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Course content

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

Objectives

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.

Structure

  • You will have gained 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
  • You will have three different possibilities to complete your degree in the third term, including writing a dissertation or an applied project. You can also opt to gain 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 Quantitative 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 MSc in Quantitative Finance starts with two compulsory induction weeks, mainly dedicated to:

  • 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 refresher course of advanced financial mathematics, statistics, computing and electronic databases

Career pathways

The job opportunities for students from the three quants masters programmes are very similar. similar. They usually find employment with large investment banks, but also some smaller boutique finance firms, hedge funds or other specialist companies.

Working as a general or technical analysts, risk management position, working on fixed income security desks and the asset management industry including hedge funds are typical jobs which students from the MSc Quantitative Finance go into. Energy companies, such as Npower, have also recruited quants students. Students from the MSc Quantitative Finance will have covered more topics relating to forecasting and regression analysis.

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


Visit the Quantitative Finance (MSc) page on the Cass Business School website for more details!

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