Taught course

Quantitative Finance

City, University of London · Cass Business School

Entry requirements

  • A UK upper second class degree or above, or the equivalent from an overseas institution.
  • Your academic background should be in a highly quantitative subject such as mathematics, physics, engineering, economics or computer science and having covered areas such as statistics, linear algebra and calculus.

Months of entry


Course content

Learn technical and practical skills useful in pursuing a career in front or middle office positions.

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, including the more technical and mathematical techniques used in financial markets; but you don’t need to have a background in finance.

You’ll study core modules focusing on asset pricing, risk management and introductions to key financial securities such as equities, fixed income securities and derivatives. From there you’ll progress to specialist learning in econometrics, and cover a large amount of stochastics and numerical methods.

You’ll cover basic and advanced topics in econometrics including ARCH and GARCH models, co-integration and dealing with high frequency data. You will also have the opportunity to work with a number of different estimation techniques, including OLS, Maximum Likelihood and GMM.

You’ll work extensively with the Matlab programming language in the core modules alongside other languages such as VBA, Python or C as optional modules. You’ll choose five from around 40 optional modules in your final term. You can also choose to complete a traditional dissertation, which counts for four optional modules, or a shorter ‘applied research project’, which is the equivalent of two optional modules.

Qualification and course duration


full time
12 months

Course contact details

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