lecturing applied mathematics and scientific computing. Based on my teaching experience, I wrote lecture notes on Computational Partial Differential Equations which are used for teaching the core Computational Applied Mathematics module. I currently teach the Scientific Computing and C++ module which is also core for this course, and I supervise a few MSc dissertations every summer.
In developing, supporting and teaching on this course, I follow the principle that a specialised MSc should equip graduates with skills and knowledge required to be competitive on the highly demanding job market. As Course Director, my duty is to ensure the quality of the degree and its smooth running. I’m also involved in organising extracurricular activities and providing career advice for MSc students.
Careers and professional development
This course offers a solid grounding in financial mathematics and will prepare you for quantitative roles in banks and other financial institutions dealing with risk analysis and management.
The course also provides training suitable for admission on PhD programmes in financial mathematics and quantitative finance.
Average starting salary and career progression
100% of postgraduates in the School of Mathematical Sciences secured work or further study within six months of graduation. The average starting salary was £30,800, with the highest being £60,000.*
* Known destinations of full-time home postgraduates who were available for employment, 2016/17. Salaries are calculated based on the median of those in full-time paid employment within the UK.
Careers support and advice
We offer individual careers support for all postgraduate students whatever your course, mode of study or future career plans.
You can access our Careers and Employability Service during your studies and after you graduate. Expert staff will help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.
More than 1,500 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.
Fees and funding
As a student on this course, we do not anticipate any extra significant costs, alongside your tuition fees and living expenses. You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies which you would need to factor into your budget.
Scholarships and bursaries
School scholarships for UoN UK alumni
We invite our alumni to continue with us for masters study. 10% of the alumni scholarships may be offered to University of Nottingham graduates (both UK/EU and International) who have studied at the UK campus, for 2020/2021 entry.
In 2020/21 a limited number of scholarships of up to £2,000 will be awarded by the School of Mathematical Sciences to international students which will allow you to also apply for other scholarships.
Government loans for masters courses
Masters student loans of up to £10,906 are available for taught and research masters courses. Applicants must ordinarily live in the UK or EU.
International and EU students
Masters scholarships are available for international and EU students from a wide variety of countries and areas of study. You must already have an offer to study at Nottingham to apply. Please note closing dates to ensure you apply for your course with enough time.
This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.
About the School
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