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Mathematics and Finance
Broaden your knowledge of mathematics and quantitative finance for a career in the financial services sector.
Develop skills for a career in the finance and beyond
Become familiar with latest industry practice, trends and research
Enhance your financial expertise on a project carried out with departmental experts or on an external industry placement
Course key facts
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Qualification
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MSc
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Duration
1 year, 2 years
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Start date
September 2024
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Study mode
Full-time, Part-time
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Fees
Full-time: £41,750
Part-time: £20,875 HomeFull-time: £41,750
Part-time: £20,875 Overseas
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Delivered by
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Location
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South Kensington
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Minimum entry standard
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2:1 in mathematics, applied mathematics, statistics or physics
Course overview
Prepare for a wide range of careers in quantitative finance on this varied Master's course.
This course will deepen your understanding of major aspects of mathematical finance. You'll explore latest industry practice and research, with regular insights from leading practitioners.
The varied programme covers key mathematical foundations, finance principles and tools, and implementation and data analysis.
You'll receive training in a range of mathematical, statistical and programming tools required to pursue or advance a career within financial services.
You'll also apply your knowledge from the course on a research project. This will be carried out internally or on a placement with a bank, hedge fund or similar financial institution.
Structure
This page is updated regularly to reflect the latest version of the curriculum. However, this information is subject to change.
Find out more about potential course changes.
Please note: it may not always be possible to take specific combinations of modules due to timetabling conflicts. For confirmation, please check with the relevant department.
You’ll take all of these core modules.
Core modules
Become familiar with option pricing theory and its mathematical and conceptual underpinnings
Understand the new regulations imposed on banks to require more statistical knowledge and assess the current needs of the financial sector.
Explore probability theory, measure theory and the basic tools from stochastic analysis that provide the mathematical foundations for option pricing theory.
Learn why proper risk management is of utmost importance for the solvency of financial institutions and stability of the entire financial system.
Understand the theory and practice of term structure of interest rates in relation to credit risk, funding liquidity costs, collateral modelling and multiple curves.
Become familiar with programming in C++ and in Python for quantitative finance problems.
Evaluate derivatives used in today’s financial markets and examine simulation methods used in finance and probabilistic numerical methods for PDEs.
You’ll choose five optional modules.
Optional modules
Receive a detailed overview of models/techniques used in the algorithmic trading space, with an emphasis on both theoretical aspects and practical applications.
Learn the structure and components of multi-layer neural nets and develop deep neural networks to solve computational and statistical problems in finance.
Overview the evolution of data science in the context of Fintech, RegTech and Suptech, and apply new analytical techniques to real world challenges.
Discover how quantum computing technology and algorithms can be used to solve financial problems, including portfolio optimisation and data generation.
Explore the main numerical tools required to work in a quantitative field, including the mathematical techniques underlying Finite difference schemes, Fourier transforms, and quadrature and linear programming.
Develop your understanding of data analysis and ‘machine learning’ techniques, illustrated by applications in finance.
Advance your knowledge of derivatives pricing and asset allocation and build familiarity with the stochastic volatility model and jump diffusion model.
Discover how to solve several classes of convex optimisation problems, including linear, quadratic, stochastic, conic, and robust programming.
Master core stochastic analysis skills and develop a rigorous understanding of the key definitions and theorems in Malliavin calculus.
Understand the basic properties of rough path analysis and the signature of a path and its key analytic and algebraic properties.
Develop a thorough understanding of how trades occur in financial markets and learn how to measure liquidity and recognise the recent increase in liquidity fragmentation and hidden, “dark” liquidity.
Apply the main concepts and techniques from dynamics stochastic optimisation and stochastic control theory to the realm of quantitative finance.
Apply probabilistic, variational and dynamic programming methods to solve problems that arise from algorithmic and high frequency trading.
Complement your existing financial knowledge by building an appreciation of the specificities of foreign exchange and fixed income markets.
Understand the principles of quantitative portfolio management and apply and implement widely-used approaches such as factor models and momentum strategies.
Between May and September, you'll complete an external placement with a finance-related company.
You'll develop a deeper understanding of some advanced mathematical methods to solve problems of practical importance in the financial industry.
Teaching and assessment
Balance of teaching and learning
Key
- Lectures, tutorials and practicals
- Research project
- 84% Lectures, tutorials and practicals
- 16% Research project
Teaching and learning methods
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Independent research project
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Lectures
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Office hours
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Problem classes / problem sheets
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Tutorials
Assessment methods
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Coursework
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Dissertation
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Written examinations
Entry requirements
We consider all applicants on an individual basis, welcoming students from all over the world.
How to apply
Applications are now closed for 2024 entry.
You may be invited to attend an interview with our staff as part of your application.
Details of this will be sent to you following your application.
There is no application fee for MRes courses, Postgraduate Certificates, Postgraduate Diplomas, or courses such as PhDs and EngDs.
If you are applying for a taught Master’s course, you will need to pay an application fee before submitting your application.
The fee applies per application and not per course.
- £80 for all taught Master's applications, excluding those to the Imperial College Business School.
- £100 for all MSc applications to the Imperial College Business School.
- £150 for all MBA applications to the Imperial College Business School.
If you are facing financial hardship and are unable to pay the application fee, we encourage you to apply for our application fee waiver.
Find out more about how to apply for a Master's course, including references and personal statements.
An ATAS certificate is not required for students applying for this course.
Tuition fees
Home fee
Full-time
£41,750
Part-time
£20,875per year
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
For courses starting on or after 1 August 2024, the maximum amount is £12,471. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
Overseas fee
Full-time
£41,750
Part-time
£20,875per year
You should expect and budget for your fees to increase each year.
Your fee is based on the year you enter the university, not your year of study. This means that if you repeat a year or resume your studies after an interruption, your fees will only increase by the amount linked to inflation.
Find out more about our tuition fees payment terms, including how inflationary increases are applied to your tuition fees in subsequent years of study.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a UK national, or EU national with settled or pre-settled status under the EU Settlement Scheme, you may be able to apply for a Postgraduate Master’s Loan from the UK government, if you meet certain criteria.
For courses starting on or after 1 August 2024, the maximum amount is £12,471. The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
The loan is not means-tested and you can choose whether to put it towards your tuition fees or living costs.
How will studying at Imperial help my career?
Acquire a number of highly transferable skills, including active research, data analysis and problem-solving skills.
Graduates are highly sought after in a range of fields, including quantitative finance, trading and risk management.
With specialised knowledge, you'll be highly sought after in a range of careers.
These include Financial Analysts, Quantitative Analysts and Risk Management Analysts.
Further links
Contact the department
- Email: mathfin@imperial.ac.uk
Course Directors: Dr Jack Jacquier and Dr Eyal Neuman
Visit the Department of Mathematics website.
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Terms and conditions
There are some important pieces of information you should be aware of when applying to Imperial. These include key information about your tuition fees, funding, visas, accommodation and more.
You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.
Programme specifications