The MSc in Computational Finance will introduce students to the computational methods that are widely used by practitioners and financial institutions in today's markets. This will provide students with a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics, and agent-based modelling. These techniques will be used to understand financial markets from a post-crisis perspective which incorporates findings from the study of financial markets at high-frequency time scales, modern approaches to understanding systematic risk and financial contagion, and disruptive technologies such as distributed-ledgers and crypto-currencies. The programme is highly practical, and students will have the opportunity to apply their learning to real-world data and case studies in hands-on laboratory sessions.
Computational Finance studies problems of optimal investment, risk management and trade execution from a computational perspective. As with any engineering discipline, computational finance analyses a given problem by first building a model for it and then examining the model. In computational finance, however, our model is typically analysed by running computer programs, rather than solving mathematical equations. In addition to standard computational methods such as Monte-Carlo option pricing, you will also learn more advanced modelling techniques such as agent-based modelling, in which the model itself takes the form of a computer program.
The programme will provide a foundation in the core skills required for successful risk management and optimal investment by giving a grounding in the key quantitative methods used in finance, including computer programming, numerical methods, scientific computing, numerical optimisation, and an overview of the financial markets. You can then go on to study more advanced topics, including the market micro-structure of modern electronic exchanges, high-frequency finance, distributed-ledger technology and agent-based modelling.
Students are expected to go in to careers such as Investment Banking, Hedge Funds and Regulatory Bodies.
The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. You will develop skills so that you are able to formulate a well posed problem from a description in financial language, carry out relevant mathematical analysis, develop and implement an appropriate numerical scheme and present and interpret these results.
The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.
You will take three introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics and MATLAB.
The first term focuses on compulsory core material, offering 80 hours of lectures and 40 hours of classes/practical. The core courses are as follows:
In the second term, three streams are offered; each stream consists of 32 hours of lectures and 16 hours of classes/practical. The Tools stream is mandatory and you will also take either the Modelling stream or the Data-driven stream.
As well as the streams, the course includes a compulsory one-week (24 hours of lectures) intensive module on quantitative risk management which is to be held in/around the week before the third term.
The third term is dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor.
The second component of the financial computing course, Financial Computing with C++ 2 (24 hours of lectures and practicals in total), is held shortly after the third term.
The examination will consist of the following elements:
MSc graduates have been recruited by prominent investment banks and hedge funds. Many past students have also progressed to PhD-level studies at leading universities in Europe and elsewhere.
This Masters degree provides you with knowledge of advanced finance concepts, whilst developing your quantitative, mathematical and research skills.
Taught by experienced academics based in both Leeds University Business School and the School of Mathematics, you’ll cover key topics including financial derivative pricing, discrete and continuous time models, risk management and portfolio optimisation, as well as statistical methods for finance.
You will be equipped with a rare combination of mathematical skills and the latest business finance knowledge, which is highly sought after in the financial sector by banks, investment and consultancy companies. It’s also excellent preparation if you’re interested in pursuing further academic research.
This course is ideal if you’ve previously studied finance, economics, mathematics, physics or computing, and are interested in applying your skills to financial markets.
As a student, you will be able to access the knowledge of our advanced specialist research units, which also have strong links with leading institutions in the US, Europe and Asia. These include the Centre for Advanced Study in Finance (CASIF), the Institute of Banking and Investment (IBI) and the Credit Management Research Centre (CMRC).
This research makes an important contribution to your learning on the MSc Financial Mathematics; you will benefit from a curriculum that is informed by the latest knowledge and critical thinking.
You will also benefit from our strong relationships with the finance, credit and accounting professions. This provides a connection to the latest practitioner and policy developments, giving you a masters degree that is relevant to the contemporary environment.
In your first semester you’ll develop a broad understanding of corporate finance and how financial theory relates to practice in business and financial markets. This will put your mathematical studies into context while you develop your skills in applied statistics and probability, optimisation methods and discrete time finance.
You’ll build on these skills in topics such as continuous time finance, risk management and computational methods. You’ll also gain specialist knowledge in topics that suit your career ambitions such as risk and insurance, actuarial science and behavioural finance.
The programme will improve your research skills and allow you to study different research methodologies, including those employed by our own leading academics. This will prepare you for your dissertation – an independent research project on a topic of your choice that you’ll submit by the end of the year.
You'll also take two optional modules.
We use a variety of teaching and learning methods to help you make the most of your studies. These will include lectures, seminars, workshops, online learning and tutorials. Independent study is also vital for this course allowing you to prepare for taught classes and sharpen your own research and critical skills.
In addition to the assessed modules and research dissertation, you benefit from professional training activities and employability workshops. Thanks to our links with major companies across the business world, you can also gain a practical understanding of key issues.
Recent activities have included CV building and interview sessions, professional risk management workshops and commercial awareness events. For example, students have developed their knowledge of financial markets through a one-week trading simulation. Read more about professional development activities for postgraduate finance students.
Assessment methods emphasise not just knowledge, but essential skills development too. They include formal exams, group projects, reports, computer simulation exercises, essays and written assignments, group and individual presentations.
This diversity enables you to develop a broad range of skills as preparation for professional life.
You have various opportunities open to you as a Financial Mathematics graduate, including: quantitative analysis, risk management, investment banking, financial consultancy, insurance, accounting and academia.
Previous graduates have gone on to secure employment with Allianz (London), AstraZeneca, Barclays, Cathay Life Insurance, CITIC Group, Commerzbank, Deloitte, First Direct, Gaz de France, HSBC, KPMG, Moody’s, PricewaterhouseCoopers, Royal Bank of Scotland, RSA and UK Government Actuary’s Department.
We help you to achieve your career ambitions by providing professional development support and training as part of the course. You benefit from the support of a professional development tutor, who will work with you to develop the important professional skills that employers value.
Read more about our careers and professional development support.
The University of Leeds Careers Centre also provides a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website