Masters Degrees in Probability, United Kingdom

You can study this Mathematical Sciences MSc programme full-time or part-time. It offers students the opportunity to specialise in a broad range of areas across pure and applied mathematics, statistics and probability, and theoretical physics.

The topics we cover include:

- advanced probability theory
- algebra
- asymptotic methods
- geometry
- mathematical biology
- partial differential equations
- quantum field theory
- singularity theory
- stochastic analysis
- standard model/string theory.

By completing the first semester you qualify for the PG certificate. By completing the second, you qualify for the PG Diploma. Then, by completing your dissertation, you qualify for the MSc.

Key Facts

REF 2014
92% of our research impact judged at outstanding and very considerable, 28% improvement in overall research at 4* and 3*.

Facilities
A dedicated student resource suite is available in the Department, with computer and reading rooms and a social area.

Why Department of Mathematical Sciences?

Range and depth of study options

We offer a very wide range of modules, from advanced algebra and geometry, to partial differential equations, probability theory, stochastic analysis, and mathematical physics. With these you can tailor your programme to specialise in one of these areas, or gain a broad understanding of several. This allows you to build up the required background for the project and dissertation modules, which offer the opportunity to undertake an in-depth study of a topic of your choice, supervised by a leading expert in the field.

Exceptional employability

At Liverpool, we listen to employers’ needs. Alongside key problem solving skills, employers require strong communication skills. These are integral to this programme. Graduates go on to research degrees, or become business and finance professionals, or to work in management training, information technology, further education or training (including teacher training) and scientific research and development.

Teaching quality

We are proud of our record on teaching quality, with five members of the Department having received the prestigious Sir Alastair Pilkington Award for Teaching. We care about each student and you will find the staff friendly and approachable.

Accessibility

We take students from a wide variety of educational backgrounds and we work hard to give everyone the opportunity to shine.

Supportive atmosphere

We provide high quality supervision and teaching, computer labs, and and you will benefit from the friendly and supportive atmosphere in the Department, as evidenced by student feedback available on our university website. A common room and kitchen for the exclusive use of the Department’s students, and a lively maths society help to foster a friendly and supportive environment.

Career prospects

The excellent University Careers Service is open to all postgraduates. Graduates of the MSc and PhD programmes move on to many different careers. Recent graduates have moved into fast track teacher programmes, jobs in finance (actuarial, banking, insurance), software development, drugs testing and defence work, as well as University postdoctoral or lecturing posts. The MSc programme is of course a natural route into doctoral study in Mathematics and related fields, both at Liverpool and elsewhere. Some of our PhD students move on to postdoctoral positions and to academic teaching jobs and jobs in research institutes, both in the UK and elsewhere.

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About the course

Mathematical finance is an area of applied mathematics where concepts and techniques that lie close to the heart of pure mathematics are applied routinely to solve a great variety of important practical problems arising in the day-to-day business of the world's financial institutions.

The objective of the Brunel MSc in Financial Mathematics is to guide students through to a mastery of the sophisticated mathematical ideas underlying modern finance theory, along with the associated market structures and conventions, with emphasis on:

- The modelling of the dynamics of financial assets, both in equity markets and in fixed-income markets
- The pricing and hedging of options and other derivatives, and
- The quantification and management of financial risk.

Candidates are also provided with the means to master the numerical and computational skills necessary for the practical implementation of financial models, thus enabling you to put theory into practice and putting you in a good position to carry out work for a financial institution. We therefore offer a programme that provides a balanced mixture of advanced mathematics (including modern probability theory and stochastic calculus), modern finance theory (including models for derivatives, interest rates, foreign exchange, equities, commodities, and credit), and computational technique (GPU-based high-performance computing).

The MSc in Financial Mathematics offers a range of exciting modules during the Autumn and the Spring terms, followed by an individual research project leading to a dissertation that is completed during the Summer term.

Aims

Financial mathematics is a challenging subject, the methods of which are deployed by sophisticated practitioners in financial markets on a daily basis. It builds on the application of advanced concepts in modern probability theory to enable market professionals to tackle and systematically resolve a huge range of issues in the areas of pricing, hedging, risk management, and market regulation. The main objective of the Brunel MSc in Financial Mathematics is to provide candidates with the knowledge they need to be able to enter into this exciting new area of applied mathematics and to position themselves for the opportunity to work in financial markets.

Among the main distinguishing features of our programme are the following:

We aim to teach the key ideas in financial asset pricing theory from a thoroughly modern perspective, using concepts and methods such as pricing kernels, market information filtrations, and martingale techniques, as opposed say to the more traditional but old-fashioned approach based on the historical development of the subject.

In our programme candidates are asked at each stage to undertake a critical re-examination of the hypotheses implicit in any financial model, with a view to gaining a clear grasp of both its strengths and its limitations.

The programme includes courses on high-performance computing that provide candidates with the techniques whereby financial models can be implemented.

Course Content

Programme structure

The programme offers five "compulsory" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. There are lectures, examinations and coursework in eight modules altogether, including the five compulsory modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.

Compulsory modules:

Probability and stochastics
Financial markets
Option pricing theory
Interest rate theory
Financial computing I

Elective Modules:

Portfolio theory
Information in finance with application to credit risk management
Mathematical theory of dynamic asset pricing
Financial computing II
Statistics for Finance
Financial Mathematics Dissertation

Special Features

The Department of Mathematics, home to its acclaimed research centre CARISMA, has a long tradition of research and software development, in collaboration with various industry partners, in the general area of risk management.

The Department is a member of the London Graduate School in Mathematical Finance, which is a consortium of mathematical finance groups of Birkbeck College, Brunel University London, Imperial College London, King’s College London, London School of Economics, and University College London. There is a strong interaction between the financial mathematics groups of these institutions in the greater London area, from which graduates can benefit. In particular there are a number of research seminars that take place regularly throughout the year which students are welcome to attend.

Assessment

Assessment is by a combination of coursework, examination, and dissertation. Examinations are held in May. The MSc degree is awarded if the student reaches the necessary overall standard on the taught part of the course and submits a dissertation that is judged to be of the required standard. Specifically, to qualify for the MSc degree, the student must: (a) take examinations in eight modules including the four compulsory modules, (b) attain the minimum grade profile (or better) required for a Masters degree and (c) submit a dissertation of the required standard. If a student does not achieve the requirements for the degree of MSc, they may, if eligible, be awarded a Postgraduate Diploma.

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The MSc Financial Mathematics programme enables graduates and professionals with a strong mathematics background to research, develop and apply quantitative and computational techniques to finance. It covers topics from classical options pricing to post-crisis investment and risk management. The Department of Mathematics has a superb reputation for research-led teaching and strong links to industry and our graduates are highly sought after.

Key benefits

- A rigorous approach to quantitative finance taught entirely by the Department of Mathematics.

- End-to-end coverage of the skills needed for working in the financial, actuarial or related industry: probability theory, optimisation, statistics and computer implementation.

- Unrivalled facilities, including access to live market data in our Bloomberg Data laboratory.

- A stone’s throw from the City of London's financial centre

- Full or part time study (most lectures given late afternoons)

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/financial-mathematics-msc.aspx

Course detail

- Description -

Financial mathematics plays a crucial role in all sectors of financial markets including fixed income, credit derivatives, pensions, insurances, energy and even bets on the weather. The application of mathematics has had a profound effect upon finance and has allowed the creation of entirely new markets for financial products.

The financial mathematics programme at King’s is unique in its emphasis upon mathematical rigour. It encompasses all the skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. Our outstanding teaching is matched by outstanding facilities for the study and research of financial markets.

- Course purpose -

This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.

- Course format and assessment -

At least eight taught modules assessed by written examinations and one individual project. Two prizes are normally awarded each year for best overall performance in the MSc in Financial Mathematics.

Career prospects

Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 20 universities worldwide (2015/16 QS World Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

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This cutting edge MSc programme will equip you with the mathematical, financial and computational skills needed to quantify and manage risk effectively in today’s finance, investment and insurance industries. Such companies use advanced probabilistic models at the core of their business. They recruit people with the right mathematical, statistical and programming skills and financial knowledge who can understand, develop and implement such models.

The course is also an excellent preparation for students wishing to embark upon research degree (PhD) in financial or actuarial mathematics. Working professionals who would like to move from their current field into finance or for finance professionals who would like to take their careers to the next level will also benefit greatly from this course.

You will gain a strong understanding of:

- applied probability theory, stochastic analysis and mathematical modelling
- computational methods
- financial derivatives
- risk management methodologies
- financial econometrics

The 12-month programme consists of seven taught compulsory modules plus one taught elective module, followed by a research project carried out over the summer period upon completion of Semester Two. The course is taught mainly by members of the Institute for Financial and Actuarial Mathematics which is part of the Department of Mathematical Sciences . Some relevant modules are taught by the Management School.

Why Department of Mathematical Sciences?

Range and depth of study options

We offer a very wide range of modules, from advanced algebra and geometry, to partial differential equations, probability theory, stochastic analysis, and mathematical physics. With these you can tailor your programme to specialise in one of these areas, or gain a broad understanding of several. This allows you to build up the required background for the project and dissertation modules, which offer the opportunity to undertake an in-depth study of a topic of your choice, supervised by a leading expert in the field.

Exceptional employability

At Liverpool, we listen to employers’ needs. Alongside key problem solving skills, employers require strong communication skills. These are integral to this programme. Graduates go on to research degrees, or become business and finance professionals, or to work in management training, information technology, further education or training (including teacher training) and scientific research and development.

Teaching quality

We are proud of our record on teaching quality, with five members of the Department having received the prestigious Sir Alastair Pilkington Award for Teaching. We care about each student and you will find the staff friendly and approachable.

Accessibility

We take students from a wide variety of educational backgrounds and we work hard to give everyone the opportunity to shine.

Supportive atmosphere

We provide high quality supervision and teaching, computer labs, and and you will benefit from the friendly and supportive atmosphere in the Department, as evidenced by student feedback available on our university website. A common room and kitchen for the exclusive use of the Department’s students, and a lively maths society help to foster a friendly and supportive environment.

Career prospects

The excellent University Careers Service is open to all postgraduates. Graduates of the MSc and PhD programmes move on to many different careers. Recent graduates have moved into fast track teacher programmes, jobs in finance (actuarial, banking, insurance), software development, drugs testing and defence work, as well as University postdoctoral or lecturing posts. The MSc programme is of course a natural route into doctoral study in Mathematics and related fields, both at Liverpool and elsewhere. Some of our PhD students move on to postdoctoral positions and to academic teaching jobs and jobs in research institutes, both in the UK and elsewhere.

Upon successful completion of the degree you will be ideally equipped to work in investment banks, pension or investment funds, hedge funds, consultancy and auditing firms or government regulators.

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In recent years, finance has been one of the areas where high-calibre mathematicians have been in great demand. With the advent of powerful and yet economically accessible computing, online trading has become a common activity, but many have realised that a certain amount of mathematics is necessary to be successful in such fields.

One of our most popular courses, MSc Mathematics and Finance allows those with a background in mathematics to study finance. Since finance routinely involves modelling and evaluating risk, asset pricing and price forecasting, mathematics has become an indispensable tool for this study.

You explore topics including:
-Models and mathematics in portfolio management
-Risk management in modern banking
-Financial modelling
-Actuarial modelling
-Applied statistics

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00610&subgroup=2

Our expert staff

Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

There is undoubtedly a shortage of mathematicians in general, and an even greater one of those with knowledge of finance.

Our course produces graduates with a sound background in mathematics and finance. Key employability skills include computing, use of algorithms, data analysis, mathematical modelling and understanding financial statements.

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Dissertation
-Research Methods
-Financial Modelling
-Mathematics of Portfolios
-Research Methods in Finance: Empirical Methods in Finance
-Stochastic Processes
-Applied Statistics (optional)
-Bank Strategy and Risk (optional)
-Bayesian Computational Statistics (optional)
-Combinatorial Optimisation (optional)
-Derivative Securities (optional)
-Economics of Financial Markets (optional)
-Financial Derivatives (optional)
-Ordinary Differential Equations (optional)
-Partial Differential Equations (optional)
-Statistical Methods (optional)
-Metric Spaces

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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:
-Professor M. Schweizer (ETH Zurich and Swiss Finance Institute) An overview of quadratic hedging and related topics
-Professor H. Follmer (Humboldt University of Berlin) Monetary valuation of cash flows under Knightian uncertainty
-Professor M. H. A. Davis (Imperial College London) Contagion models in credit risk

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.

Coursework and assessment

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.

Career opportunities

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.

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The MSc in Mathematics gives an in-depth training in advanced mathematics to students who have
already obtained a first degree with substantial mathematical content. Students successfully completing the MSc will acquire specialist knowledge in their chosen areas of mathematics, and the MSc is an excellent preparation for those who are considering pursuing research in mathematics.

The main areas of mathematics that may be pursued within this MSc are pure mathematics (especially algebra and combinatorics), dynamical systems, probability and statistics, and astronomy. The MSc programme is very flexible, and in consultation with your academic adviser you may choose modules in different areas or specialise in one.

Programme outline
You will normally take eight modules in total, with one module typically comprising 24 hours of lectures and 12 hours of tutorials given during a twelve-week semester. In addition to the MSc modules offered at Queen Mary, you can also choose from an extremely wide range of advanced mathematics modules offered at other Colleges of the University of London. During the summer period, supervised by an academic member of staff, you are required to complete a dissertation, working largely independently in an advanced topic in mathematics or statistics.

For details of modules typically offered, see: http://www.maths.qmul.ac.uk/postgraduate/msc-maths-stats/modules

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This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

This MSc will give an Operational Research perspective on risk and its management.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses have previously included:

• Computing for OR and Finance
• Fundamentals of Optimization
• Fundamentals of OR
• Methodology, Modelling and Consulting Skills
• Probability and Statistics
• Simulation
• Stochastic Modelling

Option courses are generally grouped into the following areas:

• Finance
• Industry
• Optimization
• Statistics

As part of your option course choices Operational Research with Risk requires you to study a combination from a set of courses which, previously, has included

• Credit Scoring
• Stochastic Optimization
• The Analysis of Survival Data
• Statistical Modelling
• Risk Analysis

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined British Airways, the Government OR Service, Barclays, Deloitte, Capgemini and smaller specialised OR, finance and energy companies.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

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This course, commonly referred to as Part III, is a one-year taught Master's course in mathematics. It is an excellent preparation for mathematical research and it is also a valuable course in mathematics and in its applications for those who want further training before taking posts in industry, teaching, or research establishments.

Students admitted from outside Cambridge to Part III study towards the Master of Advanced Study (MASt). Students continuing from the Cambridge Tripos for a fourth year, study towards the Master of Mathematics (MMath). The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree.

There are over 200 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. There are normally about 80 courses, covering an extensive range of pure mathematics, probability, statistics and the mathematics of operational research, applied mathematics and theoretical physics. They are designed to cover those advanced parts of the subjects that are not normally covered in a first degree course, but which are an indispensable preliminary to independent study and research. Students have a wide choice of the combination of courses that they offer, though naturally they tend to select groups of cognate courses. Normally classes are provided as back-up to lecture courses.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/mapmaspmm

Course detail

The structure of Part III is such that students prepare between six and nine lecture courses for examination. These lecture courses may be selected from the wide range offered by both Mathematics Departments. As an alternative to one lecture course, an essay may be submitted. Examinations usually begin in late May, and are scheduled in morning and afternoon sessions, over a period of about two weeks. Two or three hours are allocated per paper, depending on the subject. Details of the courses for the current academic year are available on the Faculty of Mathematics website. Details for subsequent years are expected to be broadly similar, although not identical.

Most courses in the Part III are self-contained. Students may freely mix courses offered by the two Mathematics Departments. Courses are worth either two or three credit units depending on whether they last for 16 or 24 lectures respectively. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units. An essay (should a candidate choose to submit one) counts for 3 credit units. Part III is graded Distinction, Merit, Pass or Fail. A Merit or above is the equivalent of a First Class in other Parts of the Mathematical Tripos.

Learning Outcomes

After completing Part III, students will be expected to have:

- Studied advanced material in the mathematical sciences to a level not normally covered in a first degree;
- Further developed the capacity for independent study of mathematics and problem solving at a higher level;
- Undertaken (in most cases) an extended essay normally chosen from a list covering a wide range of topics.

Students are also expected to have acquired general transferable skills relevant to mathematics as outlined in the Faculty Transferable Skills Statement http://www.maths.cam.ac.uk/undergrad/course/transferable_skills.pdf .

Format

Courses are delivered predominantly by either 16 or 24 hours of formal lectures, supported by additional examples classes. As an alternative to one lecture course, an essay may be submitted. There is also the possibility of taking a reading course for examination. There are normally additional non-examinable courses taught each year.

Essay supervision and support for lectures by means of examples classes is approximately 30 hours per year.

Formal examinable lectures and non-examinable lectures total approximately 184 hours per year, of which on average 112 hours are for examinable courses.

Some statistics courses may involve practical data analysis sessions.

There is an opportunity to participate in the Part III seminar series, either by giving a talk or through attendance. This is encouraged but does not contribute to the formal assessment.

Twice a year students have an individual meeting with a member of academic staff to discuss their progress in Part III. Students offering an essay as part of their degree may meet their essay supervisor up to three times during the academic year.

Assessment

Candidates may substitute an essay for one lecture course. The essay counts for 3 credit units.

Lecture courses are assessed by formal examination. Courses are worth either two or three credit units depending on whether they are 16 or 24 hours in length respectively. A 16 hour course is assessed by a 2 hour examination and a 24 hour course, a 3 hour examination. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units.

Continuing

MASt students wishing to apply for the PhD must apply via the Graduate Admissions Office for readmission by the relevant deadline. Applicants will be considered on a case by case basis and offer of a place will usually include an academic condition on their Part III result.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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Our Quantitative Finance and Risk Management MSc will develop your understanding of generalist finance issues. You'll also develop specialist practical skills in quantitative methodology and risk management.

Worldwide growth in the financial services sector has fuelled the demand for graduates with a sound understanding of generalist finance issues, combined with specialist skills in quantitative methodology and risk management. This course meets this demand. It builds on the Business School’s established strengths in economics and finance.

The course advances your understanding of the:
-Role of finance in a modern economy
-Operation and behaviour of financial markets and investors
-It will enable you to develop a career in the financial services sector. It will also suit future quantitative analysts in economics and finance.

What you'll learn

This course will provide opportunities for you to develop relevant skills and a practical understanding of:
-The behaviour of international financial markets
-The ability to analyse the strategies of financial market investors
-The role of finance in a modern economy

Advanced software

Where possible you will have access to advanced statistical software including:
-Eviews
-SPSS
-Stata
-Gauss
-MATLAB
-SAS
-Maple
-Minitab

You will also have access to a number of financial databases including:
-Bloomberg
-Thompson Financial's DataStream
-Fame
-Amadeus
-WRDS
-Compustat
-CRSP
-Oriana

Your development

On completion of this course, you will be able to demonstrate practical skills and the ability to:
-Deal with complex issues both systematically and analytically
-Use this analysis to make sound judgements
-Deploy advanced analytical techniques in the areas of finance and risk management
-Critically assess the quality of the analytical data generated by these techniques
-Synthesise and present relevant data, conclusions and recommendations to both specialist and non-specialist audiences
-Apply the knowledge, skills and understanding gained on the programme to complex issues within finance and related industries

Career focus

The course will suit those wanting to develop a career in the broad financial services sector. It is particularly relevant to a career as a quantitative analyst in the investment banking and risk management fields.

Graduates from this course have undertaken various roles including:
-Senior Associate Chartered Accountant
-Financial Trader
-Auditor
-Risk Analyst
-Economist
-Financial Analyst
-Investor Relations Advisor

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This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights, handling large data sets to managing investments and minimising risks. The skills of Operational Research (OR) and Data Science are in high demand.

The MSc in Operational Research with Data Science is a new, forward-looking programme that delivers high-quality training in operational research, optimization and statistics. Students will have strong technical skills in these areas and the ability to apply them using appropriate software.

This MSc programme delivers:

• technical skills in operational research, optimization and statistics
• practical skills in programming and modelling for a wide range of applications
• communications skills in writing and audio-visual presentation

Programme structure

You need to obtain a total of 180 credits to be awarded the MSc. All students take courses during semester 1 and 2 to the value of 120 credits. Successful performance in these courses (assessed through coursework or examinations or both) permits you to start work on a three-month dissertation project (60 credits) for the award of the MSc degree.

Compulsory courses have previously included:

• Fundamentals of Optimization
• Fundamentals of Operational Research
• Methodology, Modelling and Consulting Skills
• Computing for Operational Research and Finance

Themed courses have previously included:

• Simulation
• Statistical Regression Models
• Machine Learning & Pattern Recognition
• Introductory Applied Machine Learning
• Bioinformatics 1
• Stochastic Modelling
• Credit Scoring
• Large Scale Optimization for Data Science
• Modern Optimization Methods for Big Data Problems
• Optimization Methods in Finance
• Combinatorial Optimization
• Time Series Analysis and Forecasting
• Advanced Computing for Operational Research
• Operational Research in Telecommunications
• Biomedical Data Science
• The Analysis of Survival Data
• Likelihood and Generalized Linear Models
• Probabilistic Modelling and Reasoning

Optional courses chosen from postgraduate courses in the following areas:

• Finance
• Industry
• Optimization
• Statistics
• Data Science

Learning outcomes

At the end of this programme you will have:

• flexible problem-solving skills based on deep knowledge of operational research, optimization, data analysis techniques and the ability to apply them using appropriate software
• transferable skills to maximize their prospects for future employment, including writing, oral presentation, team-working, numerical and logical problem-solving, planning and time-management

Career opportunities

Graduates will gain the transferable skills required to pursue careers in a data-rich operational research environment, and will be in an ideal position to apply for work in a wide range of institutions in the public and private sector. The degree is also excellent preparation for further study in operational research, optimization or data science.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

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Our suite of Finance Master’s degrees brings you a deep theoretical and conceptual knowledge of finance and related quantitative skills, which will prepare you for a range of careers in global financial institutions and blue-chip companies. Our postgraduates are highly employable in a wide range of roles. The skills they acquire at WBS open up opportunities to work for banks and treasuries, asset managers, regulators and consultancies, policy-makers and many others.

Course Details

Six core modules cover key material in finance, statistics and maths. Every year we offer many elective modules, available through various study routes: delivered here at WBS. Please note that availability and delivery modes may vary.

Modules are taught by staff from WBS, Warwick's Department of Statistics, and the Mathematics Institute through a combination of lectures, classes, and computer lab sessions. A one-week induction module, run by the Mathematics Institute, will ensure you have the mathematical prerequisites for the course. Assessment is a mix of exams and coursework with your dissertation bringing all your learning together at the end.

Lectures & classes

Lectures introduce key theories, concepts, and economic models. You will solve financial problems and numerical exercises, analyse case studies, and make presentations of research published in academic journals.

Lab work

Lab work will give you hands-on experience of using software to perform finance-related calculations and conduct realistic simulations. Econometric methods are also taught in the lab, so you will learn to apply econometric software to empirical research and financial market estimations.

Your dissertation

A 10,000 word dissertation gives you the opportunity to test and apply techniques and theories you have been learning and to complete an original piece of research. You will be supervised and supported by one of our academic staff.

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The MSc in Insurance and Risk Management is a well-established course that explores the multi-faceted world of risk management and reflects the growing interplay between insurance, risk management and financial services. As such, it will equip you with the all-round skills necessary to succeed in a constantly developing business environment.

The programme combines a practical approach with sound theory to create a learning experience that is both challenging and stimulating. You will emerge with a well-regarded and flexible postgraduate degree, solidly positioned to build a successful career in an exciting and increasingly complex business world.

Cass's location, close to the City of London, has enabled us to establish close links with many leading financial organisations. This will help you to access outstanding networking and career opportunities.

Professional examinations

Students have the opportunity to earn substantial exemptions from professional examinations in the field of insurance and risk management, including 205 - 210 credits towards the 290 required for the Chartered Insurance Institute (CII) Advanced Diploma. Exemptions are also given from some examinations of the Institute of Risk Management (IRM).

Visit the website: http://www.cass.city.ac.uk/courses/masters/courses/insurance-and-risk-management/2017

Course detail

The MSc in Insurance & Risk Management starts with two compulsory induction weeks, focused on:

• An introduction to the Cass Careers offering with a focus on key skills and attributes that employers are looking for. The annual MSc Careers Fair at this time also provides the opportunity to meet over 60 companies who are recruiting across many sectors including finance, energy, insurance, real estate, shipping, strategic management and internal auditing.

• a refresher course of basic financial mathematics, statistics, computing and electronic databases.

Format

To satisfy the requirements of the degree course students must complete:

• eight core courses (15 credits each)
and
• five electives (10 credits each)
or
• one elective (10 credits) and a Business Research Project (40 credits)

Assessment

Assessment of modules on the MSc in Insurance & Risk Management, 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.

Career opportunities

Our graduates enjoy senior positions across the world in many types of businesses including international insurance, reinsurance and insurance broking firms, Lloyd's of London, leading investment and retail banks, leading accountancy firms, management consultancies, risk management departments of major corporations, regulatory authorities and many other fields.

Some examples of where graduates from the MSc in Insurance and Risk Management class of 2014 are working are:

• Centre Bank of Malaysia – Supervisor
• One Alliance Insurance Services – Intern
• EY – Consultant, Financial Services Risk Advisory
• Kenya Pipeline – Legal Officer.

How to apply

Apply here: http://www.city.ac.uk/study/postgraduate/applying-to-city

Funding

For information on funding, please follow this link: http://www.city.ac.uk/study/postgraduate/funding-and-financial-support

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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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About the MSc programme

The MSc Financial Mathematics is based in the Department of Mathematics, and is taught in collaboration with the Department of Finance and the Department of Statistics. The programme draws on LSE's strengths in finance and related areas to provide high-level instruction in the mathematical theory underlying finance, and training in appropriate computational methods.

The programme aims to develop your understanding of quantitative methodologies and techniques which are important for a range of jobs in investment banks and other financial institutions; to enhance your critical appreciation of major issues and emerging theory in the area of financial mathematics; and to improve your personal skills, including logical reasoning, quantitative analysis and the presentation of technical results.

In addition to compulsory courses in The Mathematics of the Black and Scholes Theory, The Foundations of Interests Rate and Credit Risk Theory, Stochastic Processes, Fixed Income Markets, and Computational Methods in Finance, you will choose optional courses to the value of one and a half units. Choices include stochastic analysis, preferences, optimal portfolio choice, equilibrium, derivatives modelling, Markov processes, financial risk analysis, international finance, and forecasting of financial time series.

Graduate destinations

This programme is ideal preparation for a range of careers in the financial sector, industry and research.

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