1:30 YouTube video

Francesco Savarese studied on the MSc in Mathematical Trading and Finance at Bayes Business School. In this video he explains how Bayes is for the ambitious and helped him to achieve his career goal to become a trader.


Who is it for?

Would you like to develop innovative and effective trading strategies in the financial market with the help of advanced mathematical and statistical tools? Join the Mathematical Trading and Finance master’s to understand how to use your excellent applied mathematical skills in the world of finance.

In the MSc Mathematical Trading and Finance, you will focus on the tools used to develop algorithms for optimal investment decisions across various asset classes, and to monitor and assess trading risk in your books.

Consequently, emphasis is given to quantitative structuring and trading, and Machine Learning techniques. You will also acquire a sound knowledge of risk management, key financial securities such as equities, fixed income products and derivatives, asset pricing, and stochastic modelling. Finally, you will master advance programming skills in Python and Matlab.

Adriano Rosa I chose the MSc in Mathematical Trading and Finance at Bayes to merge my passion for the financial market with my interest to develop and strengthen my quantitative skills. Bayes helped me to build the foundations to get my first role, gaining an advantage when it came to quantitative and programming skills. This is especially true in the Fixed Income market, where quantitative skills are necessary to succeed.

Adriano Rosa


In our postgraduate programme in Mathematical Trading and Finance, you’ll explore how financial innovation and globalisation have created new investment opportunities. Develop the quantitative skills and mathematical techniques used in financial markets, and learn how to develop algorithms for optimal investment decisions across various asset classes.

Core modules in quantitative trading and structuring differentiate this course from other quantitative finance courses. You’ll also focus on the theory of finance and different financial assets, exploring how these assets are priced and used for asset management or risk management purposes. You’ll build the mathematical and statistical skills needed in quantitative finance, including some stochastics. You’ll learn Python, and can choose to learn other programming languages, such as Matlab and VBA, as electives.

Term three offers you flexibility within your master’s: complete your postgraduate degree entirely by choosing electives, or undertake a business research or applied research project.

The difference between the MSc Mathematical Trading and Finance to the other two quants courses (MSc Financial Mathematics and MSc Quantitative Finance) are core modules which focus on quantitative trading and structuring.

Have a question about student experience at Bayes?

Talk one-on-one with a student who is currently studying at Bayes.

Ask a student


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


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 Mathematical Trading and Finance degree 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 2023/24

  • Induction: 11th September 2023 - 22nd September 2023
  • Term one: 25th September 2023 - 8th December 2023
  • Term one exams: 8th January 2024 - 19th January 2024
  • Term two: 22nd January 2024 - 5th April 2024
  • Term two exams: 22nd April 2024 - 3rd May 2024
  • Term three - international electives: 6th May 2024 - 17th May 2024
  • Term three: 20th May 2024 - 5th July 2024
  • Term three exams: 8th July 2024 - 19th July 2024
  • Resits: 12th August 2024 - 23rd August 2024
  • Additional resit week - tests only: 26th August 2024 - 30th August 2024.


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 (add timetable and search for your programme)

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 Mathematical Trading & Finance 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 Mathematical Trading & Finance.

Module Leaders include:


How to apply

Apply for MSc Mathematical Trading and Finance

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 500-600 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 award documents must be verified, and should be provided to the relevant Admissions Officer via one of the methods stated in your offer.

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.

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, in a highly quantitative programme such as computer science, finance, economics, engineering, statistics, or mathematics and physics.
  • Applicants should have sound knowledge of 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 an English language test.

If you have studied in the UK at degree level for less than three years (e.g. 3+1, 2+1, 2+2, etc.) you will be required to provide the results of an approved English language test and possibly resit the test to meet our academic entry requirements.

Full list of approved English language tests/qualifications and minimum requirements.


UK/EU/International £30,000 Tuition fees are subject to annual change

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

Our MSc in Mathematical Trading and Finance prepares you for success in the UK and around the world, in finance and related areas, within large investment banks, small specialist financial companies or boutique firms.

Your career path may take you into work as a quantitative, research or equity analyst, in risk management, on fixed income security desks, in the asset management industry including hedge funds, or into investment banking. You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.

You’ll get support on identifying and achieving your goals from our careers team throughout your course, and benefit from our industry links and alumni network.

Hear from our Mathematical Trading and Finance alumni

Class profile

Recent graduate of the MSc in Mathematical Trading and Finance programme have secured positions in companies including:

  • Analyst - Global Markets - BNP Paribas
  • Financial Structuring - Dealing Room - National Bank of Greece
  • FICC electronic trading sales - Global Markets - Credit Agricole
  • Analyst - AIM Trade Desk - Bloomberg
  • Intern - Equity Digital Market - J.P. Morgan

Previous graduates have gone on to work in financial services, insurance, investment banking and assetmanagement, across Asia, the UK and EU.

(Data provided from alumni who completed the annual destination data survey for 2020/21 and 2019/20).

Course information and statistics (2022/23 cohort)

average age of student body
less than 1
year average work experience
Human brain
in the third term to tailor your degree
Human brain
course established with support of Corporation of London