Overview
Who is it for?
Interested in tackling changes in the financial market in a mathematically sound manner? This master’s programme is for you if you have a flair for mathematics and are aiming for a successful career in the finance industry.
You don’t need a background in finance, but you do need a very good understanding of mathematics. So you’ve already got an upper second class degree, or equivalent, in physics, computer science, engineering, economics or mathematics.
You’re interested in stochastic modelling, and have a general interest in learning the more technical and mathematical techniques used in financial markets.
You’re ready to develop the skills and knowledge to undertake financial research, within a financial firm or academic institution. And you’re keen to learn from and connect with the top finance and business leaders who are guest lecturers on this course.
I would advise all prospective students considering MSc Financial Mathematics at Bayes Business School to give the opportunity to themself to attend to this business school. It is not only the knowledge and the support that this business school offers but it is also a life experience.The engagement with students from other universities around the world helped me to understand how to work in a team and express your opinion for real life problems of Finance and use Mathematics in order to solve them.
- Christiana Theocharous
Objectives
In our post-graduate master's in Financial Mathematics programme you’ll acquire the skills you need to design, implement and change pricing models and analytical tools for risk management, or push new quantitative modelling ideas across different asset classes.
You’ll focus on stochastic modelling and simulation techniques and explore econometrics, asset pricing, risk management and key financial securities such as equities, fixed income products and derivatives.
You’ll build vital programming skills in Python and Matlab during terms 1 and 2, and have the opportunity to learn other programming languages such as VBA or C as third term electives.
Choose from three ways to complete your degree in the third term, including a business research project or applied research project, or solely through electives.
Have a question about student experience at Bayes?
Talk one-on-one with a student who is currently studying at Bayes.
Ask a student
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.
Term 1
Core modules:
Asset Pricing
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
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.
Derivatives
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
To introduce derivatives and derivative models in the context of financial risk management. To complement general finance courses with specific instruction in the key derivatives area.
To enable you to use models in this area in practical applications. To transmit to you the fundamental mathematical modelling techniques underpinning the subject.
Foundations of Econometrics
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
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 you 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.
Stochastic Modelling Methods in Finance
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
The module provides the necessary mathematical tools on which the entire programme is based.
- To introduce you to Brownian motion and stochastic calculus
- To provide examples of applications of stochastic calculus in financial areas
- To provide the tools required for a rigorous understanding of financial modelling and pricing techniques
- To learn fundamental numerical methods for simulating trajectories of commonly used stochastic processes.
Applied Research Tools
- 10 credits
- 8 x 3 hour lectures over the ten week term
- 52 hours per week self directed study
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.
Term 2
Core modules:
Fixed Income
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
To provide a foundation in a crucial area of financial markets and quantitative finance. To complement the general derivatives course with specific instruction in a key derivatives area.
To acquaint you with the main modelling streams in fixed income securities. To enable you to use models in this area in practical applications. To transmit to you the fundamental mathematical modelling techniques underpinning the subject.
Risk Analysis
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
Financial disasters 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.
Advanced Stochastic Modelling
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
The module introduces more recent developments in the field of financial mathematics to:
- Introduce you to more recent advances in mathematical finance
- Provide you with the mathematical tools required for the setting up of more sophisticated financial models and valuation framework
- Introduce you to pricing frameworks that go beyond the Black-Scholes model and the necessary numerical methods.
Simulations Techniques and Financial Modelling
- 15 credits
- 3 hours per week in lectures
- 12 hours per week self directed study
This module focuses on applications of numerical methods and programming languages to finance. Students will learn how to generate scenarios using popular financial models, like the Black-Scholes model, the Heston model, the Variance Gamma model and more. Students will also gain a sound knowledge of Fourier-based methods, simulation methods such as Monte Carlo and empirical bootstrap, in addition to covering a primer in Artificial Neural Networks. Focus is placed on applications in option pricing, risk management and portfolio performance evaluation.
Term 3
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)
Projects
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.
Typical projects can involve any of the following: extracting data from electronic databases or by hand; statistical analysis of large or small populations; interviews; case studies of an industry or a sector or of a business / finance issue in a particular country setting.
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
- Modelling and Data Analysis
- Credit Risk Management
- Intro to Python
- Trading and Hedging in the Forex Market
- Trading and Market Microstructure
- VBA with Applications to Finance
- Topics in Quantitative Risk Management.
International electives
- FinTech (taught in Italy)
- Investment Strategy (taught in New York, USA).
*Please note that electives are subject to change and availability.
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 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.
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 (add timetable and search for your programme)
Please note that all academic timetables are subject to change.
Teaching staff
Course Director

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
Apply for MSc Financial Mathematics
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 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.
Ask a student
Chat to one of our current master's students now about applying for a MSc at Bayes.
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 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
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)
Career pathways
Career destinations for MSc Financial Mathematics
The MSc in Financial Mathematics equips you for a variety of careers in finance and related areas, in the UK and around the world. Graduates go on to successful careers in quant roles, traditional finance roles and data science & analytics roles or work involving developing pricing models for large financial firms.
You’ll be well qualified for a role within large investment banks, small specialist financial companies or boutique firms. The MSc in Financial Mathematics also prepares you for a PhD in the areas of Mathematical Finance and Financial Engineering.
Our careers team will support you in understanding and fulfilling your career goals, and you’ll also benefit from our strong links to major players in the finance industry.
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.
Class Profile
Recent graduates have taken up positions in:
- Analyst - Sales and Trading - J.P. Morgan
- Analyst - Equity capital markets - Citi Bank
- Analyst - Equity capital markets - Birch Faraday Capital
- Quantitative Analyst - Validus Risk Management
- ETF/ETP Data Analyst - ETFGI
Previous graduates have gone on to work in financial services, consulting, asset management and corporate banking across the UK, Asia and the EU.
(Data provided from alumni who completed the annual destination data survey for 2020/21 and 2019/20).