Financial Mathematics & Analytics

Quick Programme Summary

Description

The programme has been developed into a focussed mathematical programme that addresses the central needs and skills that employers require in the financial sector.  It combines elements of financial mathematics, statistics and modelling, together with the technical skills to perform the analytical requirements particular to the financial and business sectors.

Students acquire ICT skills and knowledge that is pertinent and focused towards their use in the workplace.  The programme encourages the development of self-directed, independent learning and research skills.  The ability to communicate and present their understanding and knowledge to both a technical and general audience is also developed through the use of presentations and feedback sessions.

Applicants will be from those with previous qualification in all areas of engineering (including engineering within the construction/craft industries) and IT looking to re-skill into the area of financial mathematics. Business and/or economics graduates are also a target group with a view to up-skill those with some experience in financial analytics or to re-skill into that area. 

Content

Modules comprising 45 ECTS credits, consisting of:

• Financial Mathematics (15 ECTS credits)
• Case Studies in Financial Mathematics (15 ECTS credits)
• Regression Models I (5 ECTS credits)
• Queueing Theory & Markov Processes (5 ECTS credits)
• Industrial and Commercial Statistics (5 ECTS credits)

How to apply

Applications are made via the DIT part-time programme application Form.   Completed application forms to be submitted by:

Email: joe.condon@dit.ie , OR

Post: Joe Condon, School of Mathematical Sciences, DIT, Kevin Street, Dublin 8. 

Entry Requirements

Entrants should hold a NFQ level 7 or higher qualification in any subject area which included a substantial mathematics component (or equivalent) and satisfy the Programme Committee that they have prior learning sufficient for a level 8 qualification in mathematics. The Institute guidelines for the Recognition of Prior Learning (RPL) will be applied. Applications will be assessed individually based upon examination results, transcripts from previous study and evidence of certificated/non-certificated additional learning.

Examinations / Assessments

End of Semester examinations twice a year in January and May/June.  Continuous Assessments for some modules throughout the academic year.

Progression

Further part-time or full-time study of mathematical sciences to honours degree and postgraduate level.

Learning Outcome

On successful completion of the programme, the student will have gained the following:

• have a good understanding of the mathematical models and methodologies used by quantitative analysts working in hedge funds and investment banks
• be able to confidently apply their knowledge of Markov processes and stochastic calculus to applications in finance
• be able to use statistical models to analyse datasets commonly encountered in the financial sector.

Career Opportunities

Graduates of this programme will have access to many areas of the job market in the financial sector. Potential employers include investment houses, private and state asset management organizations, insurance and reinsurance companies, as well as traditional banks and banking regulation bodies.

Back to Top