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Masters Degrees (Financial Mathematics)

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The MSc Financial Mathematics draws on tools from applied mathematics, computer science, statistics and economic theory to prepare you for roles in which you will combine in-depth knowledge of financial products and risk with sophisticated technical and programming skills. Read more
The MSc Financial Mathematics draws on tools from applied mathematics, computer science, statistics and economic theory to prepare you for roles in which you will combine in-depth knowledge of financial products and risk with sophisticated technical and programming skills.

You will acquire solid knowledge of probability theory and stochastic processes, numerical analysis and programming languages, asset pricing theory and risk analysis, with special emphasis on valuation and risk management.

Typical career paths of graduates from our MSc Financial Mathematics include research positions (in both financial and academic institutions), or roles involving the development, management and improvement of derivatives models using advanced programming languages, and model validation such as Equity/Equity Derivatives Quant, Quantitative Financial Engineer, or Quantitative Risk Analyst.

This programme is rigorous with respect to the mathematics but also places great emphasis on linking theory with real world developments. You will often be exposed to the teaching of real world practitioners from the City of London.

Cass's proximity to the City of London, and our close links to many of its institutions, will help you to access outstanding networking and career opportunities.

Visit the website: http://www.cass.city.ac.uk/courses/masters/courses/financial-mathematics

Course detail

There are 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.

Attendance is mandatory.

Format

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

• eight core courses (15 credits each)
and
• two additional core modules plus three electives (10 credits each)
or
• three electives (10 credits each) and an Applied Research Project (20 credits)
or
• one elective (10 credits) and a Business Research Project (40 credits)

Assessment

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.

Career opportunities

Many graduates from the MSc in Financial Mathematics progress to one of two fields:

• derivatives valuation and portfolio management within investment houses
• research departments within banks and consultancy firms

Some examples of where graduates from the MSc in Financial Mathematics class of 2014 are working are:

• Bank of China - Management Trainee
• Santander - Credit Fraud Analyst
• Renaissance Re - Analyst
• Deutsche Bank - Bookrunner

How to apply

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

Funding

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

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

Key benefits

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

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

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

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

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

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

Course detail

- Description -

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

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

- Course purpose -

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

- Course format and assessment -

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

Career prospects

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

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

About Postgraduate Study at King’s College London:

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

Scholarships & Funding:

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

Free language tuition with the Modern Language Centre:

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

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This 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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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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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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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. Read more

About the MSc programme

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

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

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

Graduate destinations

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

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The Certificate in Financial Mathematics (CT1) is one of nine Core Technical subjects offered by the Institute and Faculty of Actuaries, providing a basic grounding in financial mathematics and its simple applications. Read more
The Certificate in Financial Mathematics (CT1) is one of nine Core Technical subjects offered by the Institute and Faculty of Actuaries, providing a basic grounding in financial mathematics and its simple applications

This course is taught by distance learning, using materials and technology already used on our MSc/PGCert in Actuarial Science. It can be taken as a stand-alone course or as a ‘taster’ for the degree. The course tuition will prepare you for the IFoA exam which can be sat in April or September.

You will receive:
•Access to the e-book of the industry-standard text for CT1, 'An Introduction to Mathematics of Finance: A Deterministic Approach' by Professor Stephen Garrett.
•This covers all material with worked examples
•Access to the University's virtual learning environment, Blackboard
•Electronic forums and podcasts used to support your learning
•Email access to Professor Stephen Garrett who will respond to your questions within 48 hours
•Regular assignments with full marking and feedback
•A mock examination with full marking and feedback
•Access to the University's extensive digital library

You may also attend an intensive one-day tutorial held shortly before the exam, on the University's main campus, for which there will be an additional cost of £120

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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

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, Moody’s Analytics 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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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.

Degree information

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 a 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.

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.

Top career destinations for this degree:
-University Teacher, Chechen State University
-Operational Permanent Control Analyst, BNP Paribas
-UK Education Consultant, SI-UK Education Council
-CFA (Chartered Financial Analyst), Quartic Training
-MSc Financial Mathematics, University College London (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.

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.

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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

https://www.abdn.ac.uk/study/postgraduate-taught/degree-programmes/920/financial-mathematics/

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:

https://www.abdn.ac.uk/study/international/tuition-fees-and-living-costs-287.php

*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

https://www.abdn.ac.uk/study/postgraduate-taught/finance-funding-1599.php

https://www.abdn.ac.uk/funding/

Living in Aberdeen

Find out more about:

  • Your Accommodation
  • Campus Facilities
  • Aberdeen City
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Find out more about living in Aberdeen:

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Living costs

https://www.abdn.ac.uk/study/international/finance.php



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

Course Details

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

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

Lectures & classes

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

Lab work

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

Your dissertation

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

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* Ranked within the UK top 10 Business Schools according to The Times and The Sunday Times Good University Guide 2015 and The Complete University Guide 2016. Read more
* Ranked within the UK top 10 Business Schools according to The Times and The Sunday Times Good University Guide 2015 and The Complete University Guide 2016

* EQUIS accredited placing us in the top 1% of business schools globally

* Connections with an extensive and diverse range of businesses including Canon, Thomson Reuters, Lloyds Banking Group, IBM, Coca Cola and the Met Office

* Our teaching is research-led – you will study with internationally respected academics who are experts in their fields
We have partnerships with over 40 overseas universities or business schools and this figure is growing all the time

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 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.

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. 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.

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 and Advanced Mathematics Project.

Optional modules

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

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