Financial and Computational Mathematics MSc

 
  

Fact file

Qualification
MSc Financial and Computational Mathematics
Duration
1 year full-time
Entry requirements
2:1 (upper second class honours degree or international equivalent) in mathematics, physics or engineering. A strong mathematics background is essential.
Other requirements
In exceptional cases applicants with a 2.2 (lower second class honours degree or international equivalent) with substantial mathematical content may be considered.
IELTS
6.5 (with no less than 6.0 in any element)

If these grades are not met, English preparatory courses are available
Start date
September
Campus
University Park Campus
School/department
Tuition fees
You can find fee information on our fees table.
 

Overview

This course focuses on the mathematical modelling and computational techniques used in the financial industry, as well as the required background in finance.
Read full overview

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. The MSc in Financial and Computational Mathematics is designed to reflect this combination of knowledge and skills so that its graduates are well equipped to enter the competitive job markets of quantitative finance and related fields.

The course is focused on computational techniques and mathematical modelling used in the financial industry and on the required background in finance. Optional modules also equip graduates with foundations of data analytics. The course is provided by the School of Mathematical Sciences with valuable input from the School of Economics. To ensure that the degree keeps pace with changes in employer expectations and employment opportunities, the course has its own advisory board which consists of leading experts from the financial industry and academia.

Applicants should have a solid background in mathematics including calculus, linear algebra, ordinary differential equations and basic techniques used in probability and statistics.

Key facts

  • The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 70 full-time academic staff.
  • The REF 2014 results place the School in the top 10 nationally within Mathematical Sciences for 'research power' and 'research quality'; with 32% of its research recognised as world-leading and a further 56% as internationally excellent. 
  • The research environment was classified as 75% world-leading in vitality and sustainability, with the remaining 25% internationally excellent, reflecting the outstanding setting the School provides for its academic staff as well as its postdoctoral and postgraduate researchers.
  • The course has its own advisory board (see below) consisting of leading experts from the financial industry and academia.
  • The course is offered in collaboration with the School of Economics.

Advisory Board and Expert Support

To continuously keep Financial and Computational Mathematics MSc 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 are involving 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.

 

Course details

The MSc Financial and Computational Mathematics is a full-time degree studied over a period of approximately 12 months commencing from late September. Students on this course take taught modules and prepare a dissertation. Classes are in the form of teaching/learning sessions, including computer practical sessions, which take place during normal semesters.

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 dissertations. 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.

Prerequisite Information

The MSc Financial and Computational Mathematics is designed for students with a first degree in mathematics or a related subject with substantial mathematical content (e.g. engineering and physics, computer science and economics). If you’re taking this MSc you won’t need a background in finance, just enthusiasm and a willingness to learn the subject.

The following book gives an indication of the level of mathematics required:

  • All the Mathematics You Missed (But Need to Know for Graduate School), Thomas A Garrity (CUP).

A basic understanding of the content of chapters 1-3 and 12-16 would be advisable.

Scientific Computing

  • An Introduction to Numerical Analysis, Endre Suli and David Mayers (CUP).

You should be able to understand, with some work (reading maths books is never easy!), chapters 1-2, 6-7 and 11-12. Alternatively, you can use the textbook Numerical Mathematics by Alfio Quarteroni, Riccardo Sacco, Fausto Saleri published by Springer, where you can examine the basics of chapters 1-3, 6, 8-11 and 13.

Probability and Statistics

Applicants should be familiar with elementary probability and statistics. The following are suggested as basic texts for revision purposes:

  • Introductory Probability and Statistical Applications, P.L. Meyer
  • Probability (first two chapters), A.N. Shirayev
  • A First Course in Probability, S.M. Ross
  • Probability and Math Statistics, L.D. Taylor

C++

We do not require any prior knowledge of C++. You may however wish to look through any introductory book on C++ such as:

  • Guide to Scientific Computing in C++, J.P. Francis and J. Whiteley, J.R. Hubbard
  • Schaum's Outline of Programming with C++,  J.R. Hubbard
  • Schaum's Outline of Fundamentals of Computing with C++ (or the online tutorial)

Financial Mathematics

Likewise, we do not require any prior knowledge of financial mathematics or finance but if you would like to undertake some preliminary reading, you can refer to:

  • Stochastic Calculus for Finance, S.E. Shreve (I. Springer, 2004)
  • Introductory Course on Financial Mathematics, M.V. Tretyakov (ICP, 2013)

Extracurricular Activities

To improve students’ practical skills and knowledge, 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.

Take a look at what is happening this current academic year.

 
 

Modules

The structure of the MSc is modular, with individual modules having either 20, 15 or 10 credits. One credit represents 10 hours of student work, meaning that a 20 credit module represents 200 hours of study including formal teaching, independent study, revision, and the preparation of assessments. The MSc degree requires the successful completion of 180 credits, 120 of which are taught modules, and 60 credits of a financial mathematics dissertation.

There may be slight variations in the lists of modules permitted in any particular year.

Compulsory

The Financial Mathematics module introduces the main concepts of financial mathematics, such as pricing and hedging of financial instruments (forwards, futures, options, swaps) with a focus on discrete models. It also develops your knowledge of probability and stochastic calculus.

The Advanced Financial Mathematics module builds upon the concepts from finance and your knowledge of probability and stochastic processes introduced in the Financial Mathematics module. It has three major topics: continuous time modelling for equity derivatives pricing, pricing interest rate (fixed-income) derivatives, and credit risk modelling, which are underpinned by the theory of stochastic processes and stochastic differential equations. In these two modules you will acquire knowledge and skills relevant to the mathematical modelling widely used in the financial industry for financial risk management.

The modules Scientific Computing and C++ and Computational Applied Mathematics aim at improving and developing your knowledge of computational techniques which are widely used in the financial industry and at learning programming in C++.

Previous Financial and Computational Mathematics Dissertation topics included:

  • Feature generation project: Statistical techniques and the probability of default (with a collaborating financial firm)
  • The optimal portfolio rebalancing strategy with trading costs
  • A modified SABR model for pricing FX options (with a collaborating financial firm)
  • Jumps in high-frequency financial data
  • Extension of the skew normal distribution and applications in financial options pricing (with a collaborating financial firm)
  • Credit value adjustment for interest rate swaps
  • Deciphering your credit score (with a collaborating financial firm)

Students must also take 40 credits restricted to one of the three streams below:

Optional Stream 1
(Mathematics/Statistics and Computing)

The modules Time Series and Forecasting and Statistical Machine Learning provide the graduates with solid statistical background required in data analytics.

Optional Stream 2A

Optional Stream 2B

The modules we offer are inspired by the research interests of our staff and as a result may change for reasons of, for example, research developments or legislation changes. This list is an example of typical modules we offer, not a definitive list.

 
 

Funding

UK/EU Students 

Postgraduate loans

The government offers loans of up to £10,280 for students studying a taught or research masters course commencing in September 2017.

These loans will be a contribution towards the costs associated with completing a postgraduate masters course and can be used towards tuition fees or living costs as you decide. The loan is non-means tested and will be paid directly to you, the student, rather than the University.

If you are a home student or have UK residential status you will be eligible for a government loan and in some cases EU students may also be eligible.

Full information can be found at the postgraduate loans page on the student services website.

Tuition Fees

Information on current course tuition fees can be found on the University finance pages.

Graduate School

The Graduate School website at the University of Nottingham provides more information on internal and external sources of postgraduate funding.

School scholarships for UoN UK alumni

We invite our alumni to continue with us for masters study. 10% alumni scholarships may be offered to University of Nottingham graduates who have studied at the UK campus, for 2018/19 entry.

International Students

Tuition Fees

Information on current course tuition fees can be found on the University Finance pages

In 2018/19 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.

International and EU students

The University of Nottingham offers a range of masters scholarships for international and EU students from a wide variety of countries and areas of study.

Applicants must receive an offer of study before applying for our scholarships. Please note the closing dates of any scholarships you are interested in and make sure you submit your masters course application in good time so that you have the opportunity to apply for them.

The International Office also provides information and advice for international and EU students on financing your degree, living costs, external sources of funding and working during your studies.

Find out more on our scholarships, fees and finance webpages for international applicants.

 
 

Careers

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. You will gain experience of the type of problems encountered by academic and qualitative practitioners, both via taught courses and project work on an individual and group basis. 

Average starting salary and career progression

In 2016, 89% of postgraduates from the School of Mathematical Sciences who were available for employment had secured work or further study within six months of graduation. The average starting salary was £25,933, with the highest being £35,000.*

*Known destinations of full-time home postgraduates 2015/16. Salaries are calculated based on the median of those in full-time paid employment within the UK.

Career prospects and employability

The University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers** and 
can offer you a head-start when it comes to your career. 

“The pace of change in the financial services sector has never been faster than it is today. Rapid technological advances combined with ever heightening customer expectations require firms and their employees to generate ideas, calculate business cases and build prototypes faster than ever before.  The MSc in Financial and Computational Mathematics at the University of Nottingham provides all the fundamental building blocks for a successful employee working in an analytical role in this challenging environment.” 

Darren Carlile, Capital One

“MSc in Financial and Computational Mathematics at the University of Nottingham is an excellent programme run by one of the top Mathematics departments in the UK. It blends mathematics, finance and computing in a natural and consistent way and equips its graduates very well with knowledge and skills required for quantitative jobs in the financial sector.”

Dr Maria Krivko, Quantitative Analyst at a world-leading financial firm

Those who take up a postgraduate research opportunity with us will not only receive support in terms of close contact with supervisors and 

specific training related to your area of research, you will also benefit from dedicated careers advice from our Careers and Employability Service

Our Careers and Employability Service offers a range of services including advice sessions, employer events, recruitment fairs and skills 
workshops – and once you have graduated, you will have access to the service for life.

** The Graduate Market 2013-2016, High Fliers Research.

 
 
 
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Disclaimer
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.

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