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Masters Degrees (Quant)

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Programme overview. The Advanced Master in Quantitative Finance offers prospective students a rich curriculum combining finance, statistics, econometrics, programming and mathematics. Read more

Programme overview

The Advanced Master in Quantitative Finance offers prospective students a rich curriculum combining finance, statistics, econometrics, programming and mathematics. This Master guarantees a full coverage of financial disciplines, such as asset and derivative pricing, numerical methods and programming skills. This advanced course work is designed for students with a quantitative background, obtained either from recent education or through professional experience.

Programme objectives

The main objective of this master is to train a new generation of quants. You will gain cutting-edge knowledge in quantitative finance and will learn how to apply it to real-life problems.

You will not only be exposed to up-to-date models, but you will also understand their advantages and limitations, both in theory and in practice.

By the end of the year, you will be able to:

• Become an analyst and/or manager in a quant group

• Price equities and bonds

• Construct and programme structured products

• Perform tail-risk analysis

• Extract information from massive databases

• Understand and trade in complex derivative products such as volatility derivatives

Job opportunities

The obvious companies for such profiles are large financial institutions, private banking, and hedge funds, seeking to fulfil positions like quant team member, risk manager, quant analyst/risk modeller, asset liability manager, derivatives specialist, financial supervisor and product structure.

Geographically, job opportunities are not only concentrated to Europe, in particular London, Paris, Amsterdam, Frankfurt, and Zurich, but are extended to the rest of the world (e.g. Singapore, Hong Kong and New York).

However, to successfully grow in your professional life and make the right choices for your career, it is fundamental to define your goals and have the tools to achieve them. The Solvay Brussels School’s career service will help you in building your career thanks to its strong connection with the business sector and to its dynamic team who will accompany each participant into the professional world. From self-assessment to networking opportunities, our team will assist participants to realise their full potential. Through a full range of seminars, coaching sessions, workshops, events and other resources, we help our participants to discover the career path best suited to their personal fulfilment.

Interested? Visit http://am.solvay.edu/quantitative-finance/

Application Deadline

> Non-EU students: May 31st 2018 (recommendation related to visa procedures)

> EU students: July 15th 2018



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

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

About this degree

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

Students undertake modules to the value of 180 credits.

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

Core modules

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

Optional modules

Students select 60 credits from optional modules.

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

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

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

Dissertation/report

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

Teaching and learning

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

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

Careers

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

Employability

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

Why study this degree at UCL?

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

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

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

Research Excellence Framework (REF)

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

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

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



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

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

Core Modules

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

Elective Modules

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

What are my career prospects?

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

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

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2-year Master’s programme that gives students strong preparation in contemporary economic theory and econometric analysis methods enabling them to analyze and forecast economic processes;. Read more
• 2-year Master’s programme that gives students strong preparation in contemporary economic theory and econometric analysis methods enabling them to analyze and forecast economic processes;
• Good skills in economic theory and econometric methods and training in solving real life problems using state-of-art economic analysis techniques;
• Internationally competitive economic education: lectures from TOP international economics PhD programmes and leading economists in Estonia;
• Research experience or apprenticeship training in Estonian financial and public sector institutions;

Tuition fee: 3200 EUR/year. Tuition-waiver scholarships available.

More info: http://www.ut.ee/quant

Application deadline: April 16

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The objective of the Specialised Programme in Quantitative Finance is to train top level specialists able to advance in today’s global financial sector characterised by constant change and continuous innovation. Read more
The objective of the Specialised Programme in Quantitative Finance is to train top level specialists able to advance in today’s global financial sector characterised by constant change and continuous innovation.

This 12-month programme has been developed to help graduates from engineering schools and universities, possessing a strong background in mathematics, computer science, physics and similar areas of expertise, launch their career in quantitative finance. After completing this specialised programme, graduates take up various positions like Risk Manager, Financial Engineer or ‘Quant’, Asset Manager, Fund Manager and others.

The academic courses include both the fundamentals of management as well as specialised courses like quantitative methods, economic and financial environments, life insurance and pension funds management. This academic part is complemented by a 6 month period in-company.

The Specialised Programme in Quantitative Finance takes place in our campus in Paris.

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