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Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes. Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes: Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

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.

Key Features

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.

Course Content

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.

Facilities

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.

Careers

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.

Research

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.

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The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role. Read more
The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role.

The depth of the mathematics taught should enable graduates to pursue research careers in stochastic analysis, financial mathematics or other relevant areas.

The period October to June is devoted to lectures, tutorials and practical sessions comprising the core and optional modules. This is followed by a period of about 14 weeks devoted to an individual project.

Core study areas include measure theory and martingales, stochastic models in finance, stochastic calculus and theory of stochastic pricing and a research project.

Optional study areas include programming and numerical methods, regular and chaotic dynamics, financial economics, functional analysis, elements of PDEs, static and dynamic optimisation, asset management and derivatives, and corporate finance

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

Programme modules

Semester 1:
Compulsory Modules
- Introduction to Measure Theory and Martingales
- Stochastic Models in Finance

Optional Modules (choose two)
- Programming and Numerical Methods
- Regular and Chaotic Dynamics
- Financial Economics

Semester 2:
Compulsory Modules
- Stochastic Calculus and Theory of Stochastic Pricing
- Research Project

Optional Modules (choose three)
- Functional Analysis
- Elements of PDEs
- Static and Dynamic Optimisation
- Either Asset Management and Derivatives or Corporate Finance

Assessment

A combination of written examinations, reports, individual and group projects, and verbal presentations.

Careers and further study

This programme may lead to a wide range of employment within industry, the financial sectors, and research establishments. It may also provide an ideal background for postgraduate research in Stochastic Analysis, Probability Theory, Mathematical Finance and other relevant areas.

Scholarships and sponsorships

A number of part-fee studentships may be available to appropriately qualified international students.

Why choose mathematics at Loughborough?

Mathematics at Loughborough has a long history of innovation in teaching, and we have a firm research base with strengths in both pure and applied mathematics as well as mathematics education.

The Department comprises more than 34 academic staff, whose work is complemented and underpinned by senior visiting academics, research associates and a large support team.

The programmes on offer reflect our acknowledged strengths in pure and applied research in mathematics, and in some cases represent established collaborative training ventures with industrial partners.

- Mathematics Education Centre (MEC)
The Mathematics Education Centre (MEC) at Loughborough University is an internationally renowned centre of research, teaching, learning and support. It is a key player in many high-profile national initiatives.
With a growing number of academic staff and research students, the MEC provides a vibrant, supportive community with a wealth of experience upon which to draw.
We encourage inquiries from students who are interested in engaging in research into aspects of learning and teaching mathematics at Masters, PhD and Post Doc levels. Career prospects With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

- Career prospects
With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates
go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

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This programme gives you a flexible syllabus to suit the demands of employers that use modern financial tools and optimization techniques in areas such as the financial sector and energy markets. Read more

Programme description

This programme gives you a flexible syllabus to suit the demands of employers that use modern financial tools and optimization techniques in areas such as the financial sector and energy markets.

We will give you sound knowledge in financial derivative pricing, portfolio optimization and financial risk management.

We will also provide you with the skills to solve some of today’s financial problems, which have themselves been caused by modern financial instruments. This expertise includes modern probability theory, applied statistics, stochastic analysis and optimization.

Adding depth to your learning, our work placement programme puts you at the heart of financial organisations such as Aberdeen Asset Management, Barrie & Hibbert and Lloyds Banking Group.

Programme structure

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

Compulsory courses:

Discrete-Time Finance
Finance, Risk and Uncertainty
Fundamentals of Optimization
Optimization Methods in Finance
Research-Linked Topics
Risk-Neutral Asset Pricing
Simulation
Stochastic Analysis in Finance I
Stochastic Analysis in Finance II

Option courses:

Advanced Time Series Econometrics
Combinatorial Optimization
Credit Scoring
Fundamentals of Operational Research
Financial Risk Management
Computing for Operational Research and Finance
Large Scale Optimization for Data Science
Microeconomics 2
Nonlinear Optimization
Numerical Partial Differential Equations
Parallel Numerical Algorithms
Programming Skills
Risk Analysis
Stochastic Modelling
Stochastic Optimization

Career opportunities

Graduates have gone on to work in major financial institutions or to continue their studies by joining PhD programmes.

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The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods. Read more

Programme description

The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods.

Currently graduates in this field are expected to have a working knowledge of advanced computational finance (including construction of algorithms and programming skills) as well as a sound knowledge of the theory of Probability and Stochastic Analysis. These are the core theories needed in the modern valuation of complex financial instruments.

This MSc programme delivers:

a flexible programme of study relevant to the needs of employers such as: top investment banks, hedge funds and asset management firms
a solid knowledge in financial derivative pricing, risk management and portfolio management
the transferable computational skills required by the modern quantitative finance world

Programme structure

You must obtain a total of 180 credits to be awarded the MSc. Over semesters 1 and 2, you will take compulsory courses worth a total of 85 credits and optional courses worth a further 35 credits. Successful performance in these courses (assessed through coursework or examinations or both) allows you to start work on a three-month dissertation project, worth 60 credits, for the award of the MSc degree.

There are two streams: the Financial stream and the Computational stream.

Compulsory courses (both streams):

Stochastic Analysis in Finance (20 credits, semester 1)
Discrete-Time Finance (10 credits, semester 1)
Finance, Risk and Uncertainty (10 credits, semester 1)
Object-Oriented Programming with Applications (10 credits, semester 1)
Risk-Neutral Asset Pricing (10 credits, semester 2)
Stochastic Control and Dynamic Asset allocation (10 credits, semester 2)
Monte Carlo Methods (5 credits, semester 2)
Research-Linked Topics (10 credits, semesters 1 and 2)

Optional courses - Computational stream:

Numerical Methods for Stochastic Differential Equations [compulsory] (5 credits, semester 2)
Numerical Partial Differential Equations [compulsory] (10 credits, semester 2)
Programming Skills - HPC MSc (10 credits, semester 1)
Parallel Numerical Algorithms - HPC MSc (10 credits, semester 1)

Optional courses - Financial stream:

Financial Risk Theory [compulsory] (10 credits, semester 2)
Optimization Methods in Finance [compulsory] (10 credits, semester 2)
Advanced Time Series Econometrics (10 credits, semester 2)
Credit Scoring (10 credits, semester 2)
Computing for Operational Research and Finance (10 credits, semester 1)
Financial Risk Management (10 credits, semester 2)
Stochastic Optimization (5 credits, semester 2)

Learning outcomes

At the end of this programme you will have:

developed personal communications skills, initiative, and professionalism within a mathematical context
developed transferable skills that maximise your prospects for future employment, including writing, oral presentation, team-working, numerical and logical problem-solving, planning and time-management
improved your ability to convey ideas in an articulate fashion, to build upon previous mathematical training and further develop logic and deductive skills
mastered standard and advanced mathematical tools used to solve applied problems relevant to the mathematical finance industry
developed quantitative and computational skills for the proficient fulfilment of tasks in the financial sector

Career opportunities

Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.

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Programme structure. The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. Read more
Programme structure
The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. There are examinations and coursework in eight modules altogether, including the four core modules. Additionally, all students complete a dissertation.

Core modules
0.Probability and stochastics. This course provides the basics of the probabilistic ideas and mathematical language needed to fully appreciate the modern mathematical theory of finance and its applications. Topics include: measurable spaces, sigma-algebras, filtrations, probability spaces, martingales, continuous-time stochastic processes, Poisson processes, Brownian motion, stochastic integration, Ito calculus, log-normal processes, stochastic differential equations, the Ornstein-Uhlenbeck process.


0.Financial markets. This course is designed to cover basic ideas about financial markets, including market terminology and conventions. Topics include: theory of interest, present value, future value, fixed-income securities, term structure of interest rates, elements of probability theory, mean-variance portfolio theory, the Markowitz model, capital asset pricing model (CAPM), portfolio performance, risk and utility, portfolio choice theorem, risk-neutral pricing, derivatives pricing theory, Cox-Ross-Rubinstein formula for option pricing.


0.Option pricing theory. The key ideas leading to the valuation of options and other important derivatives will be introduced. Topics include: risk-free asset, risky assets, single-period binomial model, option pricing on binomial trees, dynamical equations for price processes in continuous time, Radon-Nikodym process, equivalent martingale measures, Girsanov's theorem, change of measure, martingale representation theorem, self-financing strategy, market completeness, hedge portfolios, replication strategy, option pricing, Black-Scholes formula.


0.Financial computing I. The idea of this course is to enable students to learn how the theory of pricing and hedging can be implemented numerically. Topics include: (i) The Unix/Linux environment, C/C++ programming: types, decisions, loops, functions, arrays, pointers, strings, files, dynamic memory, preprocessor; (ii) data structures: lists and trees; (iii) introduction to parallel (multi-core, shared memory) computing: open MP constructs; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Interest rate theory. An in-depth analysis of interest-rate modelling and derivative pricing will be presented. Topics include: interest rate markets, discount bonds, the short rate, forward rates, swap rates, yields, the Vasicek model, the Hull-White model, the Heath-Jarrow-Merton formalism, the market model, bond option pricing in the Vasicek model, the positive interest framework, option and swaption pricing in the Flesaker-Hughston model.

Elective modules

0.Portfolio theory. The general theory of financial portfolio based on utility theory will be introduced in this module. Topics include: utility functions, risk aversion, the St Petersburg paradox, convex dual functions, dynamic asset pricing, expectation, forecast and valuation, portfolio optimisation under budget constraints, wealth consumption, growth versus income.


0.Information in finance with application to credit risk management. An innovative and intuitive approach to asset pricing, based on the modelling of the flow of information in financial markets, will be introduced in this module. Topics include: information-based asset pricing – a new paradigm for financial risk management; modelling frameworks for cash flows and market information; applications to credit risk modelling, defaultable discount bond dynamics, the pricing and hedging of credit-risky derivatives such as credit default swaps (CDS), asset dependencies and correlation modelling, and the origin of stochastic volatility.

0.Mathematical theory of dynamic asset pricing. Financial modelling and risk management involve not only the valuation and hedging of various assets and their positions, but also the problem of asset allocation. The traditional approach of risk-neutral valuation treats the problem of valuation and hedging, but is limited when it comes to understanding asset returns and the behaviour of asset prices in the real-world 'physical' probability measure. The pricing kernel approach, however, treats these different aspects of financial modelling in a unified and coherent manner. This module introduces in detail the techniques of pricing kernel methodologies, and its applications to interest-rete modelling, foreign exchange market, and inflation-linked products. Another application concerns the modelling of financial markets where prices admit jumps. In this case, the relation between risk, risk aversion, and return is obscured in traditional approaches, but is made clear in the pricing kernel method. The module also covers the introduction to the theory of Lévy processes for jumps and its applications to dynamic asset pricing in the modern setting.

0.Financial computing II: High performance computing. In this parallel-computing module students will learn how to harness the power of a multi-core computer and Open MP to speed up a task by running it in parallel. Topics include: shared and distributed memory concepts; Message Passing and introduction to MPI constructs; communications models, applications and pitfalls; open MP within MPI; introduction to Graphics Processors; GPU computing and the CUDA programming model; CUDA within MPI; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Risk measures, preference and portfolio choice. The idea of this module is to enable students to learn a variety of statistical techniques that will be useful in various practical applications in investment banks and hedge funds. Topics include: probability and statistical models, models for return distributions, financial time series, stationary processes, estimation of AR processes, portfolio regression, least square estimation, value-at-risk, coherent risk measures, GARCH models, non-parametric regression and splines.

Research project

Towards the end of the Spring Term, students will choose a topic to work on, which will lead to the preparation of an MSc dissertation. This can be thought of as a mini research project. The project supervisor will usually be a member of the financial mathematics group. In some cases the project may be overseen by an external supervisor based at a financial institution or another academic institution.

Read less
Programme structure. The programme offers five "core" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. Read more
Programme structure

The programme offers five "core" 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 core modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.

Core modules

Probability and stochastics. This course provides the basics of the probabilistic ideas and mathematical language needed to fully appreciate the modern mathematical theory of finance and its applications. Topics include: measurable spaces, sigma-algebras, filtrations, probability spaces, martingales, continuous-time stochastic processes, Poisson processes, Brownian motion, stochastic integration, Ito calculus, log-normal processes, stochastic differential equations, the Ornstein-Uhlenbeck process.

Financial markets. This course is designed to cover basic ideas about financial markets, including market terminology and conventions. Topics include: theory of interest, present value, future value, fixed-income securities, term structure of interest rates, elements of probability theory, mean-variance portfolio theory, the Markowitz model, capital asset pricing model (CAPM), portfolio performance, risk and utility, portfolio choice theorem, risk-neutral pricing, derivatives pricing theory, Cox-Ross-Rubinstein formula for option pricing.

Option pricing theory. The key ideas leading to the valuation of options and other important derivatives will be introduced. Topics include: risk-free asset, risky assets, single-period binomial model, option pricing on binomial trees, dynamical equations for price processes in continuous time, Radon-Nikodym process, equivalent martingale measures, Girsanov's theorem, change of measure, martingale representation theorem, self-financing strategy, market completeness, hedge portfolios, replication strategy, option pricing, Black-Scholes formula.


Interest rate theory. An in-depth analysis of interest-rate modelling and derivative pricing will be presented. Topics include: interest rate markets, discount bonds, the short rate, forward rates, swap rates, yields, the Vasicek model, the Hull-White model, the Heath-Jarrow-Merton formalism, the market model, bond option pricing in the Vasicek model, the positive interest framework, option and swaption pricing in the Flesaker-Hughston model.

Financial computing I. The idea of this course is to enable students to learn how the theory of pricing and hedging can be implemented numerically. Topics include: (i) The Unix/Linux environment, C/C++ programming: types, decisions, loops, functions, arrays, pointers, strings, files, dynamic memory, preprocessor; (ii) data structures: lists and trees; (iii) introduction to parallel (multi-core, shared memory) computing: open MP constructs; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.

Elective modules

Portfolio theory. The general theory of financial portfolio based on utility theory will be introduced in this module. Topics include: utility functions, risk aversion, the St Petersburg paradox, convex dual functions, dynamic asset pricing, expectation, forecast and valuation, portfolio optimisation under budget constraints, wealth consumption, growth versus income.

Information in finance with application to credit risk management. An innovative and intuitive approach to asset pricing, based on the modelling of the flow of information in financial markets, will be introduced in this module. Topics include: information-based asset pricing – a new paradigm for financial risk management; modelling frameworks for cash flows and market information; applications to credit risk modelling, defaultable discount bond dynamics, the pricing and hedging of credit-risky derivatives such as credit default swaps (CDS), asset dependencies and correlation modelling, and the origin of stochastic volatility.


Mathematical theory of dynamic asset pricing. Financial modelling and risk management involve not only the valuation and hedging of various assets and their positions, but also the problem of asset allocation. The traditional approach of risk-neutral valuation treats the problem of valuation and hedging, but is limited when it comes to understanding asset returns and the behaviour of asset prices in the real-world 'physical' probability measure. The pricing kernel approach, however, treats these different aspects of financial modelling in a unified and coherent manner. This module introduces in detail the techniques of pricing kernel methodologies, and its applications to interest-rete modelling, foreign exchange market, and inflation-linked products. Another application concerns the modelling of financial markets where prices admit jumps. In this case, the relation between risk, risk aversion, and return is obscured in traditional approaches, but is made clear in the pricing kernel method. The module also covers the introduction to the theory of Lévy processes for jumps and its applications to dynamic asset pricing in the modern setting.


Financial computing II: High performance computing. In this parallel-computing module students will learn how to harness the power of a multi-core computer and Open MP to speed up a task by running it in parallel. Topics include: shared and distributed memory concepts; Message Passing and introduction to MPI constructs; communications models, applications and pitfalls; open MP within MPI; introduction to Graphics Processors; GPU computing and the CUDA programming model; CUDA within MPI; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.

Risk measures, preference and portfolio choice. The idea of this module is to enable students to learn a variety of statistical techniques that will be useful in various practical applications in investment banks and hedge funds. Topics include: probability and statistical models, models for return distributions, financial time series, stationary processes, estimation of AR processes, portfolio regression, least square estimation, value-at-risk, coherent risk measures, GARCH models, non-parametric regression and splines.

Research project

Towards the end of the Spring Term, students will choose a topic for an individual research project, which will lead to the preparation and submission of an MSc dissertation. The project supervisor will usually be a member of the Brunel financial mathematics group. In some cases the project may be overseen by an external supervisor based at a financial institution or another academic institution.

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Do you have an aptitude and passion for mathematics and statistics, a keen interest in finance and insurance and want to work for a major financial organisation in finance, insurance or the money market? This course will provide you with a deep understanding of the world of finance, and give you the ability to speak its 'language'. Read more
Do you have an aptitude and passion for mathematics and statistics, a keen interest in finance and insurance and want to work for a major financial organisation in finance, insurance or the money market? This course will provide you with a deep understanding of the world of finance, and give you the ability to speak its 'language'. This course combines theory with hands-on practical skills via an industry placement or research project – ensuring you graduate with the right skills increasingly being sought by banks and other financial institutions.

The Master of Financial Mathematics offers advanced training in the core areas of stochastic, financial and insurance modelling, statistical analysis and computational methodology, as well as in a wide range of elective topics from economics, econometrics, finance, mathematics and probability.

Graduates of this course are likely to enter specialist careers in research departments within banks, insurance and consultancy firms or derivatives of valuation and portfolio management within investment houses.

The School of Mathematical Sciences sits within the leading Faculty of Science at Monash University. This vibrant, dynamic and successful School is undergoing a period of growth with the appointment of several new senior academic staff including Professor Gregoire Loeper, Course Director for the Masters of Financial Mathematics. With mathematics as the fundamental underpinning of so many subject areas, sectors and disciplines, the School is also building ever stronger collaborations with relevant industries, including the financial sector.

Visit the website http://www.study.monash/courses/find-a-course/2016/financial-mathematics-s6001?domestic=true

Course Structure

The course is structured in three Parts. Part A. Orientation studies, Part B. Specialist studies, Part C. Applied professional practice. All students complete Part B. Depending upon prior qualifications, you may receive credit for Part A or Part C or a combination of the two.

Part A. Orientation studies
These studies provide an orientation to the field of Financial Mathematics. You will choose studies that complement your current knowledge relevant to financial mathematics, including principles of econometrics, mathematical methods and stochastic processes.

Part B. Specialist studies
These studies will provide you with advanced knowledge and skills relevant to thoughtful, innovative and evidence-based practice in financial modelling and analysis. You will acquire core knowledge of and skills in financial econometrics, and advanced mathematical modelling and computational methods in finance. You will complement these with study in areas of your choice, including interest rate modelling, Markov processes, statistical learning in finance, and global financial markets.

Part C. Applied professional practice
These studies will provide you with the opportunity to apply your knowledge skills developed in Part A and B to "real life" problems, through completing an industry project or an industry internship. Students admitted to the course who have a recognised honours degree or graduate diploma or graduate certificate in a cognate discipline including mathematics or statistics, will receive credit for this part however, should they wish to complete a 24 point research project as part of Part B they should consult with the course convenor.

For more information visit the faculty website - http://www.study.monash/media/links/faculty-websites/science

About Mathematical Sciences

The School of Mathematical Sciences at Monash University is leading the way towards finding effective solutions to some of society's most pressing problems. Maths is the language of science and forms the basis of most of modern science and engineering. Our enthusiastic mathematicians love finding the true magic and beauty in maths and subsequently pass this passion on to their students.

Teaching

Studying maths equips you with a range of valuable, unique skills. Some of the exciting areas mathematicians at Monash are working on include mathematical modelling to predict behaviour, analysis using pure maths, and stochastic processes involving risk, randomness and change.

Mathematics and statistics are also the two cornerstones for decision making and various quantitative activities in commerce, industry, education and defence. From direct and daily experience, most companies and organisations have realised that success depends critically on the level of analytical, quantitative and statistical skills of their workforce and they therefore seek employees with a sound mathematical training.

By studying mathematics at Monash, you will also develop general skills in problem-solving, critical thinking, modelling, learning, analysis, research and creativity, which can be used wherever your career may take you.

Research

The School of Mathematical Sciences focuses on these main areas of research:

- Applied and Computational Mathematics
- Pure Mathematics
- Stochastic Processes

Find out how to apply here - http://www.study.monash/courses/find-a-course/2016/financial-mathematics-s6001?domestic=true#making-the-application

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Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. Read more
Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. What makes our Department different is the equally strong research in fluid mechanics, scientific computation and statistics.

The quality of research at the postgraduate level is reflected in the scholarly achievements of faculty members, many of whom are recognized as leading authorities in their fields. Research programs often involve collaboration with scholars at an international level, especially in the European, North American and Chinese universities. Renowned academics also take part in the Department's regular colloquia and seminars. The faculty comprises several groups: Pure Mathematics, Applied Mathematics, Probability and Statistics.

Mathematics permeates almost every discipline of science and technology. We believe our comprehensive approach enables inspiring interaction among different faculty members and helps generate new mathematical tools to meet the scientific and technological challenges facing our fast-changing world.

The MPhil program seeks to strengthen students' general background in mathematics and mathematical sciences, and to expose students to the environment and scope of mathematical research. Submission and successful defense of a thesis based on original research are required.

Research Foci

Algebra and Number Theory
The theory of Lie groups, Lie algebras and their representations play an important role in many of the recent development in mathematics and in the interaction of mathematics with physics. Our research includes representation theory of reductive groups, Kac-Moody algebras, quantum groups, and conformal field theory. Number theory has a long and distinguished history, and the concepts and problems relating to the theory have been instrumental in the foundation of a large part of mathematics. Number theory has flourished in recent years, as made evident by the proof of Fermat's Last Theorem. Our research specializes in automorphic forms.

Analysis and Differential Equations
The analysis of real and complex functions plays a fundamental role in mathematics. This is a classical yet still vibrant subject that has a wide range of applications. Differential equations are used to describe many scientific, engineering and economic problems. The theoretical and numerical study of such equations is crucial in understanding and solving problems. Our research areas include complex analysis, exponential asymptotics, functional analysis, nonlinear equations and dynamical systems, and integrable systems.

Geometry and Topology
Geometry and topology provide an essential language describing all kinds of structures in Nature. The subject has been vastly enriched by close interaction with other mathematical fields and with fields of science such as physics, astronomy and mechanics. The result has led to great advances in the subject, as highlighted by the proof of the Poincaré conjecture. Active research areas in the Department include algebraic geometry, differential geometry, low-dimensional topology, equivariant topology, combinatorial topology, and geometrical structures in mathematical physics.

Numerical Analysis
The focus is on the development of advance algorithms and efficient computational schemes. Current research areas include: parallel algorithms, heterogeneous network computing, graph theory, image processing, computational fluid dynamics, singular problems, adaptive grid method, rarefied flow simulations.

Applied Sciences
The applications of mathematics to interdisciplinary science areas include: material science, multiscale modeling, mutliphase flows, evolutionary genetics, environmental science, numerical weather prediction, ocean and coastal modeling, astrophysics and space science.

Probability and Statistics
Statistics, the science of collecting, analyzing, interpreting, and presenting data, is an essential tool in a wide variety of academic disciplines as well as for business, government, medicine and industry. Our research is conducted in four categories. Time Series and Dependent Data: inference from nonstationarity, nonlinearity, long-memory behavior, and continuous time models. Resampling Methodology: block bootstrap, bootstrap for censored data, and Edgeworth and saddle point approximations. Stochastic Processes and Stochastic Analysis: filtering, diffusion and Markov processes, and stochastic approximation and control. Survival Analysis: survival function and errors in variables for general linear models. Probability current research includes limit theory.

Financial Mathematics
This is one of the fastest growing research fields in applied mathematics. International banking and financial firms around the globe are hiring science PhDs who can use advanced analytical and numerical techniques to price financial derivatives and manage portfolio risks. The trend has been accelerating in recent years on numerous fronts, driven both by substantial theoretical advances as well as by a practical need in the industry to develop effective methods to price and hedge increasingly complex financial instruments. Current research areas include pricing models for exotic options, the development of pricing algorithms for complex financial derivatives, credit derivatives, risk management, stochastic analysis of interest rates and related models.

Facilities

The Department enjoys a range of up-to-date facilities and equipment for teaching and research purposes. It has two computer laboratories and a Math Support Center equipped with 100 desktop computers for undergraduate and postgraduate students. The Department also provides an electronic homework system and a storage cloud system to enhance teaching and learning.

To assist computations that require a large amount of processing power in the research area of scientific computation, a High Performance Computing (HPC) laboratory equipped with more than 200 high-speed workstations and servers has been set up. With advanced parallel computing technologies, these powerful computers are capable of delivering 17.2 TFLOPS processing power to solve computationally intensive problems in our innovative research projects. Such equipment helps our faculty and postgraduate students to stay at the forefront of their fields. Research projects in areas such as astrophysics, computational fluid dynamics, financial mathematics, mathematical modeling and simulation in materials science, molecular simulation, numerical ocean modeling, numerical weather prediction and numerical methods for micromagnetics simulations all benefit from our powerful computing facilities.

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This masters is run jointly with Heriot-Watt University. It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. Read more

Programme description

This masters is run jointly with Heriot-Watt University. 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 since the recent financial crisis.

Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Barrie & Hibbert and Lloyds Banking Group.

Programme structure

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

Compulsory courses:

Credit Risk Modelling
Derivatives Markets
Derivative Pricing and Financial Modelling
Discrete-Time Finance
Financial Markets
Special Topics 1
Special Topics 2
Stochastic Analysis in Finance

Option courses:

Deterministic Optimization Methods in Finance
Financial Econometrics
Portfolio Theory
Numerical Techniques of Partial Differential Equations
Optimization Methods in Finance
Simulation
Statistical Methods
Statistical Inference
Time Series Analysis
Stochastic Control and Dynamic Asset Allocation

Career opportunities

Graduates typically work in major financial institutions or continue their studies by joining PhD programmes.

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Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, law and marketing. Read more
Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences as well as in finance, law and marketing. New and exciting opportunities in industry, medicine, government, commerce or research await the graduate who has gained the quantitative skills training provided by this MSc.

Degree information

The programme uses a broad-based approach to statistics, providing up-to-date training in the major applications and an excellent balance between theory and application. It covers modern ideas in statistics including applied Bayesian methods, generalised linear modelling and object-oriented statistical computing, together with a grounding in traditional statistical theory and methods.

Students undertake modules to the value of 180 credits.

The programme consists of a foundation module, four core modules (60 credits) four optional modules (60 credits) and a research dissertation (60 credits).

Core modules
-Foundation Course (not credit bearing)
-Statistical Models and Data Analysis
-Statistical Design of Investigations
-Statistical Computing
-Applied Bayesian Methods

Optional modules
-Decision and Risk
-Stochastic Systems
-Forecasting
-Statistical Inference
-Medical Statistics I
-Medical Statistics II
-Stochastic Methods in Finance I
-Stochastic Methods in Finance II
-Factorial Experimentation
-Selected Topics in Statistics
-Bayesian Methods in Health Economics
-Quantitative Modelling of Operational Risk and Insurance Analytics

Dissertation/report
All MSc students undertake an independent research project, culminating in a dissertation of approximately 10,000–12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. External organisations deliver technical lectures and seminars where possible. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics e.g. the presentation of statistical graphs and tables.

Careers

Graduates typically enter professional employment across a broad range of industry sectors or pursue further academic study.

Top career destinations for this degree:
-Management Associate, HSBC
-Statistical Analyst, Nielsen
-PhD Statistics, University College London (UCL)
-Mortgage Specialist, Citibank
-Research Assistant Statistician, Cambridge Institute of Public Health

Employability
The Statistics MSc provides skills that are currently highly sought after. Graduates receive advanced training in methods and computational tools for data analysis that companies and research organisations value. For instance, the new directives and laws for risk assessments in the banking and insurance industries, as well as the healthcare sector, require statistical experts trained at graduate level. The large amount of data processing in various industries (known as "data deluge") also necessitates cutting-edge knowledge in statistics. As a result, our recent graduates have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

One of the strengths of UCL Statistical Science is the breadth of expertise on offer; the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science.

London provides an excellent environment in which to study statistical science, being the home of the Royal Statistical Society as well as a base for a large community of statisticians, both academic and non-academic.

The Statistics MSc has been accredited by the Royal Statistical Society. Graduates will automatically be granted the society's Graduate Statistician status on application.

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This programme provides an exciting opportunity to gain an insight into the pressing economic issues of our times and learn how to assess, adapt and apply modern macroeconomic and microeconomic models to shape organisational or government policy. Read more
This programme provides an exciting opportunity to gain an insight into the pressing economic issues of our times and learn how to assess, adapt and apply modern macroeconomic and microeconomic models to shape organisational or government policy.

Our programme is designed to equip you with the skills of a professional economist, for careers in government, international organisations and business.

You will learn to understand and model issues affecting financial markets through the lens of an economist, assessing both the microeconomic impacts for firms, as well as the macroeconomic implications for the global economy.

You will develop advanced theoretical and quantitative skills, highly sought after by employers in the financial services sectors of industry and government, as well as transferable skills that will be of value for a range of other sectors.

There is the opportunity to specialise in various fields of finance. All students register for the MSc in Economics and Finance. However, depending on the choice and availability of modules and dissertation topic, it is possible to graduate with an MSc in Financial Economics instead.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/economics-finance/

Programme modules

Semester 1:
Compulsory Modules
- Macroeconomics Analysis
- Microeconomics Analysis
- Research Communication (two-semester module)
- Research Methods

Optional Modules (choose one)
- Financial Economics
- Introduction to Measure Theory and Martingales
- Stochastic Models in Finance
- The Financial System

Semester 2:
Compulsory Modules
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two semester module)

Optional Modules (choose three)
- Applied Banking and Financial Modelling
- Asset Management and Derivatives
- Banking and Financial Markets
- Comparative Banking
- Corporate Finance
- Credit Risk Management
- Development Finance
- Economics and Energy Policy
- Stochastic Calculus and Theory of Stochastic Pricing

Choice of Semester 2 modules may be restricted by the option selected in Semester 1. The School reserves the right to vary the list of optional modules.

Summer:
- Dissertation

Assessment

75% examination and 25% coursework for most modules.

Careers and further study

Well-trained, numerate economists are in high demand in every sector. This programme prepares you for a career as a professional economist in banking, education, finance, government or industry, and for higher awards by research.

Example destinations include:
- HSBC – Analyst;
- SSR Group (Sweden) – Associate FX Broker;
- Siemens – Finance Officer.

Scholarships and sponsorships

School awards may be available for high-calibre national and international students.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/economics-finance/

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This programme is ideal for those who wish to pursue a career in the financial services sectors of industry or government, particularly banking and central banking. Read more
This programme is ideal for those who wish to pursue a career in the financial services sectors of industry or government, particularly banking and central banking.

Our modules are underpinned by the latest research and best practice, having been designed to equip you with up-to-date and relevant knowledge across a number of areas, including banking, finance and research methods.

The range of optional modules on the programme will enable you to specialise in areas of economics, banking and finance that best suit your career ambitions and interests.

Core study areas include financial economics, the financial system, research communication, research methods, asset management and derivatives, corporate finance, banking and financial markets, and further quantitative techniques.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/banking-finance/

Programme modules

Semester 1:
Compulsory modules
- Financial Economics
- Research Methods
- The Financial System
- Research Communication (two-semester module)

Optional modules (choose one):
- Introduction to Measure Theory and Martingales
- Macroeconomic Analysis
- Microeconomic Analysis
- Stochastic Models in Finance

Semester 2:
Core modules
- Asset Management and Derivatives and/or Corporate Finance
- Banking and Financial Markets
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two-semester module)

Optional modules (choose one):
- Applied Banking and Financial Modelling
- Comparative Banking
- Development Finance
- Stochastic Calculus and Theory of Stochastic Pricing

Summer period:
Students satisfy the research requirement by examined participation in research seminars. Subject to special conditions, students may submit a dissertation instead.

Assessment

Modules are assessed by a combination of examinations and assignments.

Careers and further study

Example destinations include:
- Bank of China – Senior Manager
- China Everbright Bank – Client Manager
- Deutsche Bank – Analyst
- KPMG – Audit Associate
- National Australia Bank – Senior Assistant in Research
- RBS – Financial Transfer Officer

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/banking-finance/

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Take advantage of one of our 100 Master’s Scholarships to study Mathematics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Mathematics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

As an MSc by Research in Mathematics student you will be guided by internationally leading researchers and will carry out a large individual research project.

You will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Key Features

Swansea is a research-led University and the Mathematics Department makes a significant contribution, meaning that as a postgraduate Mathematics student you will benefit from the knowledge and skills of internationally renowned academics.

In the Department of Mathematics at Swansea you will find friendly teaching staff that are fully committed to providing you with a supportive teaching and learning environment. This includes outstanding student support.

All postgraduate Mathematics programmes at Swansea will equip you with skills relevant for a rewarding career in a range of diverse fields. You will also further develop your communication, presentation and analytical skills.

The Mathematics 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, multifractal and multiscale 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

Employability

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.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use, and is a popular venue for students to work independently on the regular exercise sheets set by their lecturers, and to discuss mathematics together.

The main university library, the Learning and Information Centre (LIC), contains a notably extensive collection of mathematics books.

As part of our expansion, we are building the Computational Foundry on our Bay Campus for computer and mathematical sciences. This development is exciting news for Swansea Mathematics who are part of the vibrant and growing community of world-class research leaders drawn from computer and mathematical sciences.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Mathematics 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.

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This programme will help you develop professionally in the theory and practice of statistics and operational research (OR), providing the foundations for a successful career. Read more

Programme description

This programme will help you develop professionally in the theory and practice of statistics and operational research (OR), providing the foundations for a successful career.

This programme will prepare you for work in areas such as the medical and health industry, government, the financial sector and any other area where modern statistical tools and OR techniques are used. You will also develop the wider skills required for solving problems, working in teams and time management.

You will be able to identify appropriate statistical or operational techniques, which can be applied to practical problems, and will acquire extensive skills in modelling using the packages R for Statistics and Arena for simulation. In addition, you will acquire the ability to use high-level applications in Excel.

Programme structure

This MSc consists of lecture-based courses and practical, lab-based courses. You will be assessed by exams, written reports, programming assignments and a dissertation project.

Compulsory courses

Computing for Statistics
Fundamentals of Operational Research
Fundamentals of Optimization
Likelihood and Generalised Linear Models
Methodology, Modelling and Consulting Skills
Simulation
Statistical Regression Models
Statistical Theory
Stochastic Modelling

Option courses:

The Analysis of Survival Data
Categorical Data Analysis
Clinical Trials
Computing for Operational Research and Finance
Credit Scoring
Data Analysis
Genetic Epidemiology
Large Scale Optimization for Data Science
Machine Learning & Pattern Recognition
Multivariate Data Analysis
Nonparametric Regression
Operational Research in the Airline Industry
Operational Research in Telecommunications
Risk Analysis
Stochastic Models in Biology
Stochastic Optimization
Time Series Analysis and Forecasting

Career opportunities

This programme is ideal for students who wish to apply their statistics and operational research knowledge within a wide range of sectors including the medical and health sector, government and finance. The advanced problem-solving skills you will develop will be highly prized by many employers.

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 programme is especially suitable for students wishing to gain an in-depth understanding of the field of employment relations as preparation for a career in Employment Relations, Labour Relations or related fields. Read more
This programme is especially suitable for students wishing to gain an in-depth understanding of the field of employment relations as preparation for a career in Employment Relations, Labour Relations or related fields.

In addition to providing students with a thorough grounding in the theory and practice of Employment Relations it is anticipated that on completion of the programme students will also meet the knowledge requirements for chartered membership of the Chartered Institute for Personnel and Development (CIPD), the professional body for HR, Employment Relations and related professions in the UK.

Taught by academics with a strong track record in both Employment Relations related research and practical experience of Employment Relations and HRM, the programme focuses on developing critical thinking and analytical skills alongside of the more practical skills required for a career in Employment Relations and HR.

Core subjects include employment law, developing skills for business leadership, HRM theory and practice, employee engagement, motivation and voice, work design, organisational change and development, wellbeing and work, employment relations, strategic HRM, HRM research methods, and a dissertation.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/employmentrelationsandhrm/

Programme modules

Semester 1:
Compulsory Modules
- Financial Economics
- Research Methods
- Research Communication (two-semester module)
- The Financial System

Optional Modules:
- Economics of Money and Finance
- Macroeconomic Analysis
- Microeconomics Analysis
- Stochastic Models in Finance
- Introduction to Measure Theory and Martingales

Semester 2:
Compulsory Modules
- Asset Management and Derivatives, or Corporate Finance
- Banking and Financial Markets
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two-semester module)

Optional Modules (choose one)
- Applied Banking and Financial Modelling
- Comparative Banking
- Credit Risk Management
- Development Finance
- Stochastic Calculus and Theory of Stochastic Pricing

The School reserves the right to vary the list of optional modules.

Summer:
Students satisfy the research requirement by examined participation in research seminars. Subject to special conditions, students may submit a dissertation instead.

Careers and further study

Most large organisations in both the public and private sectors employ employment relations specialists. The grounding in Employment Relations and UK employment law, in addition to a grounding in more general HRM, that the programme provides also means graduates will be well equipped to bring expertise to both specialist Employment Relations and more general HR and management roles in both private and public sector organisations.

Scholarships and sponsorships

School awards may be available for high-calibre national and international students.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/employmentrelationsandhrm/

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