Who is it for?
Would you like to forecast the future of the financial market? Choose the MSc in Quantitative Finance if you’re fascinated by the inner workings of finance, even if you don’t have a background in finance.
You’ll need a good understanding of mathematics and statistics, including the more quantitative and mathematical techniques used in financial markets. So you’re likely to hold the equivalent of a UK upper second class degree in finance, economics, engineering, maths, physics, or computer science. You’re looking for a course that will prepare you for a successful career in the finance, with theoretical and applied learning, and introductions to industry contacts and alumni working in the industry.
The Quantitative Finance programme at Bayes Business School offered an equal blend of the theoretical and the practical part, which was the right balance for me to fuel my knowledge. The MSc has provided me with a critical understanding of the world of Quantitative Finance and aided me to develop my technical and soft skills, such as identifying, forecasting and managing risk and discovering the importance and the thought-provoking nature of the financial industry.
In the master’s in Quantitative Finance, you’ll explore the quantitative aspects of finance from a practical and mathematical point of view, and learn to use financial econometrics forecasting models to make informed decisions on future investments.
Study core modules in risk management, asset pricing and introductions to key financial securities such as equities, fixed income securities and derivatives. Learn essential programming languages, Python and Matlab, in the first two terms, with a third term opportunity to learn other programming languages, such as VBA or C. Then progress to more specialist learning, covering basic and advanced topics in econometrics, stochastic modelling and numerical methods.
In term three you have flexibility to adapt your master’s to your career goals with the choice of undertaking a research project or focusing on electives.
What will you learn
- Acquire real-world skills on a practical course where you learn and apply many different techniques.
- Tailor your third term to your ambitions, choosing from a business research or applied research project or only elective modules.
- Learn from experts who have extensive experience in the financial sector and bring this knowledge to the classroom.
- Study in the heart of London’s financial district, and use our close links with nearby leading financial consultancies, investment banks and boutique financial firms to build your networks.
- Develop a critical understanding of the world of quantitative finance and the technical and soft skills necessary for career success.
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.
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
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
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
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 one with some applications to finance being introduced in term two.
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.
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.
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.
Econometrics of Financial Markets
Econometrics is an essential tool for the empirical analyses of financial markets as well as the development of quantitative strategies for forecasting, pricing and risk management analyses in financial markets.
A good understanding of the developments in financial econometrics is of great relevance to the analysis of financial markets, building both technical skills and the ability to carry out advanced empirical research.
Numerical Methods - Applications
This module introduces basic concepts used in numerical methods as well as graphical techniques often used to visualise relevant data.
The module also aims to introduce the concepts used in derviatives pricing and present Monte Carlo simulation methods in finance.
Additionally, this module aims to transmit an appreciation of performance criteria, their formulation and application in this area.
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.
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
- Applied Machine Learning
- 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
- VBA with Application for Finance.
- FinTech (taught in Italy)
- Investment Strategy (taught in New York, USA).
*Please note that electives are subject to change and availability.
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 Quantitative Finance programme, 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 Quantitative 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 Quantitative Finance.
Module Leaders include:
How to apply
We only accept online applications.
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.
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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.
- 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 for 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.
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)
With your MSc in Quantitative Finance you’re ready for a career in the finance industry, or to pursue an academic path with a PhD. Recent graduates are employed by large investment banks, financial consultancies, boutique financial firms or specialist firms. They work in hedge fund management, asset management, risk management and technical analysis, on fixed income security desks and as actuarial consultants.
Our careers team will support you in as you decide on your career path, and help you to benefit from our excellent connections with major players in the finance industry.
Hear from our Quantitative Finance Alumni.
Recent companies graduates from the MSc in Quantative Finance degree secured positions in companies including:
- ESG Associate
- Graduate - Modelling Department
- Financial Analyst - Strategy & Investments - Grant Thornton
- Model Risk Manager - Revolut
- Fixed Income Analyst - Index & Smart Beta - Legal & General Investment Management
- Actuarial Consultant - Risk - 4most Europe.
Previous graduates have gone on to work in financial services in asset management, investment banking and insurance and across the UK, EU and Asia.
(Data provided from alumni who completed the annual destination data survey for 2020/21 and 2019/20).