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Masters Degrees (Financial Computing)

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This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more

This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

  • Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.
  • You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.
  • You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.
  • We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Programme Outline

The study programme consists of four compulsory and four elective modules. The modules offered by the School of Mathematical Sciences will provide a solid understanding of the principles of mathematical finance. The modules offered within the Schools of Electronic Engineering and Computer Sciences will focus on key aspects of technological implementation.

Full time Study

You will study eight modules in total with an even split across semesters one and two. You will complete a 10,000 word dissertation/research project during semester three.

Full time Study with Industrial Experience

You will study eight modules in total with an even split across semesters one and two. You will complete a 10,000 word dissertation/research project during semester three. Expert staff will support the arrangement of your industrial placement, which will be carried out in the second year of your programme and assessed through the completion of the Industrial Placement Project.

The industrial placement takes place from the September following the taught part of the MSc and is for a maximum of 12 months. It is a student's responsibility to secure their own placement, but the EECS Placement Team will provide support. The Placement Team source and promote suitable opportunities, assist with applications, and with interview preparation.

The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed and passed the taught component of the degree and submitted your MSc project. The placement will provide you with the opportunity to apply the key technical knowledge and skills that you have learnt in your taught modules, and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.

In the event that you are unable to secure a placement we will transfer you onto the 1 year FT taught programme without the Industrial Experience. This change will also apply to any student visa you hold at the time.

Part time Study

Your programme is delivered across two academic years. You will study four modules in each year of the programme, registering upon two modules per semester to balance your workload.

Our modules are assessed by a mixture of in-term assessment and final examinations. Examinations are held between late April and early June. Dissertations are evaluated in September. Successful completion of the MSc programme will result in the award of the MSc Financial Computing (possibly with Merit or with Distinction).

Structure

Semester 1 - Compulsory

  • ECS793P Introduction to Object-Oriented Programming
  • MTH771P Foundations of Mathematical Modelling in Finance
  • MTH739N Topics in Scientific Computing

Semester 1 - Elective

  • ECS765P Functional Programming
  • ECS765P Big Data Processing
  • ECS708P Machine Learning

Semester 2 - Compulsory

  • MTH777P Financial Programming

Semester 2 - Elective

  • MTH773P Advanced Computing in Finance
  • ECS769P Advanced Object-Oriented Programming
  • ECS786P Parallel Computing
  • MTH774P Portfolio Theory and Risk Management
  • MTH772P Stochastic Calculus and Black Scholes Theory

The Project

Each MSc Financial Computing student is required to complete a 60 credit project dissertation. A typical MSc project dissertation consists of about 30 word-processed pages (10,000 words), securely bound, covering a specific research-level topic in financial computing, usually requiring the student to understand, explain and elaborate on results from one or more journal articles and possibly to implement some industry quality code.

Detailed outlines of each module for MSc Financial Computing are on Queen Mary University of London website.



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Why Study Financial Computing?. Financial institutions are under considerable pressure to increase their computational capabilities. Read more
Why Study Financial Computing?
Financial institutions are under considerable pressure to increase their computational capabilities. This is the result of increased regulatory requirements, new electronic and algorithmic trading channels as well as increased competition for speed and accuracy. This critical capability is delivered by a combination of mathematics, technology and finance.

As a result there is growing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

This unique programme provides numerate graduates with the expertise to develop a professional career in this profitable and intellectually exciting field. It has been designed to match the requirements of top employers in the industry.

Access to Expertise
The MSc in Financial Computing is directed and has been designed by Dr Sebastian del Bano Rollin former Global Head of FX Quantitative Research at Citigroup amongst other senior roles in the financial industry.

Get Industry Experience
The Financial Computing MSc can be enhanced with a one year industry placement that will allow you to gain valuable industry expertise.

Our Scholarships
We reward your academic excellence with scholarships for our MSc Financial Computing. This year we will be awarding five tuition fee scholarships of £5,000 each for outstanding graduates with degrees equivalent to a 2:1 or above.

The Programme
The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed both at science graduates with some experience in programming as well as engineering graduates with some mathematical exposure. The content of the programme is a combination of technology and applied financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance computing and GPU development. If you are studying full time with us, you will complete eight taught modules as well as completing a 10,000 word dissertation over the academic year. To view further information about the content and structure of our programme visit: http://www.qmul.ac.uk/postgraduate/taught/coursefinder/courses/155455.html

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The rigorous training on our MSc Financial Computing focuses on software engineering for large, dynamic and automated financial systems and finance models. Read more
The rigorous training on our MSc Financial Computing focuses on software engineering for large, dynamic and automated financial systems and finance models. This, alongside work on software design in a number of real-world financial systems, will enable you to become a leader in this field.

This course should interest you if you have a good first degree in computer science or engineering, or a BSc degree that provided a high level of programming expertise such as C++ and/or .NET. You receive training on the structure, instruments and institutional aspects of financial markets, banking, payment and settlement systems.

You will attain a high level of competence in software development, in the area of financial computing, for implementation in an electronic market environment, as we introduce you to information and communication technology and automation that underpins financial systems, including:
-Design issues relating to parallel and distributed networks
-Encryption, security and real-time constraints
-Straight Through Processing (STP)
-Quantitative finance
-Financial software architecture

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Big-Data for Computational Finance
-Cloud Technologies and Systems
-High Performance Computing
-Introduction to Financial Market Analysis
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Computer Security (optional)
-Constraint Satisfaction for Decision Making (optional)
-Creating and Growing a New Business Venture (optional)
-Digital Signal Processing (optional)
-E-Commerce Programming (optional)
-Financial Engineering and Risk Management (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-IP Networking and Applications (optional)
-Learning and Computational Intelligence in Economics and Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Mobile & Social Application Programming (optional)
-Programming in Python (optional)
-Industry Expert Lectures in Finance (optional)

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With the rapid advancement of computing technology, there is an increasing demand in the dynamic and challenging environment of financial services for a variety of technological talent to deliver business solutions on a global scale. Read more
With the rapid advancement of computing technology, there is an increasing demand in the dynamic and challenging environment of financial services for a variety of technological talent to deliver business solutions on a global scale. This programme addresses this demand and will train you for advanced technical or managerial roles in new interdisciplinary areas of computational techniques and equip you with financial knowledge to deliver effective business solutions. You will gain:
• theoretical and practical knowledge of key areas of finance and computing in today’s industry and research
• knowledge of the latest technology and applications for the finance industry, such as big data and business analytics
• practical skills in research, analysis, realisation and evaluation of the technical or research documents in financial computing

You will undertake eight modules in the first two semesters and a dissertation project in the third semester for a total duration of 18 months. You will choose these modules based on the subject area of your first degree, such as computing, finance or other fields. The precise content of your dissertation project will be discussed and decided with your project supervisor and is subject to approval. The department is equipped with specialist lab facilities for operating systems, networking, mobile computing and multimedia technology that will support your learning and research.

Students on this programme will study a selection of the following subjects, the actual range depending on their undergraduate programme:
-Research Methods
-Object-Oriented Programming
-Cloud Computing
-Interactive Systems
-Artificial Intelligence
-Data Mining and Data Analytics
-Databases and Data Management
-Data Mining and Machine Learnin
-Software Architecture
-Computer Systems Security
-Accounting and Financial Management
-Financial Markets
-Financial Analysis
-Portfolio Management
-Alternative Investments and Strategies
-Fixed Income and Derivative Investments
-Dissertation Project

What are my career prospects?

Graduates from this programme will find employment as software engineers, database specialists, infrastructure managers, financial analysts, financial consultants, business analysts, system analysts, investment analysts, e-finance architects, credit managers, portfolio managers, business intelligence executives, wealth services officers, and risk management auditors amongst others.

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This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Read less
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Read less
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Read less
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 course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. … Read more

The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. You will develop skills so that you are able to formulate a well posed problem from a description in financial language, carry out relevant mathematical analysis, develop and implement an appropriate numerical scheme and present and interpret these results.

The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.

You will take three introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics and MATLAB.

The first term focuses on compulsory core material, offering 80 hours of lectures and 40 hours of classes/practical. The core courses are as follows:

  • Stochastic Calculus
  • Financial Derivatives
  • Numerical Methods I - Monte-Carlo
  • Numerical Methods I - Finite Differences
  • Statistics and Financial Data Analysis
  • Financial Programming with C++ 1

In the second term, three streams are offered; each stream consists of 32 hours of lectures and 16 hours of classes/practical. The Tools stream is mandatory and you will also take either the Modelling stream or the Data-driven stream.

Modelling stream

  • Exotic derivatives
  • Stochastic volatility, jump diffusions
  • Commodities
  • Fixed income

Data-driven stream

  • Asset pricing and inefficiency of markets
  • Market microstructure and trading
  • Algorithmic trading
  • Advanced financial data analysis
  • Machine learning
  • Python

Tools stream

  • Numerical methods 2 - Monte Carlo methods
  • Numerical methods 2 - Finite differences
  • Calibration
  • Optimisation
  • Introduction to stochastic control

As well as the streams, the course includes a compulsory one-week (24 hours of lectures) intensive module on quantitative risk management which is to be held in/around the week before the third term.

The third term is dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor.

The second component of the financial computing course, Financial Computing with C++ 2 (24 hours of lectures and practicals in total), is held shortly after the third term.

The examination will consist of the following elements:

  • two written examinations and one take-home project, each of two hours' duration - the written examinations will cover the core courses in mathematical methods and numerical analysis
  • a written examination on the Modelling stream or a written examination and a computer-based practical examination on the Data-driven stream
  • a written examination assessing the Tools stream
  • a take-home project assessing the course in quantitative risk management
  • two practical examinations assessing two courses in financial computing with C++.

Graduate destinations

MSc graduates have been recruited by prominent investment banks and hedge funds. Many past students have also progressed to PhD-level studies at leading universities in Europe and elsewhere.



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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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This MSc provides an ideal foundation for graduates who wish to pursue a career as software engineers. Read more

This MSc provides an ideal foundation for graduates who wish to pursue a career as software engineers. The programme provides the opportunity to undertake a significant group software engineering project sponsored by a financial services company, allowing students to specialise in software systems engineering from a financial computing perspective.

About this degree

Students gain instruction in all aspects of software engineering needed for the development of large, complex, highly dynamic, distributed software-intensive systems. The programme covers requirements engineering, software design, validation and verification, tools for the development of software intensive systems, and provides instruction in financial information systems.

Students undertake modules to the value of 180 credits.

The programme consists of six core modules (90 credits), one optional module (15 credits), one elective module (15 credits) and a group project (60 credits).

Core modules

  • Financial Institutions and Markets (15 credits)
  • Professional Practice (15 credits)
  • Requirements Engineering and Software Architecture (15 credits)
  • Software Abstractions and Systems Integration (15 credits)
  • Tools and Environments (15 credits)
  • Validation and Verification (15 credits)

Optional modules

Students are required to select 15 credits from the Option group and 15 credits from the Elective group.

Option Group

  • Compliance, Risk and Regulation (15 credits)
  • Financial Market Modelling and Analysis (15 credits)

Elective Group

  • Complex Networks and Web (15 credits)
  • Computer Security I (15 credits)
  • Computer Security II (15 credits)
  • Distributed Systems and Security (15 credits)
  • Introduction to Logic, Semantics and Verification (15 credits)
  • Language Based Security (15 credits)
  • Malware (15 credits)
  • Modal Logic and Transition Systems (15 credits)
  • Multimedia Systems (15 credits)
  • Networked Systems (15 credits)
  • People and Security (15 credits)
  • Verification and Mechanised Proofs (15 credits)

Please note: the availability and delivery of modules may vary, based on your selected options.

Dissertation/report

All students participate in a group project, encompassing the full software development lifecycle and applying techniques learned, such as the technical skills of analysis, design and implementation.

Teaching and learning

The programme is delivered through a combination of lectures, written and laboratory exercises, and project work. Student performance is assessed through written exercises with modelling notations, laboratory exercises with tools and environments, unseen examination papers, and a significant, comprehensive group project.

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

Careers

This professionally oriented programme provides an ideal foundation for graduates who wish to pursue a career as a software architect or leader of software development organisations. It also provides an excellent introduction for those who want to pursue research in software systems engineering.

Graduates from UCL are keenly sought by the world's leading organisations, and many progress in their careers to secure senior and influential positions. UCL Computer Science graduates are particularly valued as a result of the department's international reputation, strong links with industry, and ideal location close to the City of London.

Graduates have found positions at global companies such as RBS and UBS.

Employability

There is, throughout the world, a strong demand for software engineers with solid foundations covering not only the programming aspects of software development, but also aspects related to requirements engineering, software architectures, system integration, and testing. Many surveys rank software engineering positions as among the best jobs in the world.

Following graduation, our students are generally hired as software engineers or software architects by large financial institutions, sometimes by institutions they have engaged with in the context of their MSc project.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research.

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Our Master's programmes have some of the highest employment rates and starting salaries, with graduates entering a wide variety of industries from entertainment to finance.

We take an experimental approach to our subject and place a high value on our extensive range of industrial collaborations. In the recent past, students have worked on projects and coursework in collaboration with Microsoft, IBM, and financial institutions such as JP Morgan, Citigroup and BNP Paribas.

Accreditation

IET - Partial CEng (Further Learning). CITPFL - Accredited by BCS. CEng (partial fulfilment) - Accreditation by the BCS.

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: Computer Science

96% 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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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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Financial Mathematics is a branch of Mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Read more

Overview

Financial Mathematics is a branch of Mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Its main aims are to quantify and hedge risks in the financial marketplace.

Effective computational methods are crucial for the successful use of mathematical modelling in finance. The MSc in Financial and Computational Mathematics is designed to reflect this combination of knowledge and skills so that its graduates are well equipped to enter the competitive job markets of quantitative finance and related fields.

The course is focused on computational techniques and mathematical modelling used in the financial industry and on the required background in finance. The course is provided by the School of Mathematical Sciences with valuable input from the School of Economics. To ensure that the degree keeps pace with changes in employer expectations and employment opportunities, the course has its own advisory board which consists of leading experts from the financial industry and academia.

Key facts:

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 60 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).
- In the last independent Teaching Quality Assessment, the School scored 23 out of 24.
- The course has its own advisory board (see below) consisting of leading experts from the financial industry and academia.
- The course is offered in collaboration with the School of Economics.

Module details

Core modules include: financial mathematics, advanced financial mathematics, scientific computing and c++, advanced scientific computing, financial mathematics dissertation.

Optional Stream 1 (Maths/Stats and Computing): Optimisation, Time Series and Forecasting, Statistical Foundations.

Optional Stream 2A: Econometic Theory, Financial and Macro Econometrics, Time Series Econometrics, Mathematics for Engineering Management, Game Theory.

Optional Stream 2B: Microeconomic Analysis, Financial Economics, Options and Futures Markets, Mathematics for Engineering Management, Game Theory.

English language requirements for international students

IELTS: 6.5 (with no less than 6.0 in any element)

Further information



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Mathematics and Computing for Finance at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Mathematics and Computing for Finance at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

The MSc Mathematics and Computing for Finance course has been designed to meet the growing demand for specially trained mathematicians to work in the world’s financial markets and insurance.

Despite the current volatile nature of the banking industry, many banks still have a pressing need for employees with advanced mathematical skills who can further their understanding of turbulence in financial markets.

On the Mathematics and Computing for Finance course you will study different elements of both mathematics and computing in addition to developing your communication and presentational skills through a project you will undertake. As a student of the MSc in Mathematics and Computing for Finance programme you will be fully supported to ensure that your project is best suited to support your future career plans.

Aims of MSc in Mathematics and Computing for Finance

Have in depth knowledge in stochastic analysis and parts of advanced real analysis. (Fourier analysis and Partial Differential Equations) as well as parts of numerical analysis which are central for applications to finance.

Have developed advanced computing skills being essential for handling problems relevant for a job on the finance markets.

Have, as a mathematician, a good understanding of finance markets.

Have developed skills needed to work in a highly inter-disciplinary profession, including advanced programming techniques and communication skills across the borders.

Modules

Please visit our website for a full description of modules for the MSc Mathematics and Computing for Finance.

Careers

The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistically analysis, marketing and sales.

Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.

All academic staff in Mathematics are active researchers and the department has a thriving research culture.

Student profiles

"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."

Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance



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Students develop an advanced knowledge of computational methods in finance, which is a prerequisite for a successful career in the financial industry within 'quant' teams. Read more

Students develop an advanced knowledge of computational methods in finance, which is a prerequisite for a successful career in the financial industry within 'quant' teams. 'Quants' (development analysts) design and implement complex models and are sought after by banks, fund managers, insurance companies, hedge funds, and financial software and data providers.

About this degree

This degree comprises advanced modules on quantitative and modelling skills, which are essential for 'quant' roles in trading research, regulation and risk. This applied MSc programme is distinctive in that it provides a solid mathematical and statistical foundation together with an education in advanced-level programming.

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 dissertation (60 credits).

Core modules

  • Financial Data and Statistics (15 credits)
  • Financial Market Modelling and Analysis (15 credits)
  • Market Risk Measures and Portfolio Theory (15 credits)
  • Numerical Analysis for Finance (15 credits)

Optional modules

Students select 60 credits from optional modules.

  • Algorithmics (15 credits)
  • Applied Computational Finance (15 credits)
  • Database Systems (15 credits)
  • Financial Engineering (15 credits)
  • Financial Institutions and Markets (15 credits)
  • Machine Learning with Applications in Finance (15 credits)
  • Market Microstructure (15 credits)
  • Networks and Systemic Risk (15 credits)
  • Operational Risk Measurement for Financial Institutions (15 credits)
  • Software Engineering (15 credits)
  • Stochastic Processes for Finance (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

With permission, a student may substitute up to two optional modules with electives. A list of acceptable elective modules is available on the Departmental page.

Dissertation/report

All students undertake an independent research project which culminates in a dissertation of about 10,000 words or 50 pages. Usually this will be undertaken during a summer placement in an industry environment arranged by the department.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials, seminars, and project work. It comprises two terms of teaching, followed by examinations and a dissertation. Assessment is through coursework, unseen examinations and a dissertation.

Further information on modules and degree structure is available on the department website: Computational Finance MSc

Careers

This is a relatively new programme and therefore no specific information on graduate destinations is currently available. UCL Computer Science graduates typically find work in financial institutions such as Credit Suisse, JP Morgan, Morgan Stanley, and Deutsche Bank as financial analyst application developers, quant developers, and business managers. The University of Cambridge and UCL are among top further study destinations.

Employability

Our graduates are particularly valued as a result of the department's international reputation, strong links with industry, and ideal location close to the City of London. Graduates are especially sought after by leading finance companies and organisations.

Why study this degree at UCL?

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

UCL Computer Science hosts the Doctoral Training Centre in Financial Computing and Analytics, which is the only one of its kind in the UK.

UCL's central London location ideally places it close to one of the world's most important financial centres, with which UCL pioneers industrial/academic engagements. Students on the Computational Finance MSc will benefit from teaching input from City of London practitioners.

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: Computer Science

96% 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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