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.
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.
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.
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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 module focuses on the introduction of pricing financial securities, which forms the basis for understanding asset pricing behaviour and the cornerstone of many asset pricing models. The focus is on spot securities, mainly equities and debt instruments.
The module also introduces students to the fundamental theory used by practitioners and academics in the wider field of finance, in particular asset management. That includes portfolio theory, the CAPM, factor models and measuring risk and return.
Those concepts are widely used by financial market participants. At the end of this module the various building blocks are being put together in the discussion of performance and persistence of performance of mutual funds.
Module Leader in 2022-23: Dr Dirk Nitzsche
This module introduces to derivatives instruments and derivatives markets in the context of financial risk management. Focus is specifically given to the identification of the risks inherent in derivative securities.
On completion of this module, students will be able to undertake quantitative applications of concepts in a practical setting and understand the contribution of derivative securities to a sensible risk management practice.
Module Leader in 2022-23: Prof. Keith Cuthbertson
Foundations of Econometrics
The course provides the essential statistical and econometric techniques needed to conduct quantitative research in finance and economics.
This combination of econometric theory and application will enable students to understand and interpret empirical findings in a range of financial markets, including reading of empirical academic literature and critical assessment econometric applications undertaken by industry practitioners.
Module Leader in 2022-23: Prof. Giovanni Urga
Stochastic Modelling Methods in Finance
The module provides the necessary mathematical tools on which the entire programme is based. Specifically, the module offers a rigorous introduction to Brownian motions and stochastic calculus.
Furthermore, the module focuses on the construction of the mathematical framework on which Mathematical Finance is based, starting from the no-arbitrage principle, all the way to its mathematical formulation using martingales and martingale measures.
These concepts will then be applied in Finance for pricing and hedging books of derivative contracts.
Module Leader in 2022-23: Prof. Laura Ballotta
Applied Research Tools
Strong research skills are a key element of development strategy for companies and institutions large and small. In particular the ability to programme and to automate procedures. This module focuses on Python as a programming language and students will learn the basics in term 1 with some applications to finance being introduced in term 2.
The module introduces the main programming skills which are helpful in the financial industry. Operating on matrices, loops, conditional statements, subroutine/functions/procedures and optimisations are core skills which are being introduced in this module.
The module provides a thorough introduction to the market of fixed income securities, such as bonds, swaps and interest rate options.
Futrthermore, the module covers the main modelling streams in fixed income securities. It also offers insights in the most recent issues that affected the fixed income market, such as multicurve rates, negative rates and counterparty credit risk.
Module Leader in 2022-23: Prof. Gianluca Fusai
Financial debacles are a constant reminder of the relationship between financial risk and reward. The quantitative approach to this relationship is ever more dominant in the market and subject to constant innovation.
As market participants need to keep abreast of new developments, the Risk Analysis module provides a good path of study in this field.
The aim of this module is to help you develop a solid background for evaluating, managing, and researching financial risk. To this end you will learn to analyse and quantify risk according to current best practice in the markets.
Module Leader in 2022-23: Prof. Gianluca Fusai
This trading focused module introduces students to the world of computer-based trading and dealing with high frequency data.
Some relevant market microstructure concepts, such as bid-ask spreads, liquidity and other concepts are being introduced before the focus moves to high frequency trading strategies and other automated trading concepts.
Module Leader in 2022-23: Dr Bernd Hanke
This module provides on overview of machine learning concepts, techniques and algorithms used in practice to describe and analyse complex data and design predictive analytics methods. You should expect to engage with the main idea and intuition behind modern machine learning tools from a practical perspective.
Standard computing skills in R, Python and Matlab will be used to put in practice the theory discussed during the lectures.
Module Leader in 2022-23: Dr Rui Zhu
You will be able to tailor your degree in the third term by choosing to complete your education with either a business research project or an applied research project, or solely through electives.
You may choose from the three options in your final term.
- Option 1: Students can take five specialist elective modules (5 x 10 credits).
- Option 2: Students can opt to write a 10,000-word Business Research Project (40 credits) and take one specialist elective module (1 x 10 credits).
- Option 3: Students can opt to write a 3,000-5,000-word Applied Research Project (20 credits) and take three specialist elective modules (3 x 10 credits)
Business Research Project
It is important for aspiring professionals to demonstrate, on an individual basis, their ability to apply concepts and techniques they have learned in an in-depth study of a topic of their choice and to organise their findings in a report, all conducted within a given time limit.
To train you to undertake individual research and provide you with an opportunity to specialise in a contemporary business or finance topic related to your future career aspirations.
You are required to submit a project of approximately 10,000 words on any subject area covered in the rest of the programme.
Topics covered in recent years are construction of optimised equity and crypto portfolios, impact of social media sentiment on portfolio allocation, and quantification of the performance of global minimum variance portfolios.
Applied Research Project
The aim of this module is to enable you to demonstrate how to integrate your learning in core and elective modules and then apply this to the formulation and completion of an applied research project.
You will be required to demonstrate the skills and knowledge that you have acquired throughout your MSc study.
You will undertake a short piece of applied research on a question of academic and/or practical relevance. Guidelines will be provided in order to help you identify the research question.
Based on your chosen topic, you must write a report of around 3,000–5,000 words that summarises and critically evaluates your method and your findings.
Electives offered in 2022
- Emerging Global Risks
- Advanced Financial Modelling and Forecasting
- Behavioural Finance
- Ethics, Society and the Finance Sector
- Financial Crime
- Hedge Funds
- Technical Analysis and Trading Systems
- Trading and Hedging in the Forex Market
- Trading and Market Microstructure
- VBA with Application for Finance.
- FinTech (taught in Italy)
*Please note that electives are subject to change and availability.
See the MSc in Mathematical Trading and Finance programme specification.
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)
- 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 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.
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
- 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.
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.
- 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.
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.
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)
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
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).