Course summary
Through this course of study, you will develop:
- A deep understanding of financial markets
- A cutting-edge preparation on machine learning methods and their use for financial applications
- Programming skills with state-of-the-art languages such as Python and R
- The ability to implement a systematic and independent assessment of forecasting methods and their economic value
- A wide array of quantitative methods for the analysis of risks and returns within the context of investment decisions
Entry requirements
A 2:1 or above at undergraduate level in any subject, provided there is a strong quantitative background in Statistics and Mathematics.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Students enrolling on a postgraduate degree programme are charged tuition fees each year by Queen Mary. The rate you will be charged depends on whether you are assessed as a Home/EU or Overseas student.
You can find tuition fees for each course on the course finder pages on our website by clicking the apply link, or navigate here: https://www.qmul.ac.uk/postgraduate/
Further details about postgraduate taught tuition fees can also be found on our website: https://www.qmul.ac.uk/postgraduate/taught/tuitionfees/
Provider information
Queen Mary University of London
Admissions and Recruitment Office
Mile End Road
Tower Hamlets
London
E1 4NS