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Masters Degrees (Mathematical Programming)

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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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In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. Read more

In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.

The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, Complexity Theory, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.

Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations

Admission requirements for international students

1. A completed Bachelor's degree in Mathematics or Computer Science

In order to get admission to this Master’s you will need a completed Bachelor's in mathematics or computer science that have a strong mathematical background and theoretical interests. We will select students based on their motivation and their background. Mathematical maturity is essential and basic knowledge of logic and discrete mathematics is expected.

2. A proficiency in English

In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:

- TOEFL score of ≥575 (paper based) or ≥90 (internet based)

- IELTS score of ≥6.5

- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our approach to this field

In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.

The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, General Topology, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.

Our research in this field

Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations



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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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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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This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Read more

This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Emphasis is placed on the formulation of problems, on the analytical and numerical techniques for a solution and the computation of useful results.

By the end of the course students should be able to formulate a well posed problem in mathematical terms from a possibly sketchy verbal description, carry out appropriate mathematical analysis, select or develop an appropriate numerical method, write a computer program which gives sensible answers to the problem, and present and interpret these results for a possible client. Particular emphasis is placed on the need for all these parts in the problem solving process, and on the fact that they frequently interact and cannot be carried out sequentially.

The course consists of both taught courses and a dissertation. To complete the course you must complete 13 units.

There are four core courses which you must complete (one unit each), which each usually consist of 24 lectures, classes and an examination. There is one course on mathematical methods and one on numerical analysis in both Michaelmas term and Hilary term. Each course is assessed by written examination in Week 0 of the following term.

Additionally, you must choose at least least one special topic in the area of modelling and one in computation (one unit each). There are around twenty special topics to choose from, spread over all three academic terms, each usually consisting for 12 to 16 lectures and a mini project, which culminates in a written report of around 20 pages. Topics covered include mathematical biology, fluid mechanics, perturbation methods, numerical solution of differential equations and scientific programming. 

You must also undertake at least one case study in modelling and one in scientific computing (one unit each), normally consisting of four weeks of group work, an oral presentation and a report delivered in Hilary term.

There is also a dissertation (four units) of around 50 pages, which does not necessarily need to represent original ideas. Since there is another MSc focussed on mathematical finance specifically, the MSc in Mathematical and Computational Finance, you are not permitted to undertake a dissertation in this field.

You will normally accumulate four units in core courses, three units in special topics, two units in case studies and four units in the dissertation. In addition, you will usually attend classes in mathematical modelling, practical numerical analysis and additional skills during Michaelmas term.

In the first term, students should expect their weekly schedule to consist of around seven hours of core course lectures and seven hours of modelling, practical numerical analysis and additional skills classes, then a further two hours of lectures for each special topic course followed. In addition there are about three hours of problem solving classes to go through core course exercises and students should expect to spend time working through the exercises then submitting them for marking prior to the class. There are slightly fewer contact hours in the second term, but students will spend more time working in groups on the case studies.

In the third term there are some special topic courses, including one week intensive computing courses, but the expectation is that students will spend most of the third term and long vacation working on their dissertations. During this time, students should expect to work hours that are equivalent to full-time working hours, although extra hours may occasionally be needed. Students are expected to write special topic and case study reports during the Christmas and Easter vacations, as well as revising for the core course written examinations.



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This programme develops mathematical modelling skills and provides mathematical techniques required by industry. The period October to June is devoted to lectures, tutorials and practical sessions comprising the core modules. Read more
This programme develops mathematical modelling skills and provides mathematical techniques required by industry.

The period October to June is devoted to lectures, tutorials and practical sessions comprising the core modules.

This is followed by a period of about 14 weeks devoted to an individual project either in an industrial or engineering company or at the University.

Core study areas include mathematical modelling, regular and chaotic dynamics, programming and numerical methods, advanced reliability, availability and maintainability, elements of partial differential equations, static and dynamic optimisation and fluid mechanics.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/industrial-maths-modelling/

Programme modules

Compulsory Modules:
Semester 1
- Mathematical Modelling I
- Regular and Chaotic Dynamics
- Programming and Numerical Methods
- Advanced Reliability, Availability and Maintainability

Semester 2
- Mathematical Modelling II
- Elements of Partial Differential Equations
- Static and Dynamic Optimisation
- Fluid Mechanics

Assessment

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

Careers and further Study

Graduate employment over a wide range of industries encompassing aerospace, automotive electronics, and computer interests as well as software houses, insurance companies, and research establishments and institutions.

Scholarships and sponsorships

A limited number of scholarships are available for this programme as well as the loyalty bonus scheme which reduces fees for Loughborough graduates.

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/industrial-maths-modelling/

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Logistics and Supply Chain Management is about planning and controlling the activities of a company, in order to secure that the right product is delivered in the right quantities, to the right customer, at the right time and to the right price. . Read more

Logistics and Supply Chain Management is about planning and controlling the activities of a company, in order to secure that the right product is delivered in the right quantities, to the right customer, at the right time and to the right price. 

The programme provides:

  • Methods for planning and controlling flows of goods and information in a supply chain. This includes a solid understanding of how to develop the necessary IT based tools.
  • How to design a strategy for Supply Chain Management.
  • Analytical skills that enable you to appraise, systematically structure and analyse the possible solutions to complex logistical problems.

Want to know more about the programme? >>

Programme structure

The programme has a duration of 2 years and consists of 4 semesters.

1st semester: Prerequisite courses

In the first semester the student follows the prerequisite courses that form the methodological and academic basis for the further study programme. This semester consists of 5 classes.

In Optimization Methods the student will be introduced to knowledge about how to model and solve mathematical programming problems.

The course Advanced Excel will get the students beyond basic Excel knowledge, and introduce them to programming in Excel/VBA as well as to simulation by use of @RIS.

Supply Chain Design and Management provides an introduction and a framework to the design of supply chain strategies and to manage operations in contemporary supply chains.

The focus on the discrete event simulation methodology and how this can be applied for solving logistical problems will be taught in the course in Simulation: Modelling and Analysis.

Project Management: Dynamic Scheduling and Control provides the students with an understanding of all fundamental project management disciplines and phases, and also the knowledge and expertise necessary to carry out project management design, planning, execution, delivery on time and budget

2nd semester: Specialisation courses

In the second semester the students follow the specialisation courses of the programme.

Solving practical logistical problems within the fields of Transportation and Distribution Planning will be presented in the course called Distribution and Transportation. The course covers a variety of vehicle routing problems and related solution methods.

The course in: Applied Modelling in Logistics intends to equip the students with the necessary skills to apply quantitative tools, such as simulation or optimization methods, to practical problem situations in the areas of logistics and supply chain management. This includes problem structuring and validation skills to formulate a suitable model in a problem situation, as well as literature review, writing and presentation skills.

Demand Management presents tools for forecasting and aims to provide the student with an understanding of the relationship between forecasts and planning within the company.

To provide the student with an understanding of the strategic impact of good inventory control and production planning, and how it affects system-wide supply chain performance, a class in Production Planning and Inventory Control is provided. This course involves mathematical models to determine optimal control parameters for inventory systems, both with respect to costs and service levels, as well as methods for production planning such as master production scheduling, material requirements planning and capacity planning.

3rd semester: Electives or study abroad

In the third semester, you can choose elective courses within your areas of interest. The courses can be taken either at Aarhus BSS during the semester, at the AU Summer University or at one of our more than 300 partner universities abroad. You can also participate in internship programmes either in Denmark or abroad.

4th semester: Final thesis

The fourth semester is devoted to the Master's thesis. You may freely choose the topic of the thesis and thereby get a chance to concentrate on and specialise in a specific field of interest. The thesis may be written in collaboration with another student or it may be the result of your individual effort. When the thesis has been submitted, it is defended before the academic advisor as well as an external examiner.

Want more information about this programme? Click here.



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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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Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Read more
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

Our Department of Mathematical is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

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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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Profitable design and operation of modern industrial systems requires integration of human, material, equipment and financial resources. Read more
Profitable design and operation of modern industrial systems requires integration of human, material, equipment and financial resources. In recent years this integration has become tighter due to the inclusion of information technology, and resulted in more complex systems. Industrial Engineering research focuses on quantitative analysis, synthesis and management of such complex systems. The affiliated faculty members come from the Industrial Engineering department of the College of Engineering, the Operations and Information Systems group of the College of Administrative Sciences and Economics, and other related fields. Our research areas are diverse, including Logistics, Supply Chain Management, Service Operations, Production Systems, Stochastic Processes, Financial Engineering, Mathematical Programming, Data Mining and Bioinformatics. The programs are built on the basic methodologies of operations research and their applications in manufacturing, distribution and service industries. Graduates of the M.Sc. program have been placed in respectable Ph.D. programs in North America, Europe and Turkey as well as various professional positions in industry.

Current faculty projects and research interests:

• Production Systems
• Service Operations
• Logistics
• Optimization Theory & Algorithms
• Stochastic Processes
• Finanacial Engineering
• Data Mining
• Bioinformatics
• Revenue Management
• Supply Chain Management

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Mathematics is the language that underpins the rest of science. Our Department of Mathematical Sciences has an international reputation in many areas like such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology. Read more
Mathematics is the language that underpins the rest of science. Our Department of Mathematical Sciences has an international reputation in many areas like such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

Graduate Diplomas last for six to nine months (full-time) and include the modules and assessed work of a Masters, without a dissertation. Our Graduate Diploma in Mathematics gives you training in basic mathematics techniques if your first degree contained only a modest amount of mathematics, so that you can proceed to a Masters in mathematics.

At Essex, Mathematics has truly broad reach; we are working on projects ranging from the economic impact of the behaviour of dairy cows, to understanding crowd behaviour through modelling a zombie apocalypse, to circular Sudoku and other puzzles. Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines.

You therefore gain an exceptional range of knowledge and skills that are currently in demand in mathematically oriented employment; in business, commerce, industry, government service, education and in the wider economy.

Our expert staff

Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally. You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our graduates are highly sought after by a range of employers and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other sectors.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Applied Statistics (optional)
-Bayesian Computational Statistics (optional)
-Combinatorial Optimisation (optional)
-Complex Variables and Applications (optional)
-Contingencies I
-Contingencies II
-Cryptography and Codes
-Finance and Financial Reporting (optional)
-Financial Derivatives (optional)
-Graph Theory (optional)
-Introduction to Numerical Methods (optional)
-Linear Algebra (optional)
-Mathematical Biology (optional)
-Mathematical Methods (optional)
-Mathematics of Portfolios (optional)
-Modelling Experimental Data (optional)
-Nonlinear Programming (optional)
-Ordinary Differential Equations (optional)
-Partial Differential Equations (optional)
-Project: Mathematics (optional)
-Quantum Mechanics (optional)
-Real Analysis (optional)
-Statistical Methods (optional)
-Statistics II (optional)
-Stochastic Processes (optional)
-Survival Analysis (optional)
-The Laws of Physics (optional)
-Vector Calculus (optional)

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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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Postgraduate degree programme in Financial Engineering Masters/MSc. Read more

Postgraduate degree programme in Financial Engineering Masters/MSc:

MSc Financial Engineering is a multi-disciplinary field that involves the application of the computational engineering, software engineering, and computer programming skills, as well as the underlying mathematical and statistical theories to the analysis and management of financial opportunities. Students will receive the most advanced computational and programming techniques which help them advance quickly in the field.

Course details

Financial engineering is a multi-disciplinary field that involves the application of computational engineering, software engineering, and computer programming skills, as well as the underlying mathematical and statistical theories to the analysis and management of financial opportunities. 

The programme is for strong (1st, 2.1 or equivalent) graduates from programmes in mathematics, or programmes with advanced mathematical components, and who wish to pursue a career in quantitative analysis in economic or financial sectors with state-of-art mathematical methods, computational skills and programming expertise.

Related links

Learning and teaching

In the Autumn and Spring semesters, you will take masters-level courses in both computational methods and programming and statistical methods in economics, as well as computer science courses such as the Computer Science Workshop, in addition to the core quantitative finance and further quantitative finance modules which are needed for a career in financial engineering and computational finance. 

In the summer you will undertake a project, working with research leaders in mathematics and computer sciences. This will provide directly relevant training for a career in academic, and quantitative analysis in financial industry. A key component will be training specifically in independent study and research, an essential skill for quantitative analyst.

Employability

Career opportunities

This programme gives an ideal preparation for a career in quantitative analysis in economic or financial sectors with state-of-art mathematical methods, computational skills and programming expertise. The School’s graduates work in a wide variety of fields in governmental and multi-national organisations.

University Careers Network

Preparation for your career should be one of the first things you think about as you start university. Whether you have a clear idea of where your future aspirations lie or want to consider the broad range of opportunities available once you have a Birmingham degree, our Careers Network can help you achieve your goal.

Our unique careers guidance service is tailored to your academic subject area, offering a specialised team (in each of the five academic colleges) who can give you expert advice. Our team source exclusive work experience opportunities to help you stand out amongst the competition, with mentoring, global internships and placements available to you. Once you have a career in your sights, one-to-one support with CVs and job applications will help give you the edge.

If you make the most of the wide range of services you will be able to develop your career from the moment you arrive.



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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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