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MSc Computational Finance

  • DeadlineStudy Details:

    MSc 1 year full-time

Course Description

Help build a successful career as a quantitative analyst on this one-year MSc programme in Computational Finance. You'll benefit from UCL’s renowned expertise in computational statistics and machine learning to acquire the advanced quantitative, modelling and programming skills essential for ‘quant’ roles in trading, research, regulation and risk management.

As the financial sector becomes increasingly sophisticated, there is a growing demand for experts with skills spanning mathematics, finance, statistics, and computer science. 

Join us on this fast-paced MSc to lay the groundwork for a fulfilling career as a quantitative analyst or quant in just a year.

You join the UCL Computer Science community — a world-renowned centre in computational statistics and machine learning — to learn advanced quantitative, modelling and programming skills alongside our experts. 

The syllabus is constantly reviewed to stay ahead of trends. Modules include financial engineering, numerical methods, data science, and machine learning for finance, with optional modules in algorithmic trading, market microstructure, numerical optimisation, networks and systemic risk, and blockchain technologies. 

This programme is distinctive in that it covers a mix of mathematics, finance, statistics and computer science. Computational finance sits at the intersection of these subjects. Elevating your skills in all these areas will put you one step ahead when going for quant jobs.

Entry Requirements

A minimum of an upper second-class UK bachelor's degree (or international qualification of an equivalent standard) in a relevant discipline with a strong quantitative component evidenced by good performance in mathematics and statistics exams, i.e. with marks in these subjects not below a UK upper second-class or international equivalent level. There is not an exhaustive list of relevant disciplines, but individuals with a background in mathematics, physics, statistics, computer science, engineering, economics, or finance are encouraged to apply.

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Fees

For fees and funding options, please visit website to find out more.

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

You can expect to acquire a combination of highly sought-after skills currently needed in the financial industry on this programme, which embraces mathematics, statistics, finance and computer science in equal measure.

You will graduate with advanced quantitative, modelling and programming skills, which are essential for ‘quant’ roles in trading, asset allocation, risk management, fintech, regulation and research.

Module Details

Compulsory modules

  • Numerical Methods for Finance
  • Data Science
  • Financial Engineering
  • Machine Learning with Applications in Finance
  • MSc Computational Finance Project

Optional modules

  • Applied Computational Finance
  • Probability Theory and Stochastic Processes
  • Networks and Systemic Risk
  • Market Microstructure
  • Algorithmic Trading
  • Financial Market Modelling and Analysis
  • Financial Institutions and Markets
  • Market and Credit Risk
  • Advanced Machine Learning in Finance
  • Blockchain Technologies

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