Overview

Who is it for?

Interested in tackling changes in the financial market in a mathematically sound manner? The MSc in Financial Mathematics will give you the skills to design, implement and change pricing models and analytical tools for risk management, or push new quantitative modelling ideas across different asset classes.

To successfully complete the Financial Mathematics postgraduate course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate.

Or you might have a bachelor’s degree in economics or science and in particular computer science, which, coupled with your interest in stochastic modelling, could also qualify you for this programme.

You should have a general interest in learning the more technical and mathematical techniques used in financial markets; but you don’t need to have a background in finance.

Objectives

The master's in Financial Mathematics focuses on stochastic modelling and simulation techniques, but also covers econometrics, asset pricing, risk management, and offers an introduction to key financial securities such as equities, fixed income products and derivatives.

You will be taught Python and Matlab during terms 1 and 2, and you will have the opportunity to learn other programming languages as part of our electives offering, such as VBA or C.

Term three offers you flexibility within your masters; either by writing a dissertation or undertaking a project, or by completing your postgraduate degree entirely choosing electives.

*You might still see us referred to as Cass Business School. Find out more about our name change.

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Structure

What will you learn

  • You will gain a very good understanding of the technical aspects used in financial markets, including wide ranging financial theory and different financial assets.
  • You will gain a sound knowledge of stochastic modelling and mathematical finance, and also a good understanding of econometrics and programming, in particular Python and Matlab.
  • From the MSc Financial Mathematics you will also understand how the theory is being applied in the financial industry and what practical issues are.
  • In the third term you have three different options how you can complete your MSc, including a project or choosing only electives. Popular electives include Modelling and Data Analysis, Advanced Financial Engineering and Credit Derivatives, Credit Risk Management, Quantitative Risk Management. Introduction to Python.

Induction weeks

All of our MSc courses start with two compulsory induction weeks which include relevant refresher courses, an introduction to the careers services and the annual careers fair.

Assessment methods

Assessment

We review all our courses regularly to keep them up-to-date on issues of both theory and practice.

To satisfy the requirements of the degree course students must complete:

  • nine core courses (Eight at 15 credits each, one at 10 credits)

and either

  • five electives (10 credits each)
  • three electives (10 credits each) and an Applied Research Project (20 credits)
  • one elective (10 credits) and a Business Research Project (40 credits)

Assessment of modules on the MSc in Financial Mathematics, in most cases, is by means of coursework and unseen examination.

Coursework may consist of standard essays, individual and group presentations, group reports, classwork, unseen tests and problem sets. Please note that any group work may include an element of peer assessment.

Term dates

Term dates 2022/23

  • Induction: 12th September 2022 - 23rd September 2022
  • Term one: 26th September 2022 - 9th December 2022
  • Term one exams: 9th January 2023 - 20th January 2023
  • Term two: 23rd January 2023 - 7th April 2023
  • Term two exams: 24th April 2023 - 5th May 2023
  • Term three - international electives: 8th May 2023 - 19th May 2023
  • Term three: 22nd May 2023 - 7th July 2023
  • Term three exams: 10th July 2023 - 21 July 2023
  • Resits: 14th August 2023 - 25th August 2023
  • Additional resit week - tests only: 28th August 2023 - 1st September 2023.

Timetables

Course timetables are normally available from July and can be accessed from our timetabling pages. These pages also provide timetables for the current academic year, though this information should be viewed as indicative and details may vary from year to year.

View academic timetables

Please note that all academic timetables are subject to change.

Teaching staff

Course Director

Course director profile

Dr Dirk Nitzsche

Senior Lecturer in Finance

The teaching staff on the MSc in Financial Mathematics have many years of practical experience working in the financial services sector and are also active researchers in their fields

This knowledge and experience inform the highly interactive lectures that make up the MSc in Financial Mathematics.

Module Leaders include:

Application

How to apply

Documents required for decision-making

  • Transcript/interim transcript
  • Grading system used by your university
  • Current module list if still studying
  • CV
  • Personal statement - this should be around 500 words in length and answer the following:
    • Why have you selected this course? What are your motivating factors?
    • What are your areas of interest within the course?
    • What contributions do you feel you can make to the course?
    • How do you see the course affecting your career plans?

Documents which may follow at a later date

  • English language test result if applicable
  • Confirmation of professional qualification examinations/exemptions/passes, if applicable
  • Two references
  • For a successful application to receive an unconditional status all documents must be verified, so an original or certified copy of the degree transcript must be uploaded to the application form or e-mailed to the relevant Admissions Officer upon request

We cannot comment on individual eligibility before you apply and we can only process your application once it is fully complete, with all requested information received.

Individual Appointments

If you would like to arrange an individual appointment to discuss the application process and be given a tour of the facilities, please complete this form.

Please note - these are subject to availability.

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Terms and conditions

Students applying to study at Bayes Business School are subject to City, University of London's terms and conditions.

Entry requirements

  • A UK upper second class degree or above, or the equivalent from an overseas institution.
  • Your academic background should be in a highly quantitative subject such as mathematics, physics, engineering, economics or computer science and having covered areas such as statistics, linear algebra and calculus.
  • Work experience is not a requirement of this course.

Course Syllabus

You may be requested to provide a syllabus of specific modules undertaken during your studies as part of the assessment process. This is not required at the point of submitting an application and will be requested directly by the admissions team only if required as part of the assessment.

English language requirements

If you have been studying in the UK for the last three years it is unlikely that you will have to take the test.

If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.

IELTS

  • The required IELTS level is an average of 7.0 with a minimum of 6.5 in the writing section and no less than 6.0 in any other section.

Some other English Language tests might be accepted

Fees

UK/EU/International £29,500 Tuition fees are subject to annual change

Fees in each subsequent year of study for continuing students (where applicable) will be subject to an annual increase of 2%. We will confirm any change to the annual tuition fee for continuing students in writing prior to commencing each subsequent year of study (where applicable).

Deposit: £2,000 (usually paid within 1 month of receiving offer and non-refundable unless conditions of offer are not met)

First installment: Half fees less deposit (payable during on-line registration which should be completed at least 5 days before the start of the induction period)
Second installment: Half fees (paid in January following start of course)

Information about Scholarships

Career pathways

Career destinations for MSc Financial Mathematics

Our MSc Financial Mathematics master’s provides you with the opportunity to learn quantitative analysis using stochastic, technical risk management, fixed income security, preparing you for a variety of careers.

Our graduates are well qualified for successful careers within large investment banks, small specialist financial companies or boutique firms. Hear from Financial Mathematics Alumni.

Our dedicated Careers Team will help you identify your ideal career path and work with you to maximise the potential of accomplishing your professional goals.

The MSc in Financial Mathematics also prepares you for a PhD in the areas of Mathematical Finance and Financial Engineering.

Class of 2019 and 2020 Profile

Recent graduates have taken up positions in:

  • Associate Financial Engineer, Intercontinantal Exchange Group
  • Structured Equity Derivatives Off, Credit Suisse
  • Risk Analyst,  Intercontinental Exchang
  • Quant Trader,  Latitude 34
  • Junior Quant, Behaviour Lab
  • Executive, deVere Group
  • Equity Fundamentals Analyst, Bloomberg
  • Associate, PwC

Where they are working now


  • UK - 72%
  • Europe other - 6%
  • Asia -17%

Industry post-master's

25% FInancial services - other
17% IT / Data / News Provider
17% Commercial / Corporate Banking
17% Asset Management / Investment Management
8% Accounting / Auditing Services
Data provided from alumni who completed the annual destination data survey for 2019/20, and for 2018/19.

Alumni stories

Leon Bezverkhni
Leon Bezverkhni
Financial Mathematics
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Hear from our alumni. Discover the real experiences of learning at Bayes and how Bayes helped to boost our graduates' careers.

Read Leon’s story

Course information and statistics (2021/22 cohort)

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23
average age of student body (21/22 cohort)
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Flexibility in the third term to tailor your degree to your career ambitions
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Learn from leading experts with practical experience
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Learn unique programming languages such as Python