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Masters Degrees (Mathematical Finance)

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The School of Mathematics and Alliance Manchester Business School at the University of Manchester have combined their academic strength and practical expertise to deliver the  . Read more

The School of Mathematics and Alliance Manchester Business School at the University of Manchester have combined their academic strength and practical expertise to deliver the  MSc in Mathematical Finance  (UK 1 year), ensuring that students can experience both the mathematical and economic perspective of the subject.

This is also supported by invited lectures from senior staff members of leading financial institutions and outstanding mathematicians who are internationally recognised for contributions to Mathematical Finance. Past lectures include:

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

The course provides students with advanced knowledge and understanding of the main theoretical and applied concepts in Mathematical Finance delivered from a genuinely international and multi-cultural perspective with a current issues approach to teaching. The focus is on mathematical theory and modelling, drawing from the disciplines of probability theory, scientific computing and partial differential equations to derive relations between asset prices and interest rates, and to develop models for pricing, risk management and financial product development.

The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.

Coursework and assessment

Teaching is shared by the School of Mathematics and Alliance Manchester Business School, and delivered through lectures, case studies, seminars and group project-based work.

Course unit details

There are (i) eight course units to attend over two academic terms and (ii) a dissertation project to be completed in the summer term. Teaching of the course units is shared by the School of Mathematics and the Manchester Business School and delivered through lectures, case studies, seminars and group project-based work.

First term course units (autumn): Derivative Securities; Foundations of Finance Theory; Martingales with Applications to Finance; Stochastic Calculus.

Second term course units (spring): Brownian Motion; Computational Finance; Time Series Analysis and Forecasting in Finance; Stochastic Modelling in Finance.

Third term dissertation project (summer): In this term students will conduct an original study of a topic relating to the programme and write an MSc dissertation.

Additional fee information

The fees quoted above will be fully inclusive for the course tuition, administration and computational costs during your studies.

All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of courses lasting more than a year for UK/EU students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit:  postgraduate fees . Always contact the department if you are unsure which fee applies to your qualification award and method of attendance.

Self-funded international applicants for this course will be required to pay a deposit of £1000 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. This deposit will only be refunded if immigration permission is refused. We will notify you about how and when to make this payment.

Facilities

The School of Mathematics is one of the largest integrated departments of mathematical sciences in the UK with an outstanding reputation and superb  facilities .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.



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Candidates who have a good undergraduate (BSc) degree or equivalent but whose mathematical background is insufficient for direct entry to the MSc programme may apply for a place on the conversion year for the MSc in Mathematical Finance. Read more
Candidates who have a good undergraduate (BSc) degree or equivalent but whose mathematical background is insufficient for direct entry to the MSc programme may apply for a place on the conversion year for the MSc in Mathematical Finance.

A place on the conversion year is normally offered together with a conditional offer for the MSc in Mathematical Finance in the following year, subject to successfully completing the conversion year. The normal progression requirement for progression from the conversion year to the MSc in Mathematical Finance is a final weighted average at 2:1 level (60% or above) for the modules taken in the conversion year.

Programme structure

The conversion year consists of a selection of modules to the value of 120 credits being part of the undergraduate degree in Mathematics and Finance at the University of York, with emphasis on the mathematical aspects of the course. Module choice is subject to prerequisites, timetabling constraints, availability of modules, and is subject to approval by the programme director.

The available modules may vary from year to year but are likely to include:

Term 1 (Autumn)
-Calculus (30 credits) (continues into Spring and Summer Terms)
-Algebra (20 credits) (continues into Spring and Summer Terms)
-Introduction to Probability and Statistics (20 credits)
-Statistics I (10 credits)
-Applied Probability (10 credits)
-Differential Equations (10 credits)
-Mathematical Finance I MAT00015H (10 credits)

Terms 2 and 3 (Spring and Summer Terms)
-Calculus (30 credits) (starts in Autumn, continues through Spring and completes in Summer Term)
-Algebra (20 credits) (starts in Autumn, continues through Spring and completes in Summer Term)
-Introduction to Applied Mathematics (20 credits) (starts in Spring Term, continues into Summer Term)
-Real Analysis (20 credits) (starts in Spring Term, continues into Summer Term)
-Linear Algebra (20 credits) (starts in Spring Term, continues into Summer Term)
-Vector Calculus (20 credits) (starts in Spring Term, continues into Summer Term)
-Statistics II (20 credits) (starts in Spring Term, continues into Summer Term)
-Numerical Analysis (10 credits) (Spring Term only)
-Mathematical Finance II (10 credits) (Spring Term only)

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

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

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

This MSc programme delivers:

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

Programme structure

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

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

Compulsory courses previously offered include (both streams):

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

Additional compulsory courses for Computational Stream previously offered include:

  • Numerical Partial Differential Equations (10 credits, semester 2)
  • Time Series (10 credits, semester 2)

Additional compulsory courses for Financial stream previously offered include:

  • Financial Risk Theory (10 credits, semester 2)
  • Optimization Methods in Finance (10 credits, semester 2)

Optional courses previously offered include:

  • Numerical Partial Differential Equations (10 credits, semester 2)
  • Time Series (10 credits, semester 2)
  • Financial Risk Theory (10 credits, semester 2)
  • Optimization Methods in Finance (10 credits, semester 2)
  • Integer and Combinatorial Optimization (10 credits, semester 2)
  • Bayesian Theory (10 credits, semester 1)
  • Credit Scoring (10 credits, semester 2)
  • Python Programming (10 credits, semester 1)
  • Scientific Computing (10 credits, semester 1)
  • Programming Skills - HPC MSc (10 credits, semester 1)
  • Parallel Numerical Algorithms - HPC MSc (10 credits, semester 1)
  • Applied Databases (10 credits)

Work placements/internships

We work closely with the Scottish Financial Risk Academy (SFRA) to offer a number of short courses led by industry (part of our Research-Linked Topics) and to provide the opportunity to our best students to write their dissertations during placements with financial services companies.

Learning outcomes

At the end of this programme you will have:

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

Career opportunities

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



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The Masters Programme aims to develop students’ mathematical and computational skills, and also those in financial modelling. The curriculum includes such subjects as probability theory, stochastic calculus, numerical methods, optimisation and control theory, stochastic finance, interest rate models and credit risk. Read more

The Masters Programme aims to develop students’ mathematical and computational skills, and also those in financial modelling.

The curriculum includes such subjects as probability theory, stochastic calculus, numerical methods, optimisation and control theory, stochastic finance, interest rate models and credit risk. It thus provides a thorough training in modern mathematical finance. In studying for our Masters, students are put in contact with the most important technical and quantitative topics of finance, both theoretical and applied, which range from mathematical background to the latest trends in the financial sector. Increasingly, the financial sector demands a Masters degree in Mathematical Finance from a prestigious university as a prerequisite for recruitment. Our students have often been recruited by prominente companies whilst still preparing their Masters’ thesis, at both a national and na international level. Amongst others, such companies include: EY, Mercer, KPMG, Deloitte, CGD, the Bank of Portugal, BNP Paribas, BPI, Banque Européenne d’Investissement (EIB), Banque Centrale Européenne, Lloyds Bank, and Santander bank. ISEG - Lisbon School of Economics and Management, of ULisboa, has well established departments of Mathematics, Economics and Management, which enables our students to benefit from the consequent synergies, and it provides excellent conditions for hosting the Masters in Mathematical Finance. This fact, together with the high quality of the academic staff of this Masters, all of whom hold PhDs from prestigious universities (such as the Stockholm School of Economics and the Universities of Oxford, Edinburgh and Barcelona), makes it unique in our country.



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The part-time MSc in Mathematical Finance aims to develop your mathematical modelling, data analysis and computational skills as applied to finance, without the need to take time out of your career to study. . Read more

The part-time MSc in Mathematical Finance aims to develop your mathematical modelling, data analysis and computational skills as applied to finance, without the need to take time out of your career to study. 

Incorporating concepts from applied and pure mathematics, statistics, computing and corporate finance, the course gives you a broad intellectual perspective and covers, from fundamentals to the latest research, the most important aspects of quantitative finance currently in use in the finance industry.

The course:

  • is delivered in a series of intensive week-long modules based in Oxford, so that time away from work is kept to a minimum; 
  • allows you to choose advanced modules based on, and write an academic dissertation in, an area of relevance to your career;
  • regularly updates its content to reflect the ever-changing industry and keep the material relevant;
  • is taught by a panel of world-leading academics and industrial practitioners; and

It is possible to exit the course early and be awarded the Postgraduate Diploma in Mathematical Finance, should work pressures intervene before it is possible to write a dissertation.

In order to complete the MSc each student must attend and be assessed on four core modules, three advanced modules and to submit a dissertation. Students are expected to take seven terms (28 months) to complete the course. 

Modules are taught through a series of lectures, practical sessions, guided reading, guest lectures and course assignments. 

The core modules cover the mathematical foundations of probability, statistics and partial differential equations, stochastic calculus and martingale theory, portfolio theory, the Black-Scholes model and extensions, numerical methods (finite differences and Monte Carlo), interest rate modelling, stochastic optimisation, exotic derivatives and stochastic volatility. MATLAB and Python are used as a practical computing languages.

Attendance at the four core modules is compulsory. For each module there is an assignment for which feedback and an indicative mark is given to assist you in improving your future performance. Assessment for these compulsory modules consists of two two-hour written examinations held in September of the first year.

Each of the advanced modules explores a key area in contemporary mathematical finance. The programme of advanced modules is published in July each year, and you will be asked to register your choice of three modules. Attendance at these three assessed modules is compulsory. Advanced modules will be assessed by short ‘special project’ reports, each submitted on a subject chosen by you that is covered in the module.

You will complete a dissertation on a topic chosen in consultation with your supervisor and the Course Director.



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This is an exciting and intensive one-year taught postgraduate programme. Our team of dedicated lecturers and support staff help to keep the course one of our most popular. Read more
This is an exciting and intensive one-year taught postgraduate programme. Our team of dedicated lecturers and support staff help to keep the course one of our most popular. In a typical year the class consists of around 15-20 students, from a number of different countries.

The Department of Mathematics, the University of York, and the historic City of York provide a uniquely attractive environment in which to live and study.

On this MSc programme you will develop skills and competence in Mathematical Finance which are of direct relevance in the field of work. For details of the modules currently offered please see Programme Structure. If you are unable to commit yourself to full-time campus-based study and would prefer to study by online distance learning then please visit the MSc in Mathematical Finance by Online Distance Learning.

Careers

The MSc in Mathematical Finance opens up fantastic employment opportunities to successful graduates in:
-Investment banks
-Hedge funds
-Insurance companies
-Stock brokerage
-Unit trusts
-Pension funds
-Corporate finance departments
-Other financial institutions worldwide.

Graduates can embark on careers in trading and pricing derivative financial securities (options, futures, forwards, and the like), fund management, risk management, research and development, or pursue further study to PhD level. For more information about career opportunities, please visit the career opportunities section.

You will also receive Transferable and Generic Skills training, along with the option of choosing various modules to add to the variety of the programme.

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This distance learning programme builds on the strength and success of the campus-based taught MSc Mathematical Finance at the University of York. Read more
This distance learning programme builds on the strength and success of the campus-based taught MSc Mathematical Finance at the University of York. The online MSc was launched in September 2009 to run alongside the campus-based programme.

Applications are invited for the intake of students in September or February. Candidates should submit their application at least two weeks before an intake is due to start.

A online Pre-sessional Programme is available for candidates who need to strengthen or consolidate their mathematics background before embarking on the MSc. Such candidates need to apply at least three months before an MSc intake is due to start.

Online students will be developing skills and competence in Mathematical and Quantitative Finance which are of direct relevance in the field of work, and can open up fantastic employment and progression opportunities.

The online programme has built-in flexibility to meet the needs of distance learners from diverse backgrounds:
-City and other professionals, who wish to pursue a postgraduate degree programme without disrupting their career commitments
-Individuals, companies and professional organisations seeking suitable Continuing Professional Development (CPD) courses
-Recent university graduates who need to support themselves or their families while continuing their studies to postgraduate level
-Students who find it difficult to attend a campus-based programme because of a variety of reasons such as family care commitments or disability
-Overseas students who seek a degree in Mathematical Finance from a leading British university but prefer to pursue their studies from their home country

Course outline

The distance learning programme is delivered online using Internet conferencing and application sharing software and a web-based Virtual Learning Environment (VLE).

A distinctive feature are regular one-to-one ("Oxbridge style") online tutorials and supervisory sessions.

Interactive presentations are provided on CDs and for downloading via the VLE in lieu of lectures, supported by lecture notes, worked exercises, synchronous one-to-one online tutorials and an asynchronous discussion forum.

No presence on campus is required, but access to suitable hardware, software and a good internet connection are necessary pre-requisites.

The online MSc programme consists of three stages: Certificate, Diploma and Dissertation, preceded by a brief Induction Module. The programme structure section provides the contents and specifications for the modules comprising each of these stages.

There are two four-month teaching periods in each academic year, 1 October - 31 January and 15 March - 15 June, and two intakes per year, in September and February. Completing the online MSc can take from 18 months (Fast Stream) to 36 months (Standard Stream). Transfers between the two streams are possible between stages.

Students have remote access to electronic library resources, and full pastoral and study support including a personal supervisor and a dissertation supervisor.

Assessment is by means of written coursework submitted electronically and a recorded online Viva Voce (an oral examination) held at the end of each of the three stages (Certificate, Diploma, Dissertation) of the programme.

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

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

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

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

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

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

Programme modules

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

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

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

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

Assessment

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

Careers and further study

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

Scholarships and sponsorships

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

Why choose mathematics at Loughborough?

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

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

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

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

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

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

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Practices in the financial markets over the last years have contributed to the current economic situation. Read more

Overview

Practices in the financial markets over the last years have contributed to the current economic situation. This specialised programme that has been designed to provide you with the necessary mathematical techniques and tools to understand and model the complexity of financial markets, and to succeed in a future career in the finance industry.

Designed to equip talented individuals with the skills necessary for a successful career in finance, this MSc brings together the strengths of two highly respected schools at Queen Mary – Mathematical Sciences, and Economics and Finance – to give you an in-depth understanding of the subject. Rigorous training is provided, relevant to roles in quantitative analysis, trading, financial engineering and structuring, risk management, and software development.

The programme consists of eight modules and a dissertation. You will develop an advanced understanding of the mathematical models used in finance, learn about a range of important numerical tools and techniques, gain practical skills in computer programming, and undertake a substantial research project under expert supervision in a chosen area of interest. Past dissertation topics have been in areas such as the distribution of loan portfolio value; passport options; the Heston stochastic volatility model, pricing American options using Monte-Carlo, and asset pricing with jump diffusion models.

This programme will:

Introduce you to the mathematics used by practitioners in the field.
Provide you a rigorous training and strong analytical and quantitative skills in finance.
Cover a wide range of analytical tools applied in quantitative asset pricing and financial derivatives.

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Sophisticated financial markets continue to play an essential role in the economies of the modern world, and a career in the finance and banking industry can be exciting, intellectually challenging and highly lucrative. Read more
Sophisticated financial markets continue to play an essential role in the economies of the modern world, and a career in the finance and banking industry can be exciting, intellectually challenging and highly lucrative.

In spite of recent turmoil in this sector, there is still strong demand for well-qualified individuals. Areas such as quantitative analysis and risk management are now as important as ever. However, there is an increased importance that professionals working in areas such as trading, sales and financial engineering also have a solid understanding of the mathematical models (and their limitations) that are used to price and risk-manage the financial products that are traded.

This specialised programme is aimed at both new graduates and current professionals. It has been designed to provide you with the necessary mathematical tools and techniques to understand and model the complexity of financial markets, thereby enabling you to develop a successful career in the finance industry. With this programme you will:

Understand many of the advanced mathematical models used in finance
Learn about a range of important numerical tools and techniques used in the field
Gain practical skills in computer programming and software design
Undertake a substantial project, under expert supervision, in a chosen area of interest

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This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis. Read more

This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis.

Course details

This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis.

A collaboration with https://www.arpm.co/" target="_blank">Advanced Risk and Portfolio Management (ARPM) allows MSc students to attend ARPM’s prestigious summer https://www.arpm.co/bootcamp/" target="_blank">ARPM Bootcamp at a discount.  Attending this class also gives an access to https://www.arpm.co/lab/overview/" target="_blank">the ARPM Lab, an online platform that contains an extensivebody of knowledge for quantitative risk management and quantitative portfolio management. Successful completion of it exempts students from our Risk Analytics module. 

In most cases, we expect that graduates from the Masters will take positions in quantitative analysis (or similar) in major financial institutions, such as in the City. The programme also prepares you to pursue further studies in academia.

Employability

Graduates from this MSc programme will be well prepared to compete for quantitatively demanding positions in financial institutions. The degree should also prepare them for postgraduate research, either for purely academic ends or to further qualify them for work in financial institution.

Destinations of recent graduates include Bank of America/Merrill Lynch, BNP Paribas, China Jianyin Investment Securities, Deutsche Bank, the FSA, LGIM, Société Générale and wonga.com.



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This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis. Read more

This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis.

Course details

This programme, taught jointly by the School of Mathematics and the Department of Economics, provides the skills that will enable technically able graduates (including in mathematics, science and engineering) to apply their quantitative training to financial analysis.

A collaboration with https://www.arpm.co/" target="_blank">Advanced Risk and Portfolio Management (ARPM) allows MSc students to attend ARPM’s prestigious summer https://www.arpm.co/bootcamp/" target="_blank">ARPM Bootcamp at a discount.  Attending this class also gives an access to https://www.arpm.co/lab/overview/" target="_blank">the ARPM Lab, an online platform that contains an extensivebody of knowledge for quantitative risk management and quantitative portfolio management. Successful completion of it exempts students from our Risk Analytics module. 

In most cases, we expect that graduates from the Masters will take positions in quantitative analysis (or similar) in major financial institutions, such as in the City. The programme also prepares you to pursue further studies in academia.

Employability

Graduates from this MSc programme will be well prepared to compete for quantitatively demanding positions in financial institutions. The degree should also prepare them for postgraduate research, either for purely academic ends or to further qualify them for work in financial institution.

Destinations of recent graduates include Bank of America/Merrill Lynch, BNP Paribas, China Jianyin Investment Securities, Deutsche Bank, the FSA, LGIM, Société Générale and wonga.com.



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

Who is it for?

To successfully complete this course, you must have a good understanding of mathematics. You may well have studied finance, economics, engineering or maths or physics as an undergraduate. Or you might have a bachelor’s degree in a science subject, in particular computer science. You should have a general interest in mathematics and statistics.

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 difference between the MSc Mathematical Trading and Finance to the other two quants courses (MSc Financial Mathematics and MSc Quantitative Finance) are core modules which focus on quantitative trading and structuring.

You’ll study core modules which focus on the theory of finance and different financial assets. You will look at how these assets are priced and used for asset management or risk management purposes.

The second type of core modules cover the mathematical and statistical aspects needed in quantitative finance, including some stochastics. This also includes learning some programming languages, in particular Matlab, but also VBA.  Finally, Term three offers you flexibility within your masters; either by writing a dissertation or undertaking a project. You can complete your degree entirely choosing electives.

What will you learn

  • You will have learned a good understanding of the technical aspects used in financial
  • markets, starting from the financial theory, looking at different financial instruments and showing various applications of the theoretical concepts.
  • You will gain a good understanding of stochastics, mathematical finance and econometrics as well as some programming.
  • You will also obtain a very good understanding of different financial assets, in particular derivatives, and how they can be used in different context, such as risk management, asset management or structuring.
  • The MSc Mathematical Trading and Finance will also help you do understand the financial theory used in financial markets with an emphasis on practical applications.
  • You will three different possibilities to complete your degree in the third term, including writing a dissertation or an applied project.
  • You can also opt to get all the credits through taught electives. Popular
  • electives include Behavioural Finance, Trading and Hedging in the FOREX Market, Technical Analysis, Hedge Funds or 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 Mathematical Trading and Finance 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.

Induction Weeks

The Mathematical Trading and Finance 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. They usually find employment with large investment banks, but also some smaller boutique finance firms, hedge funds or other specialist companies.

Working as an analysis or quantitative analysts, in risk management, on fixed income security desks or in the asset management industry including hedge funds are typical jobs for students from the MSc Mathematical Trading and Finance. Some students also secure positions on trading desks.

You will also have the skills to study for a PhD in the area of quantitative finance and financial markets.



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The MSc in Business Finance with professional placement is designed to enhance students' understanding of the operation of firms, with a special focus on the financing decisions they must make. Read more

About the course

The MSc in Business Finance with professional placement is designed to enhance students' understanding of the operation of firms, with a special focus on the financing decisions they must make. This requires an evaluation of the firm’s relationship to financial markets. It also requires an understanding of the theory and practice underlying corporate finance and investment decisions. By studying the operation and design of corporate financial systems, and analysing business financing and investment decisions, this masters programme should enable students to find a role within the finance department of large firms or in government bodies, as well as provide them with tools to help organise smaller businesses.

The objective of the Business Finance MSc is to produce graduates with a comprehensive knowledge and understanding of business finance and company valuation within the context of modern financial markets, without necessarily requiring a high level of mathematical or statistical knowledge as a prerequisite. The key transferable research skills acquired will enable students to proceed to PhD study. In addition, the programme will equip students with the key skills required to undertake further professional development and seek career opportunities within financial management.

Aims

You will be provided with a rigorous treatment of the theory of corporate finance

You will be taught the econometric and mathematical techniques necessary to understand the literature and undertake empirical investigations in the area of finance

Through a selection of optional modules the course will offer you a broader perspective on the subject matter and willl allow you to cover specific areas in accounting and finance that are of specific interest to you

Course Content

The MSc consists of both compulsory and optional modules, a typical selection can be found below. Modules can vary from year to year, but these offer a good idea of what we teach.

The full-time Business Finance MSc programme is designed with four equally weighted modules in each of the first two terms, with three being compulsory and one an option from a list. The dissertation carries one third of the marks for the course and is undertaken after the modules have been completed. The part-time option is designed with two modules in each of four terms. The compulsory modules give an excellent coverage of core material in finance designed in a way to be applicable to business. The Business Finance MSc analyses the theory and practice of business finance, focusing on financial decision making within firms and how they interact with the financial markets and institutions.

Through the optional modules the course is also designed to offer a broader perspective on the subject matter and allows you to cover specific areas in accounting and finance that is of particular interest to you.

Compulsory Modules

Essentials of Mathematics and Statistics
Quantitative Methods for Business Finance
Foundations of Finance
Business Economics
Company Valuation
Business Finance
Business Finance Workshop
Dissertation

Optional Modules

Students must choose two optional modules from the following:

Either Financial Reporting in Capital Markets
Or International Finance

Either International Accounting Standards and Policy
Or Investment Valuation Models

Part-time option

Level 1

Essentials of Mathematics and Statistics
Foundations of Finance
Quantitative Methods for Business Finance
Business Finance Workshop
Business Finance

Level 2

Business Economics
Company Valuation

Students must choose two optional modules from the following:

Financial Reporting in Capital Markets
International Finance
International Accounting Standards and Policy
Investment Valuation Models
The Dissertation must be submitted in the spring term of the third year.

Special Features

A key feature of this course that distinguishes it from other finance masters programmes is that it emphasises the applied aspects of business finance and financial decision making within firms. As such, there is more focus on real-life, up-to-date analysis of business decisions and less emphasis on the theoretical foundations and mathematical underpinnings of finance. This is particularly suited to students who would like to enhance their knowledge of finance within a business context but who have backgrounds in a wider business or management field.

Now full-time students have the opportunity to spend time in industry with the Professional Practice placement. This allows you to not only apply what you learn in real-world situations, but will significantly enhance your employability prospects upon graduating.
Another feature is that the emphasis on the applied nature of financial decision making is reinforced through the Business Finance Workshop. This is a series of presentations and discussions of cutting-edge topics led by industry leaders and practitioners.

The course is one of four specialist masters programmes developed by leading experts in the Economics and Finance Department at Brunel. As a student here you will be part of a long standing and thriving environment for research and study with many advantages and benefits such as:

Outstanding academic expertise and research-led teaching
95% of our academics are nationally and internationally recognised for their work in economics and econometrics in the latest Research Assessment Exercise (2008)
As a result, you will benefit from up-to-the-minute research-led teaching by academic staff who regularly publish in international peer-reviewed journals, have an impact on international regulatory design and obtain significant research grants.

Professional training facilities
You will have access to a variety of professional databases used in business and the finance industry which include Datastream, Bloomberg, Bank Scope, Osiris, Reuters 3000 Xtra and Thomson One Banker
We hold regular training sessions and external visits with Bloomberg, which will enhance your research and expose you to real-world factors that will be important in future finance related employment.

Scholarships
Brunel offers a number of scholarships for UK, EU and international students.

Excellent links with leading organisations
We have excellent links with business and the finance industry, which will help you to network with organisations and get ahead in your career.

Industry talks, guest lectures and research seminars
A number of industry talks with professionals from the private sector will be invited to teach part of the programme and will provide you with further practical experience
There is a wide range of events on offer, such as guest lectures and research seminars to keep you up-to-date on the latest developments and will help build your contacts.

Teaching

Effective learning is achieved through a combination of lectures, seminars, directed independent study, workshops, oral presentations, and varied assessment patterns. Use of appropriate IT resources is expected (e.g. electronic resources to access data, and relevant software programmes used in research methods). Dissertation research will give you the opportunity to integrate your knowledge of important themes, frameworks and research findings in business finance obtained via lectures, seminars, and workshops.
Students who successfully complete a professional placement will be invited to attend a tutorial day to give a presentation about their experience. An optional reflective journal during the placement may assist in preparation for the presentation and dissertation.

Assessment

All modules are assessed by a combination of coursework and final examinations. Students who successfully complete the taught part of the course can proceed to the dissertation stage. Students who do not follow the pathway with Professional Practice are expected to work on their dissertation in the summer and to submit the final draft in mid-September. Students who follow the Professional Practice pathway will complete their placement during the summer and work on their dissertation afterwards, submitting in January.

Professional Placement

All students who enrol on the full-time Business Finance MSc will have the opportunity to complete a placement. A placement can significantly improve your employability and expose you to real-world situations in the Banking and Finance industry, and importantly, allow you to network with industry professionals.

Students completing the work placement option will have a competitive edge in pursuing careers as high-level analysts, economists and managers in financial institutions, governments, financial regulators, business companies and central banks, as well as international organisations.

The placement option is available to full-time applicants and will last for 12-15 weeks during the summer of your course. Placements will begin at the earliest in the last week of May and will finish by September Some employers may also provide a salary.

For students who complete the placement, their dissertation will be completed after the placement has finished. Students who do not find a placement will do their dissertation throughout the summer and submit in September.

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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