Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes: Theory and Application at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
The MRes in Stochastic Processes: Theory and Application is delivered through optional modules for the taught element followed by a large research project that contributes to the field in an explicit way, rather than merely applying existing knowledge.
The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.
The Department’s research groups include:
Algebra and Topology Group
Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.
Analysis and Nonlinear Partial Differential Equations Group
Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.
Stochastic Analysis Group
Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multi-fractal and multi-scale systems, Infinite dimensional stochastic analysis and others.
Mathematical Methods in Biology and Life Sciences Group
Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing.
The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.
As a student on the MRes Stochastic Processes programme you will study a range of topics for the taught element including:
Stochastic Calculus based on Brownian Motion
Levy processes and more general jump processes
The advanced Black-Scholes theory
Theory and numerics of parabolic differential equations
Java programming
The Stochastic Processes: Theory and Application course consists of a taught part (60 credits) and a research project (120 credits). Students will have a personal supervisor for their research project from the start of their studies.
Research projects could be of a theoretical mathematical nature, or they could be more applied, for example in financial mathematics or actuarial studies. Some of the research projects will be of an interdisciplinary character in collaboration with some of Swansea's world class engineers. For such projects it is likely that EPSRC funding would be available.
The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use. It is a popular venue for students to work independently on the regular example sheets set by their lecturers, and to discuss Mathematics together.
Our main university library, Information Services and Systems (ISS), contains a notably extensive collection of Mathematics books.
The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistical analysis, marketing and sales.
Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.
The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.
All academic staff in Mathematics are active researchers and the department has a thriving research culture.
The ICMA Centre’s financial engineering degree is highly respected by quantitative analysts and their employers. The credit crunch and subsequent events have emphasised the need to develop better pricing and better hedging models for all complex products. The practical and quantitative skills that you will develop on the programme will equip you to meet this challenge.
Our compulsory modules provide a firm grounding in probability theory, stochastic calculus, derivatives pricing, quantitative and numerical methods, structuring products, volatility analysis, and the modelling of credit, equity, foreign exchange and interest rate derivatives. We also provide a thorough training in C++ and other programming tools.
Optional modules will allow you to focus on risk analysis, portfolio management, designing trading strategies or econometric analysis. This newly structured degree aims to further enhance the strong reputation of its precursor – the MSc in Financial Engineering and Quantitative Analysis, which was established back in 1999. A good background in mathematics is required for acceptance to this programme (see entry requirements below).
October – December: Part 1 Autumn Term
January: Part 1 Exams
January-April: Part 2 Spring Term
May – June: Part 2 Exams
June – August (12 month programme only): Part 3
August/Sep (12 month programme only): Part 3 Coursework deadlines
Part 1 compulsory modules
Part 2 compulsory modules
Part 2 optional modules
Students on the 9-month (12-month) programme can select 40 (20) credits from the following modules:
Part 3 optional modules
Students on the 12-months programme should take 20 credits from the following:
Full-time: 9 months Full-time: 12 months
Students will be resident and undertake full-time study in the UK. Under both, the 9 and 12-month programmes students take compulsory and/or elective modules in Part 2.
The 12 month option involves taking an elective 20 credit module between July and August, which would also mean a 20 credit reduction in the number of taught modules taken in the spring term.
Many of our financial engineering graduates are now working as Quants in large London banks and other financial institutions. Others have pursued PhDs and have successful academic careers. Financial instruments are becoming ever more sophisticated, so graduates that understand complex modelling techniques are always in great demand. The high quantitative content of this programme opens many doors to a wide range of careers. You could structure and develop new debt or equity solutions to meet clients funding and hedging needs, or you could become a proprietary trader in exotic derivatives, or a software specialist or a quantitative analyst supporting the traders.
There are excellent opportunities on the buy-side, with hedge funds and investment institutions, as well as in investment banking and in software analytics. Opportunities in quantitative research, or with a rating agency, are among the many other attractive alternatives. Outside of mainstream banking and investment, you might also consider firms involved in commodity and energy trading, or the treasury divisions of leading multinationals and management consultancies.
ICMA Fixed Income Certificate
To obtain the requisite knowledge to pass the rigorous FIC exam, students are required to take the ICMA Centre Fixed Income Cash and Derivatives Markets module at Part 2. In order to receive the FIC certificate, students will need to register and pass the FIC exam through ICMA.
This MSc programme is run by Heriot-Watt University jointly with The University of Edinburgh. Upon graduation, you will receive a degree certificate bearing crests of both universities.
It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. You will also learn quantitative skills for developing and managing risk that are in high demand.
This programme involves two taught semesters of compulsory and optional courses, followed by a dissertation project.
The teaching is shared between Heriot-Watt University (HW) and The University of Edinburgh (UoE). The timetable is arranged so that you spend three days a week at the Heriot-Watt Riccarton Campus and two days a week at University of Edinburgh’s King’s Buildings Campus.
The dissertation project is either carried out with an industrial partner (e.g. Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group) or supervised by academics at Heriot-Watt University. The programme typically involves the following courses.
Compulsory courses:
Option courses:
Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group.
Graduates typically work in major financial institutions or continue their studies by joining PhD programmes.
This one-year interdisciplinary MSc programme delivered by the Management School and the Faculty of Science and Technology is designed to give you in-depth knowledge of the problems and issues in the financial sector, and enables you to develop advanced analytical, problem-solving and technical skills.
The programme gives you access to expertise and facilities in different but related areas, and offers a wide range of potential topics for your summer dissertation. Optional modules also allow you to develop particular specialisms.
You will acquire skills in data and financial analysis, forecasting, optimisation, and computer programming. You’ll also become proficient in various statistical and econometrics packages.
You will study a range of modules as part of your course, some examples of which are listed below.
Core
Optional
Information contained on the website with respect to modules is correct at the time of publication, but changes may be necessary, for example as a result of student feedback, Professional Statutory and Regulatory Bodies' (PSRB) requirements, staff changes, and new research.
There is considerable variety in the teaching methods used on the MSc in Quantitative Finance. These include lectures and discussion sessions, groupwork, case studies, presentations and workshops on the use of statistical packages.
The style of teaching is often highly interactive, so you will be contributing actively to class discussions and engaging in groupwork with students from many different backgrounds. As some of the modules are shared with other faculties and Management School programmes such as Money, Banking and Finance, Management Science and Finance, you will also have an opportunity to work with Masters students from many different programmes.
The Careers Team at LUMS helps you shape your career plans and supports your job-hunting process in a variety of ways, including personalised one-to-one support and interactive workshops on areas such as career strategies, writing CVs and applications, interview skills, psychometric testing, what to expect at assessment centres, and online networking strategies.
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.
The part-time MSc in Mathematical Finance aims to develop your mathematical modelling, data analysis and computational skills as applied to finance, without the need to take time out of your career to study.
Incorporating concepts from applied and pure mathematics, statistics, computing and corporate finance, the course gives you a broad intellectual perspective and covers, from fundamentals to the latest research, the most important aspects of quantitative finance currently in use in the finance industry.
The course:
It is possible to exit the course early and be awarded the Postgraduate Diploma in Mathematical Finance, should work pressures intervene before it is possible to write a dissertation.
In order to complete the MSc each student must attend and be assessed on four core modules, three advanced modules and to submit a dissertation. Students are expected to take seven terms (28 months) to complete the course.
Modules are taught through a series of lectures, practical sessions, guided reading, guest lectures and course assignments.
The core modules cover the mathematical foundations of probability, statistics and partial differential equations, stochastic calculus and martingale theory, portfolio theory, the Black-Scholes model and extensions, numerical methods (finite differences and Monte Carlo), interest rate modelling, stochastic optimisation, exotic derivatives and stochastic volatility. MATLAB and Python are used as a practical computing languages.
Attendance at the four core modules is compulsory. For each module there is an assignment for which feedback and an indicative mark is given to assist you in improving your future performance. Assessment for these compulsory modules consists of two two-hour written examinations held in September of the first year.
Each of the advanced modules explores a key area in contemporary mathematical finance. The programme of advanced modules is published in July each year, and you will be asked to register your choice of three modules. Attendance at these three assessed modules is compulsory. Advanced modules will be assessed by short ‘special project’ reports, each submitted on a subject chosen by you that is covered in the module.
You will complete a dissertation on a topic chosen in consultation with your supervisor and the Course Director.
The School of Mathematics and Alliance Manchester Business School at the University of Manchester have combined their academic strength and practical expertise to deliver the MSc in Mathematical Finance (UK 1 year), ensuring that students can experience both the mathematical and economic perspective of the subject.
This is also supported by invited lectures from senior staff members of leading financial institutions and outstanding mathematicians who are internationally recognised for contributions to Mathematical Finance. Past lectures include:
The course provides students with advanced knowledge and understanding of the main theoretical and applied concepts in Mathematical Finance delivered from a genuinely international and multi-cultural perspective with a current issues approach to teaching. The focus is on mathematical theory and modelling, drawing from the disciplines of probability theory, scientific computing and partial differential equations to derive relations between asset prices and interest rates, and to develop models for pricing, risk management and financial product development.
The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.
Teaching is shared by the School of Mathematics and Alliance Manchester Business School, and delivered through lectures, case studies, seminars and group project-based work.
There are (i) eight course units to attend over two academic terms and (ii) a dissertation project to be completed in the summer term. Teaching of the course units is shared by the School of Mathematics and the Manchester Business School and delivered through lectures, case studies, seminars and group project-based work.
First term course units (autumn): Derivative Securities; Foundations of Finance Theory; Martingales with Applications to Finance; Stochastic Calculus.
Second term course units (spring): Brownian Motion; Computational Finance; Time Series Analysis and Forecasting in Finance; Stochastic Modelling in Finance.
Third term dissertation project (summer): In this term students will conduct an original study of a topic relating to the programme and write an MSc dissertation.
The fees quoted above will be fully inclusive for the course tuition, administration and computational costs during your studies.
All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of courses lasting more than a year for UK/EU students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit: postgraduate fees . Always contact the department if you are unsure which fee applies to your qualification award and method of attendance.
Self-funded international applicants for this course will be required to pay a deposit of £1000 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. This deposit will only be refunded if immigration permission is refused. We will notify you about how and when to make this payment.
The School of Mathematics is one of the largest integrated departments of mathematical sciences in the UK with an outstanding reputation and superb facilities .
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.
The Masters Programme aims to develop students’ mathematical and computational skills, and also those in financial modelling.
The curriculum includes such subjects as probability theory, stochastic calculus, numerical methods, optimisation and control theory, stochastic finance, interest rate models and credit risk. It thus provides a thorough training in modern mathematical finance. In studying for our Masters, students are put in contact with the most important technical and quantitative topics of finance, both theoretical and applied, which range from mathematical background to the latest trends in the financial sector. Increasingly, the financial sector demands a Masters degree in Mathematical Finance from a prestigious university as a prerequisite for recruitment. Our students have often been recruited by prominente companies whilst still preparing their Masters’ thesis, at both a national and na international level. Amongst others, such companies include: EY, Mercer, KPMG, Deloitte, CGD, the Bank of Portugal, BNP Paribas, BPI, Banque Européenne d’Investissement (EIB), Banque Centrale Européenne, Lloyds Bank, and Santander bank. ISEG - Lisbon School of Economics and Management, of ULisboa, has well established departments of Mathematics, Economics and Management, which enables our students to benefit from the consequent synergies, and it provides excellent conditions for hosting the Masters in Mathematical Finance. This fact, together with the high quality of the academic staff of this Masters, all of whom hold PhDs from prestigious universities (such as the Stockholm School of Economics and the Universities of Oxford, Edinburgh and Barcelona), makes it unique in our country.
MSc Risk Management & Financial Engineering is a highly quantitative programme tailored to high calibre and technically-minded graduates wanting a deeper, more analytical study of risk management and financial engineering than is found in general finance programmes.
The programme is accredited by the Professional Risk Managers’ International Association (PRMIA) and the School offers students on this programme the opportunity to attend PRMIA events, have access to its resources and receive considerable discounts on PRMIA exams.
In September you will study five foundation modules to introduce the tools of modern finance and enhance your career development skills. These include:
• Markets and Securities
• Financial Modelling
• Application of Matlab to Finance
• Data Structures and Algorithms using Python
• The Finance Industry
You’ll take eight core modules which are the backbone of our programme, providing you with a solid knowledge base in each subject area. Each module builds on previous experience while introducing new and challenging disciplines. These include:
• Empirical Finance: Methods and Applications
• Financial Engineering
• Financial Statistics
• Investments and Portfolio Management
• Risk Management and Valuation
• Stochastic Calculus
You will also receive training in Visual Basic for Applications (VBA), choose from a variety of electives and undertake a final project. The selection of electives include:
• Advanced Options Theory
• Credit Risk
• Advanced Financial Statistics
• Enterprise Risk Management
• Fixed Income Securities
• International Elective: Macro and Finance for Practitioners
• International Finance
• Insurance
• Structured Credit and Equity Products
• Private Equity and Venture Capital
• Wealth Management and Alternative Investments
• Topics in FinTech Innovation
