Mathematical Trading and Finance

Program Overview

---

Mathematical Trading and Finance MSc

Key information

• Duration: 12 months
• Attendance mode: Full-time
• Location: Bunhill Row, Central London
• Start of programme: September 2025
• Application deadline: Rolling applications
• Entry year: Showing course information for 2025

Overview

This course is designed for numerate graduates with strong quantitative foundations—typically from backgrounds in STEM subjects such as Finance, Engineering, Statistics, Physics, or Computer Science.

It’s ideally suited for individuals who aspire to secure roles in trading, structuring, or risk management at leading investment banks, hedge funds, or proprietary trading firms. If your goal is to move into a high-impact, analytically driven position in financial markets, this course will give you the skills and insights to stand out.

You’ll gain a deep understanding of how advanced mathematics, stochastic processes, and machine learning can be applied to real-world trading challenges—bridging the gap between academic theory and market practice.

In addition, you'll develop hands-on coding proficiency in key programming languages used across the industry, including Python, Matlab, and C/C++. These are essential tools for building financial models, designing trading algorithms, and executing data-driven strategies in fast-paced environments.

Our rankings

• 72% international cohort (last enrolled cohort)
• 3rd best in London, 44th in Europe (Financial Times European Business School Ranking 2024)
• 1st in London for Career progress (Financial Times Master’s in Finance ranking 2024)

Accreditation

Bayes Quants finance master's degrees are part of the network of academic partners of The Certificate in Quantitative Finance Institute.

Why choose this course?

• Networking opportunities with international experts
• Bayes Financial Engineering Workshops have recently hosted speakers from: Morgan Stanley, Deutsche Bank, UBS, US Federal Reserve Bank, ICE, and many more
• Tailor your course to suit you, switch degree pathway in your second term
• You can choose MSc Quantitative Finance or MSc Financial Mathematics if they suit you more.

Course objectives

In our postgraduate programme in Mathematical Trading and Finance, you will explore how financial innovation and globalisation have created new investment opportunities. You will also 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.

Compulsory modules in quantitative trading and structuring and machine learning 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.

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

Teaching staff

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.

Course director:

• Professor Laura Ballotta

Module Leaders include:

• Dr Dirk Nitzsche
• Dr Bernd Hanke
• Dr Rui Zhu
• Professor Keith Cuthbertson
• Professor Gianluca Fusai
• Professor Giovanni Urga.

Course content

Pre-Study and Induction weeks

Before your program begins, you'll be required to complete a series of online pre-study modules, designed to set you up for success. These include Fundamentals of Python, Mathematics, Probability and Statistics.

Please note that while these modules are essential for your preparation, they do not contribute to your final award calculation.

In addition to these modules, 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.

This comprehensive preparation will ensure you start your program with confidence. You'll be well equipped to tackle the academic challenges ahead and fully leverage all the opportunities your program has to offer.

Course structure

• The three quantitative finance degrees at Bayes share the first term course content. This gives you the opportunity to dip into the quantitative content, learn what you are interested in pursuing and then you can swap to Financial Mathematics or Quantitative Finance in your second term if those suit you.

Term 1

• Asset Pricing
• Derivatives
• Foundations of Econometrics
• Stochastic Modelling Methods in Finance

Term 2

• Fixed Income
• Risk Analysis
• Quantitative Trading
• Machine Learning

Term 3

You will be able to tailor your degree in the third term by choosing electives to complete your education.

You may choose from the following options in your final term:

• Option 1: Electives
• Option 2: General Research Project

Assessment methods

• Course work
• Examinations
• Presentation
• Groupwork
• Problem sets

Term dates

Term dates 2025/26

• Induction: 15th September 2025 - 26th September 2025
• Term one: 29th September 2025 - 12th December 2025
• Term one exams: 5th January 2026 - 16th January 2026
• Term two: 19th January 2026 - 3rd April 2026
• Term two exams: 20th April 2026 - 1st May 2026
• Term three - international electives: 4th May 2026 - 15th May 2026
• Term three: 18th May 2026 - 3rd July 2026
• Term three exams: 6th July 2026 - 17th July 2026
• Resits: 10th August 2026 - 21st August 2026
• Additional resit week - tests only: 24th August 2026 - 28th August 2026.

Careers

Our graduates go on to pursue a wide range of careers in derivatives trading and risk management with many of the world’s leading financial institutions. Recent employers include Bank of China, Commerzbank AG, Dare and Societe Generale.

Recent graduates have secured positions such as:

• Data Scientist
• Market Analyst
• Quantitative Analyst
• Energy Trader
• Risk Analyst
• Financial Engineer
• ALM Risk Manager.

Fees & funding

International fee

• September 2025 entry: £33,100

UK/Home fee

• September 2025 entry: £26,500

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
• Work experience is not a requirement of this course.

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.

Apply

Please see our Application Guide for details of the documents you will need to supply as part of your application, and other useful information.

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

Frequently asked questions

Apply for September 2025 entry

We only accept online applications.

Apply - MSc Mathematical Trade and Finance

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 and will be on campus.

Terms and conditions

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

Student life

We are located right in the heart of London. Being a City St George's student allows you to take advantage of all that London has to offer.

London is continually ranked first as 'Best Student City' in the world to study in (QS, 2025).

• Living in London
• Student support
• Accommodation

Have a question about student experience at Bayes?

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

Ask a student

Contact us

Speak to one of our staff from Master's programmes teams.

• Book an MSc Consultation
• Enquiries form
• Events

Related courses

• Financial Mathematics
• Financial Technology and Innovation
• Quantitative Finance