MSc in Financial and Computational Mathematics

General

Program Description

The course teaches advanced financial mathematics combined with computational techniques. You'll learn mathematical techniques and skills that are used across the financial sector to quantify and hedge risk. Practical experience of using statistical software will develop your skills in mathematical modelling.

The programme includes teaching expertise from the School of Mathematical Sciences and the School of Economics. You will study core modules including:

  • Financial Mathematics
  • Computational Applied Mathematics
  • Scientific Computing and C++

Choose optional modules to suit your interests. Expert teaching staff will support you and provide one-to-one guidance through your written dissertation.

A highlight of the course is our partnerships with leading industry and academic experts. The panel includes individuals from Credit Suisse, Oxford University and other organisations. This ensures the degree remains relevant and up to date with changes in quantitative finance. Representatives from companies such as Capital One and Bloomberg also provide guest lectures during the year.

Female aerospace engineer writes equations

Why choose this course?

  • Guest lectures - network with experts from Capital One, Bloomberg and the Financial Conduct Authority.
  • Research-led modules informed by Statistics and Probability and Scientific Computation research groups.
  • Top 10 in the UK for research power and quality (Research Excellence Framework 2014).
  • Advisory board consisting of the leading financial industry and academic experts to ensure MSc is topical.

Course content

On arrival to Nottingham, you will be given the opportunity to select your preferred stream from:

Optional stream one: Mathematics, Statistics and Computing

It complements the core modules with applied mathematics and statistics knowledge.

Optional stream 2A: Econometrics

The focus of this stream is on econometrics. It provides advanced knowledge of mathematical and statistical methods applied in economics and finance. Some modules are taught by the School of Economics.

Optional stream 2B: Microeconomics

The focus of this stream is on microeconomics, with Economics and Finance modules offered by the School of Economics. They are complemented by modules providing advanced knowledge on mathematical methods offered by the School of Mathematical Sciences.

The course is made up of 120 credits of taught modules and a 60 credit financial mathematics dissertation.

Modules

Core modules

  • Advanced Financial Mathematics
  • Computational Applied Mathematics
  • Financial mathematics
  • Financial and Computational Mathematics Dissertation
  • Scientific Computing and C++

Optional stream one: Mathematics, Statistics and Computing

  • Optimization
  • Statistical Foundations
  • Statistical Machine Learning
  • Time Series and Forecasting

Optional stream 2A: Econometrics

  • Econometric Theory
  • Financial and Macro Econometrics
  • Game Theory
  • Mathematics for Engineering Management
  • Time Series Econometrics

Optional stream 2B: Microeconomics

  • 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

Learning and assessment

How you will learn

  • Lectures
  • Problem classes
  • Computer labs
  • Independent study
  • Supervision
  • Presentation

How you will be assessed

  • Examinations
  • Coursework
  • Reports
  • Programming tasks

The mathematics modules of the course are assessed by:

  • Examinations
  • Coursework
  • Written reports
  • Oral reports
  • Programming tasks

The economics modules of the course are assessed by:

  • Examinations
  • Coursework

You will be awarded the Master of Science Degree provided you have successfully completed the taught stage by achieving a weighted average mark of at least 50% with no more than 40 credits below 50% and no more than 20 credits below 40%.

You must achieve a mark of at least 50% in the dissertation.

Contact time and study hours

The number of formal contact hours varies depending on the optional modules you are studying. As a guide, in the Autumn and Spring semesters, you will typically spend around 15 hours per week (between Monday and Friday) in lectures.

You will work on your research project between June and September, usually based at the University.

Teaching is provided by academic staff within the School of Mathematical Sciences and the School of Economics. Modules are typically delivered by Professors, Associate and Assistant Professors. Additional support in small group and practical classes may involve PhD students and post-doctoral researchers.

The majority of your lecturers and tutors will be based within the mathematics building. This means if you need to get in touch with them during office hours, they can be contacted easily as they are close by.

Class sizes are typically no more than 20 students.

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2021 entry.

Home/ UK students

Undergraduate degree 2:1 in mathematics, physics or engineering
Portfolio

Applicants should have a solid background in mathematics including calculus, linear algebra, ordinary differential equations and probability and statistics at degree level.

In exceptional cases, applicants holding a 2.2 with substantial mathematical content may be considered.

EU/ International students

Undergraduate degree 2:1 in mathematics, physics or engineering
International and EU equivalents We accept a wide range of qualifications from all over the world.
Portfolio

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)
English language requirements As well as IELTS (listed above), we also accept other English language qualifications. This includes TOEFL iBT, Pearson PTE, GCSE, IB and O level English.

English language support

If you need support to meet the required level, you may be able to attend a presessional course. Our Centre for English Language Education is accredited by the British Council for the teaching of English in the UK.

For presessional English courses, you must take IELTS for UKVI to meet visa regulations.

If you successfully complete your presessional course to the required level, you can then progress to your degree course. This means that you won't need to retake IELTS or equivalent.

Alternative qualifications

We recognise that applicants have a variety of experiences and follow different pathways to postgraduate study.

We treat all applicants with alternative qualifications on an individual basis. We may also consider relevant work experience.

If you are unsure whether your qualifications or work experience are relevant, contact us.

accounting, report, credit card

Where you will learn

University Park Campus

University Park Campus covers 300 acres, with green spaces, wildlife, period buildings and modern facilities. It is one of the UK's most beautiful and sustainable campuses, winning a national Green Flag award every year since 2003.

Most schools and departments are based here. You will have access to libraries, shops, cafes, the Students’ Union, sports village and a health centre.

You can walk or cycle around campus. Free hopper buses connect you to our other campuses. Nottingham city centre is 15 minutes away by public bus or tram.

Dedicated MSc study room

There is a dedicated workroom for masters students, based within the School of Mathematical Sciences.  It is equipped with desktop computers, this provides a quiet study space.

Careers

Careers advice

We offer individual careers support for all postgraduate students.

Expert staff can 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.

Job prospects

The ability to think logically and critically combined with your problem-solving expertise gained on the course will prepare you for future employment.

Our graduates have gone on to work as business analysts, data scientists and trading analysts.

They work for organisations such as:

  • Capitalab
  • Deloitte
  • DRW

The course also provides suitable training for a PhD in areas such as financial mathematics, quantitative finance, applied mathematics.

Career progression

97.5% of postgraduates from the School of Mathematical Sciences secured graduate-level employment or further study within 15 months of graduation. The average annual salary for these graduates was £28,131.*

* HESA Graduate Outcomes in 2020. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

Last updated Oct 2020

About the School

The Faculty of Science undertakes world-class research spanning wide-ranging topics including quantum physics, plant genomics, human imaging, sustainable chemistry, neuroscience, mathematical modellin ... Read More

The Faculty of Science undertakes world-class research spanning wide-ranging topics including quantum physics, plant genomics, human imaging, sustainable chemistry, neuroscience, mathematical modelling and beyond. We work closely with industry on the training of the next generation of scientists and collaborate worldwide to ensure our research has a major societal impact. The Faculty of Science comprises seven schools and has strong links with the School of Life Sciences and School of Veterinary Medicine and Science. Schools from within the faculty also collaborate with those from the University's other faculties to form various research centres and research institutes. Read less
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