Ambitious students with an educational background in Economics, Finance or STEM (Science, Technology, Engineering, and Mathematics) subjects and with a proven quantitative talent will be ideally suited to this programme.
This course covers a broad range of subjects related to the mathematical modelling of financial markets and the pricing and hedging of financial securities. The course equips you with the necessary theoretical, mathematical and computational skills needed to pursue a career in quantitative finance. If you are a competitive student looking for a career in finance that will use your quantitative talents to the full, this is the course for you.
For graduates wishing to pursue further the theoretical dimension of the discipline, the curriculum content provides the perfect basis for a PhD in Finance.
The course was awarded Risk Management Accreditation by the Professional Risk Managers International Association (PRMIA), confirming the suitability of the course for preparing graduates for a career as professional risk managers. Graduating students obtain exemptions to PRMIA level 1 and 2 exams.
The programme can be undertaken on a part-time basis, thus enabling current professionals with the relevant background to combine working life with study, however, this is dependent on students’ employment commitments. Note that this is not a dedicated part-time programme and that students will be required to attend lectures, tutorials and complete group assignments in conjunction with the full-time cohort, for whom the schedule is primarily during working hours for a block of hours on several days a week. Modules in the autumn trimester will be delivered in a compressed format meaning that modules are taught intensively over two 6-week periods, requiring additional attendance at lectures and tutorials. Employer support is therefore essential.
Quick Facts
12 Months Full-Time Programme Duration
100% Employed After 6 Months
24 months Part-Time Programme Duration
End August 2023 Starting
Vision and Values Statement
The MSc Quantitative Finance programme is aimed at students with a background in an economics, finance or mathematics-related discipline to prepare students for a specialist career in the financial services industry as a quantitative analyst or risk manager. The purpose of the programme is to provide mathematically talented students with the knowledge and capacity to be experts in financial decision-making under uncertainty using financial economics, mathematics, statistics and computer technology skills (Purpose).
The educational values of the programme are to provide students with the knowledge and capacity to: be experts in financial decision-making under uncertainty using financial economics, mathematics and computer skills; be producers as well as informed users of financial models used to aid decision making; critically evaluate these financial models, understanding their uses as well as their limitations; appraise, evaluate and manage financial risk and return; and to manage portfolios of equity, fixed income, foreign exchange, derivatives, commodities and energy securities. The programme is externally accredited by a major international risk management organization (education and subject/discipline/professional values).
The learning environment consists of both theoretical and applied components. The theory in lectures is further enhanced with specific examples in small group tutorials. The applied projects covered in lectures are further developed as an autonomous group or individual projects using state of art financial databases available in our data room. An internship option is also integrated into the programme (the nature of the learning environment for students).
The programme uses teaching, learning and assessment approaches such as presentations, project work, decision-making analysis, work placements, group work, case studies, and examinations and includes many stakeholder groups and individuals in the design and delivery of the curriculum (key approaches to teaching, learning and assessment).
