Overview
Who is it for?
To successfully complete the Financial Mathematics postgraduate course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate.
Or you might have a bachelor’s degree in economics or science and in particular computer science, which, coupled with your interest in stochastics, could also qualify you for this programme.
You should have a general interest in learning the more technical and mathematical techniques used in financial markets; but you don’t need to have a background in finance.
Objectives
The master's in Financial Mathematics focuses on stochastics and simulation techniques, but also covers some econometrics. You’ll study core modules covering asset pricing, risk management and an introduction to key financial securities such as equities, fixed income and derivatives.
You’ll cover a wide range of elementary and advanced topics in stochastics, including Levy processes and different simulation techniques.
You’ll be taught Python during terms 1 and 2 and you have the opportunity to learn other programming languages as part of our electives offering, such as Matlab or VBA.
There are three ways to complete the third term. Either you’ll choose five electives from around 40 optional modules in your final term. Or you can choose to complete a traditional dissertation, known as a ‘business research project’, which counts for four electives, or a shorter ‘applied research project’, which is the equivalent of two elective modules.
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Structure
What will you learn
- You will have gained 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 good understanding of stochastic and mathematical finance and gained some knowledge of econometrics and forecasting. You will also have obtained a good understanding of programming, in particular 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 Monte Carlo Simulations; Tree-based pricing methods; Fourier inversion based methods; Applications in Risk Management.
This module integrates the programming language Matlab and is partly lab based.
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 planned to run in 2020
- Advanced Financial Engineering and Credit Derivatives
- Credit Risk Management
- An Introduction to Machine Learning
- Introduction to Copula Modelling
- Introduction to Python
- Operational Risk Management
- Trading and Hedging in the Forex Market
- Trading and Market Microstructure
- Ethics, Society and the Finance Sector
International elective
- Introduction to FinTech (taught in Italy)
See the MSc in Financial Mathematics programme specification.
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 2021/22
- Induction: 20th September 2021 - 1st October 2021
- Term one: 4th October 2021 - 17th December
- Term one exams: 10th January 2022 - 21st January 2022
- Term two: 24th January 2022 - 8th April 2022
- Term two exams: 25th April 2022 - 6th May 2022
- Term three - international: 9th May 2022 - 20th May 2022
- Term three: 23rd May 2022 - 8th July 2022
- Term three assessments: 11th July 2022 - 22nd July 2022
- Resits: 15th August 2022 - 26th August 2022
- Additional resit week – tests only: 29th August 2022 - 2nd September 2022
- Research Project Submissions: Thursday 1st September 2022
Note: term one resit tests for the Energy / Shipping Trade and Finance degrees will normally take place in the week immediately prior to the August resit period.
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.
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
Applications for 2021 are now closed.
Applications for 2022 entry will open in November 2021.
Documents required for decision-making
- Transcript/interim transcript
- 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 documents must be verified, so an original or certified copy of the degree transcript must be uploaded to the application form or e-mailed to the relevant Admissions Officer upon request
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
Unfortunately, as a result of the evolving situation regarding the coronavirus (COVID-19) pandemic, we can only offer online appointments to discuss your application. To book one, please get in touch with the relevant Admission Officer
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.
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 the test.
If you have studied a 2+2 degree with just two years in the UK you will be required to provide IELTS results and possibly to resit the tests to meet our requirements.
IELTS
- The required IELTS level is an average of 7.0 with a minimum of 6.5 in the writing section and no less than 6.0 in any other section.
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
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.
Our graduates are well qualified for successful careers within large investment banks, small specialist financial companies or boutique firms.
Our dedicated Careers Team will help you identify your ideal career path and work with you to maximise the potential of accomplishing your professional goals.
Class of 2019 Profile
Recent graduates have taken up positions in:
- Associate Financial Engineer, Intercontinantal Exchange Group
- Structured Equity Derivatives Off, Credit Suisse
- Junior Quant, Behaviour Lab
- Executive, deVere Group
- Equity Fundamentals Analyst, Bloomberg
- Associate, PwC
Where they are working now
- UK - 67%
- Europe other - 8%
- Asia -17%
Industry post-master's
Alumni stories
Hear from our alumni. Discover the real experiences of learning at Bayes and how Bayes helped to boost our graduates' careers.
Read Leon’s story