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Masters Degrees (Financial Mathematics)

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This programme is now closed but you may want to consider other courses such as the . Mathematics MSc. . . Read more

This programme is now closed but you may want to consider other courses such as the Mathematics MSc

The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.

  • A rigorous approach to quantitative finance taught entirely by the Department of Mathematics.
  • In-depth coverage of the skills needed for working in the financial, actuarial or related industry: probability theory, optimisation, statistics and computer implementation.
  • Unrivalled facilities in central London with City of London's financial centre close by, and with access to live market data in our Bloomberg Data Laboratory.
  • Flexible study programme offering the opportunity to study part-time.
  • King’s is a member of the London Graduate School in Mathematical Finance which provides advanced courses for students who wish to push beyond the MSc core syllabus.
  • Lecturers on the programme have extensive experience in consulting and work for financial companies and institutions such as Bank of Finland, Commerzbank, Deutsche Bank, Goldman Sachs, ION Trading, Standard Chartered Bank and Winton Capital Management.

Description

Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management

Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.

Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.

The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.

Bloomberg terminal laboratory

King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.

You will use the Bloomberg terminals to:

  • Gain an intuition for the conduct of real financial markets
  • Develop potential investment strategies
  • Experience using real-world investment and risk management software and obtain data for research.

The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.

We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.

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

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Average per week: Three hours for 11 weeks per each 15 credit module.

You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.  

Career destinations

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.

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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. Read more

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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Who is it for?. To successfully complete this course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate. Read more

Who is it for?

To successfully complete this course, you must have a very good understanding of mathematics. You may well have studied maths, physics or engineering degrees as an undergraduate.

Or you might have a bachelor’s degree in economics or science and in particular computer science, which, coupled with your interest in stochastics, could also qualify you for this programme.

You should have a general interest in learning the more technical and mathematical techniques used in financial markets; but you don’t need to have a background in finance.

Objectives

The MSc Financial Mathematics focuses on stochastics and simulation techniques, but also covers some econometrics. You’ll study core modules covering asset pricing, risk management and an introduction to key financial securities such as equities, fixed income and derivatives.

You’ll cover a wide range of elementary and advanced topics in stochastics, including Levy processes and different simulation techniques. You’ll be taught Matlab and VBA and you have the opportunity to learn other programming languages as part of our electives offering, such as Python or C++.

There are three ways to complete the third term. Either you’ll choose five electives from around 40 optional modules in your final term. Or you can choose to complete a traditional dissertation, known as a ‘business research project’, which counts for four electives, or a shorter ‘applied research project’, which is the equivalent of two elective modules.

Structure

  • You will have gained a very good understanding of the technical aspects used in financial markets, including wide ranging financial theory and different financial assets.
  • You will gain a good understanding of stochastic and mathematical finance and gained some knowledge of econometrics and forecasting. You will also have obtained a good understanding of programming, in particular Matlab.
  • From the MSc Financial Mathematics you will also understand how the theory is being applied in the financial industry and what practical issues are.
  • In the third term you have three different options how you can complete your MSc, including a project or choosing only electives. Popular electives include Modelling and Data Analysis, Advanced Financial Engineering and Credit Derivatives, Credit Risk Management, Quantitative Risk Management. Introduction to Python.

Assessment

We review all our courses regularly to keep them up-to-date on issues of both theory and practice.

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

  • nine core courses (Eight at 15 credits each, one at 10 credits)

and either

  • five electives (10 credits each)
  • three electives (10 credits each) and an Applied Research Project (20 credits)
  • one elective (10 credits) and a Business Research Project (40 credits)

Assessment of modules on the MSc in Financial Mathematics, 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.

Two Induction Weeks

The Financial Mathematics course starts with two compulsory induction weeks, focused on:

  • an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.
  • a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1.

Career pathways

The job opportunities for students from the three quants Masters programmes are very similar and students usually find employment with either large investment banks, or smaller specialist companies or financial boutique firms. Working as a quantitative analysts using stochastic, technical risk management position, pricing fixed income securities and structuring are some of the positions Financial Mathematics students are well qualified for. You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.



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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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This Masters degree provides you with knowledge of advanced finance concepts, whilst developing your quantitative, mathematical and research skills. Read more

This Masters degree provides you with knowledge of advanced finance concepts, whilst developing your quantitative, mathematical and research skills.

Taught by experienced academics based in both Leeds University Business School and the School of Mathematics, you’ll cover key topics including financial derivative pricing, discrete and continuous time models, risk management and portfolio optimisation, as well as statistical methods for finance.

You will be equipped with a rare combination of mathematical skills and the latest business finance knowledge, which is highly sought after in the financial sector by banks, investment and consultancy companies. It’s also excellent preparation if you’re interested in pursuing further academic research.

This course is ideal if you’ve previously studied finance, economics, mathematics, physics or computing, and are interested in applying your skills to financial markets.

Academic excellence

As a student, you will be able to access the knowledge of our advanced specialist research units, which also have strong links with leading institutions in the US, Europe and Asia. These include the Centre for Advanced Study in Finance (CASIF), the Institute of Banking and Investment (IBI) and the Credit Management Research Centre (CMRC).

This research makes an important contribution to your learning on the MSc Financial Mathematics; you will benefit from a curriculum that is informed by the latest knowledge and critical thinking.

You will also benefit from our strong relationships with the finance, credit and accounting professions. This provides a connection to the latest practitioner and policy developments, giving you a masters degree that is relevant to the contemporary environment.

Course content

In your first semester you’ll develop a broad understanding of corporate finance and how financial theory relates to practice in business and financial markets. This will put your mathematical studies into context while you develop your skills in applied statistics and probability, optimisation methods and discrete time finance.

You’ll build on these skills in topics such as continuous time finance, risk management and computational methods. You’ll also gain specialist knowledge in topics that suit your career ambitions such as risk and insurance, actuarial science and behavioural finance.

The programme will improve your research skills and allow you to study different research methodologies, including those employed by our own leading academics. This will prepare you for your dissertation – an independent research project on a topic of your choice that you’ll submit by the end of the year.

Course structure

Compulsory modules

  • Corporate Finance 15 credits
  • Dissertation in Financial Mathematics 30 credits
  • Applied Statistics and Probability 15 credits
  • Discrete Time Finance 15 credits
  • Continuous Time Finance 15 credits
  • Risk Management 15 credits
  • Computations in Finance 15 credits
  • Optimisation Methods for Finance 15 credits

Optional modules

You'll also take two optional modules.

  • Security Investment Analysis 15 credits
  • Portfolio Risk Management 15 credits
  • Behavioural Finance 15 credits
  • Financial Derivatives 15 credits
  • International Investment 15 credits
  • Models in Actuarial Science 15 credits

For more information on typical modules, read Financial Mathematics MSc in the course catalogue

Learning and teaching

We use a variety of teaching and learning methods to help you make the most of your studies. These will include lectures, seminars, workshops, online learning and tutorials. Independent study is also vital for this course allowing you to prepare for taught classes and sharpen your own research and critical skills.

In addition to the assessed modules and research dissertation, you benefit from professional training activities and employability workshops. Thanks to our links with major companies across the business world, you can also gain a practical understanding of key issues.

Recent activities have included CV building and interview sessions, professional risk management workshops and commercial awareness events. For example, students have developed their knowledge of financial markets through a one-week trading simulation. Read more about professional development activities for postgraduate finance students.

Assessment

Assessment methods emphasise not just knowledge, but essential skills development too. They include formal exams, group projects, reports, computer simulation exercises, essays and written assignments, group and individual presentations.

This diversity enables you to develop a broad range of skills as preparation for professional life.

Career opportunities

You have various opportunities open to you as a Financial Mathematics graduate, including: quantitative analysis, risk management, investment banking, financial consultancy, insurance, accounting and academia.

Previous graduates have gone on to secure employment with Allianz (London), AstraZeneca, Barclays, Cathay Life Insurance, CITIC Group, Commerzbank, Deloitte, First Direct, Gaz de France, HSBC, KPMG, Moody’s, PricewaterhouseCoopers, Royal Bank of Scotland, RSA and UK Government Actuary’s Department.

Careers support

We help you to achieve your career ambitions by providing professional development support and training as part of the course. You benefit from the support of a professional development tutor, who will work with you to develop the important professional skills that employers value.

Read more about our careers and professional development support.

The University of Leeds Careers Centre also provides a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website



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This programme provides you with advanced analytical training, quantitative knowledge and the practical skill sets required by modern financial institutions. Read more
This programme provides you with advanced analytical training, quantitative knowledge and the practical skill sets required by modern financial institutions. It aims to equip you with a solid education in financial analysis, risk management and financial engineering for a successful career in the finance and banking industries. It is heavily maths/quant weighted with advanced maths modules and programming modules designed with practical applications in mathematical/quant finance.

The programme will equip you with:
• intellectual skills and theoretical understandings appropriate for the study of financial mathematics and quantitative analysis at postgraduate level
• practical mathematics and object-oriented programming skills linking finance theories to real-world application
• skills in research, evaluation and analysis and the quantitative techniques to evaluate and interpret complex data and research literature
• skills and abilities to devise, plan and undertake complex research projects in the field of financial mathematics

Core Modules

• Advanced Modelling Methods in Finance
• Advanced Financial Econometrics
• Computational Methods in Finance
• Continuous Time Finance
• Advanced Statistics
• Stochastic Calculus
• Dissertation

Elective Modules

• Microeconomics for Financial Mathematics
• Quantitative Methods
• Numerical Computation in Finance
• Advanced Risk Management

What are my career prospects?

A graduate degree in financial mathematics gives you many employment opportunities in the business world such as in banks, investment firms, insurance companies, consulting services to financial industries, government regulators, business entities, and teaching and research at universities or research institution, and government entities.

NOTE: ICAEW ACCREDITATION IS STILL OUTSTANDING. APPLICATION IN PROGRESS.

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The financial services industry place great emphasis on raising the level of mathematics used in banks in applications to pricing, hedging and risk management. Read more

The financial services industry place great emphasis on raising the level of mathematics used in banks in applications to pricing, hedging and risk management. This MSc provides students with the skills necessary in mathematics, statistics and computation for a career in this fast-developing field.

About this degree

Students will develop a detailed understanding of the application of mathematics, statistics and computation to problems in finance, and will gain the necessary practical tools for the pricing, hedging and risk management of a diverse range of financial products in several asset classes.

Students undertake modules to the value of 180 credits.

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

A Postgraduate Diploma will be offered to the students that have completed 8 taught modules (120 UCL credits).

A Postgraduate Certificate will be offered to the students that have completed 4 taught modules (60 UCL credits).

Core modules

  • Asset Pricing in Continuous Time
  • Forecasting
  • Interest Rates and Credit Modelling
  • Quantitative and Computational Finance

Optional modules

Four modules must be chosen from the following list.

  • Applied Computational Finance
  • Equities, Foreign Exchange and Commodities Modelling
  • Market Risk, Measures and Portfolio Theory
  • Mathematics and Statistics of Algorithmic Trading
  • Numerical Analysis for Finance
  • Probability
  • Statistical Inference
  • Stochastic Processes
  • Quantitative Modelling of Operational Risk and Insurance Analytics

Dissertation/report

All MSc students undertake an independent research project, which culminates in a research report of approximately 10,000 words.

Teaching and learning

The programme is delivered through a combination of lectures, practical classes, tutorials and problem-solving exercises. Assessment is through written papers, coursework, examinations and the research report and presentation.

Further information on modules and degree structure is available on the department website: Financial Mathematics MSc

Careers

Many students have progressed to careers in financial services in the City of London or in their home country; a number of graduates have proceeded to a PhD.

Recent career destinations for this degree

  • Structurer, BNP Paribas
  • PhD in Mathematics, University College London (UCL)
  • University Teacher, Chechen State University
  • CFA (Chartered Financial Analyst), Quartic Training
  • MSc Financial Mathematics, UCL

Employability

The financial services industry requires quantitative finance professionals who are able to analyse data, to program, and who are expert in mathematics and computational statistics. Career prospects for graduates of this programme are excellent.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Mathematics is an internationally renowned department which carries out excellent individual and group research applying modelling techniques to problems in financial, industrial, biological and environmental areas.

The department hosts a stream of distinguished international visitors. In recent years four staff members have been elected fellows of the Royal Society, and the department publishes the highly regarded research journal Mathematika.

A notable aspect of this applied Master's programme is that students will be educated to an advanced level in statistics and computing.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Mathematics

82% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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A combination of mathematics, statistics and computing, financial mathematics is a specialism vital to the day-to-day functioning of the world's economic institutions. Read more
A combination of mathematics, statistics and computing, financial mathematics is a specialism vital to the day-to-day functioning of the world's economic institutions. Highly technical and theoretical aspects of mathematics take on a practical importance which can affect millions of lives through this fascinating discipline, which involves predicting the behaviour of markets and suggesting strategies for investment.


Why study MSc Financial Mathematics at Middlesex?

We believe strongly that the work you do must be relevant to the world of work – that's why our course has a strong practical slant. It also has the unusual and significant advantage of including from-scratch training in computer programming, allowing you to develop first-class computing skills alongside your mathematical expertise.You'll need a good degree in maths, or a related subject like physics or engineering, but no prior knowledge of finance.

Course highlights

Our course combines a comprehensive grounding in the theory of financial mathematics with thorough practical training
Our subscriptions to Bloomberg and Datastream allow you to work with real datasets
We'll teach you to code in widely-used languages such as C++, Java and Python, without the need for prior experience
Guest lectures from industry specialists allow you to gain insights from practising professionals into real-life situations
The course is designed either for graduates considering a financial career, or for those already working in the industry looking for a greater understanding of finance and insurance risk

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About the MSc programme. 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. Read more

About the MSc programme

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 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 aims to develop your understanding of quantitative methodologies and techniques that 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.

Further information on graduate destinations for this programme



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Your programme of study. Many organisations particularly in the financial sector require quite complex financial transactions to be completed within their systems and databases internally and externally in order to provide the most up to date financial information to customers. Read more

Your programme of study

Many organisations particularly in the financial sector require quite complex financial transactions to be completed within their systems and databases internally and externally in order to provide the most up to date financial information to customers. Other organisations particularly within trading and investment areas, currencies and international organisations rely on modelling and scenarios to ensure their business models survive change. There are a lot of businesses and applications that require somebody with Financial Mathematics to set up systems which allow internal and external customers to see exact information whilst calculations go on behind the scenes. The insurance, pensions and domestic energy industries are good examples of business which requires a specific ability to provide advanced methods of calculation.

The programme gives you a rigorous method of acquiring vital skills which financial industries are looking for. You learn financial programme and work with big data sets used in the above industries, banking and many other industries. There is also a new industry which relies on these skills to programme IOT applications and devices which are used to similarly calculate within financial and statistical markets.

Courses listed for the programme

Semester 1

  • Discrete Time Modules
  • Economics Theory for Finance
  • Economics Theory and Data Analysis for Finance
  • Mathematics for Finance

Semester 2

  • Continuous Time Models
  • Time Series

Semester 3

  • Dissertation

Find out more detail by visiting the programme web page

Why study at Aberdeen?

  • You get access to Thomson Reuters Eikon trading floor to integrate study with real time trading
  • We are supported by strong research collaborations with the Institute of Pure and Applied Mathematics
  • You are also supported by our Business School
  • Skills which are essential to financial economists in private and public sector are taught to develop rigour and confidence

Where you study

  • University of Aberdeen
  • Full time

International Student Fees 2017/2018

Find out about fees:

  • International
  • Scotland and EU
  • Other UK

Find out more from the programme page

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page and the latest postgraduate opportunities

Living in Aberdeen

Find out more about:

Your Accommodation

Campus Facilities

Find out more about living in Aberdeen and living costs



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The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. Read more

The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. With the growth and progression of business across the globe, the need for those who can understand quantitative financial methods are becoming increasingly lucrative, sought-after individuals. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting and expanding field.To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with our internationally respected Mathematics department, this comprehensive MSc programme will prepare you for careers in areas that require expert skills in mathematical and financial modelling, computational analysis and business management.

You will gain essential, complementary skills in multiple areas of study such as probability and stochastic analysis, option pricing, risk analysis and extremes, computational methods using MATLAB/C++, financial management and investment analysis. In addition, you will branch into a specialist area of study as you conduct a substantial project in a field of your choosing. The project will allow you to develop your research, computational and modelling skills with support from staff who have extensive experience working in multiple financial services and insurance industries.

Careers

The programme prepares you for a career in financial modelling within financial institutions themselves and within other sectors. It builds upon the success of Exeter’s well-established range of Masters programmes in Finance and related areas, many of whose graduates now hold senior positions in areas such as corporate financial strategy, financial planning, treasury and risk management and international portfolio management.

With the strong links between the College and the Met Office, the course also prepares you for career opportunities within reinsurance and credit risk management, especially in the development of financial models that rely on weather/climate systems.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

Recent examples of compulsory modules are as follows; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology; Advanced Mathematics Project.

Optional modules

Some recent examples are as follows; Topics in Financial Economics; Investment Analysis 1; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis II; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++; Level 3 Mathematics Modules.



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This MSc programme is run by Heriot-Watt University jointly with The University of Edinburgh. Upon graduation, you will receive a degree certificate bearing crests of both universities. Read more

This MSc programme is run by Heriot-Watt University jointly with The University of Edinburgh. Upon graduation, you will receive a degree certificate bearing crests of both universities.

It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. You will also learn quantitative skills for developing and managing risk that are in high demand.

Programme structure

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

The teaching is shared between Heriot-Watt University (HW) and The University of Edinburgh (UoE). The timetable is arranged so that you spend three days a week at the Heriot-Watt Riccarton Campus and two days a week at University of Edinburgh’s King’s Buildings Campus.

The dissertation project is either carried out with an industrial partner (e.g. Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group) or supervised by academics at Heriot-Watt University. The programme typically involves the following courses.

Compulsory courses:

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

Option courses:

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

Work placements/internships

Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group.

Career opportunities

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



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Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. Read more

Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. The solution by Black, Scholes and Merton of the option pricing problem set off a revolution in finance resulting in the introduction of sophisticated mathematical techniques in the financial markets and corporate planning.

To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with expertise in the Mathematical Research Institute of the Mathematics Department at the University, this intensive MSc programme, available over 9 or 12 months, will prepare you for careers in areas such as international banking or international business. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting field.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

The compulsory modules can include;

  • Methods for Stochastics and Finance;
  • Analysis and Computation for Finance;
  • Mathematical Theory of Option Pricing;
  • Fundamentals of Financial Management;
  • Research Methodology and Advanced Mathematics Project;

Optional modules

Some examples of the optional modules are as follows;

  • Topics in Financial Economics;
  • Investment Analysis;
  • Banking and Financial Services;
  • Derivatives Pricing;
  • Domestic and International Portfolio Management;
  • Investment Analysis;
  • Financial Modelling;
  • Advanced Corporate Finance;
  • Alternative Investments;
  • Quantitative and Research Techniques;
  • Advanced Econometrics;
  • Dynamical Systems and Chaos;
  • Pattern Recognition;
  • Introduction to C++
  • Level 3 Mathematics Modules.

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

Learning and teaching

Teaching is by lectures, example classes, computer classes, tutorials, set work, project work, reading and self-study. The exact form and number of the lectures and tutorials varies from module to module and is chosen according to the material to be covered.

You will use the computer programming language Matlab and online financial databases such as Bloomberg and Datastream.



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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. Read more
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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This masters programme covers the advanced mathematics that has revolutionised finance since the works of Black, Scholes and Merton in the early seventies. Read more
This masters programme covers the advanced mathematics that has revolutionised finance since the works of Black, Scholes and Merton in the early seventies. This programme is aimed at those students who are passionate about mathematics and driven to make a career amongst the many and varied financial institutions throughout the world.

The programme, which is part of the Maxwell Institute for Mathematical Sciences, the joint research institute of mathematical sciences at the University of Edinburgh and Heriot-Watt University, provides an intensive training in the mathematical ideas and tools vital to the finance industry. By developing essential new mathematical concepts, especially in stochastic calculus, and placing the mathematics in the contexts of financial markets, derivative pricing and credit risk, the programme equips students for a range of exciting and potentially lucrative career opportunities.

The programme is delivered jointly between Heriot-Watt University and the University of Edinburgh. This means you will be enrolled as a student at both univerities and benefit from access to all the services and facilities each university has to offer.

Teaching is delivered by renowned academics from both Heriot-Watt and the University of Edinburgh - some classes will therefore take place at Heriot-Watt's campus and others at the University of Edinburgh campus. Successful students will graduate with a degree awarded jointly by Heriot-Watt and the University of Edinburgh and both names will appear on the graduation certificate.

Programme content

Core courses

Derivatives Markets
Derivative Pricing and Financial Modelling
Financial Markets
Discrete-Time Finance
Stochastic Analysis in finance
Credit Risk Modelling
Special Topics, including industry lead projects

Options

Statistical Methods
Financial Econometrics
Time Series Analysis
Modern Portfolio Theory
Optimisation Methods in Finance
Numerical Methods for PDEs
Simulation in Finance
Deterministic Optimisation Methods in Finance

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