Financial and Computational Mathematics

Our postgraduate Financial and Computational Mathematics programme equips graduates in mathematics, physics, or engineering with the skills necessary to pursue a successful career in quantitative finance. Modern financial technology is based upon sophisticated computational techniques for the modelling of asset and market movements, and the valuation of financial derivatives. Employers actively seek graduates with an understanding of the mathematical background as well as the computational skills needed to apply it; this course provides a solid grounding in both these disciplines and includes a team-based research project with opportunities to work in partnership with the industry.

Why Choose This Course
Employers in the banking and investment sector require graduates with a deep understanding of the relevant mathematical concepts as well as the practical and computational skills associated with applying them. This course provides both, and is an opportunity for students pursuing mathematical degrees that are not specifically financial in nature to continue to studies in advanced mathematics with a financial focus, and therefore enhance their employment options.

UCC itself enjoys proximity to financial employers in Ireland (for example the International Finances Services Centre [IFSC] in Dublin) and in other European financial centres, including London.

Connected Curriculum

Our learning approach reflects our commitment to the Connected Curriculum where we emphasise the connection between students, learning, research and leadership through our vision for a Connected University. Our staff are at the forefront of this integrative approach to learning and will support you in making meaningful connections within and between topics such as mathematics, finance, and technology.

Available Scholarships

We support our postgraduate community by offering scholarships and bursaries to prospective and current students. Please see the SEFS Scholarships and Funding PG page for more information.

Entry requirements

- Candidates must have obtained at least a 2.2 degree or equivalent in the mathematical sciences or another quantitative subject.
- Candidates who have obtained at least a 2.2 honours degree in Engineering or Physics will be considered and should be able to demonstrate to the Course Coordinator some prior experience of probability and statistics, linear algebra, multivariate calculus, ordinary differential equations, and programming.
- Candidates, for whom English is not their primary language, should possess an IELTS of 6.5 (or TOEFL equivalent) with no less than 6.0 in each individual category.
- All candidates must be ultimately approved by the Course Co-ordinator.
- Overseas applicants who wish to study in Ireland should consult the Department of Justice Study in Ireland webpage at: https://www.irishimmigration.ie/coming-to-study-in-ireland/.

English Language Requirements

Applicants that are non-native speakers of the English language must meet the university approved English language requirements available here.

For applicants with qualifications completed outside of Ireland

Applicants must meet the required entry academic grade, equivalent to Irish requirements, please find our grades comparison by country here.

International/non-EU applicants

For full details of the non-EU application procedure please visit our how to apply pages for international students. In UCC, we use the term programme and course interchangeably to describe what a person has registered to study in UCC and its constituent colleges, schools, and departments.

Not all courses are open to international/non-EU applicants, please check the fact file above.

For more information please contact the International Office.

Assessment Info

A variety of assessment methods are used during this course. In addition to the traditional end-of-year written examinations, you will undertake a series of individual and group assignments and projects during the year in the areas of both management accounting and information systems.

In addition, an applied research project is undertaken in groups by all students during the second teaching term, culminating with a series of group presentations to leading industry experts who in turn provide invaluable feedback and advice to each student group.

The IS6215 Business Research and Communications Skills module (10 credits), which forms part of the course syllabus, is an invaluable tool for you in preparing for such presentations.

Subjects taught

Programme Structure

Part I of the programme comprises 60 credits of taught modules.
Part II comprises a dissertation in Financial and Computational Mathematics worth 30 credits.

Part I
Core Modules
MF6010 Probability Theory in Finance (10 credits)
MF6011 Derivatives, Securities, and Option Pricing (5 credits)
MF6012 Computational Finance I (5 credits)
MF6013 Computational Finance II (5 credits)
MF6014 Topics in Financial Mathematics (5 credits)
MF6015 Continuous-Time Financial Models (5 credits)
AM6004 Numerical Methods and Applications (5 credits)
CS6322 Optimisation (5 credits)

Elective Modules (Choose 15 credits)
AM4062 Applied Stochastic Differential Equations (5 credits)
AM6007 Scientific Computing with Numerical Examples (5 credits)
AM6019 Partial Differential Equations (5 credits)
ST4400 Data Analysis II (5 credits)
ST6040 Machine Learning and Statistical Analytics I (5 credits)
ST6041 Machine Learning and Statistical Analytics II (5 credits)
CS6503 Introduction to Relational Databases (5 credits)

Part II
MF6016 Dissertation in Financial and Computational Mathematics (30 credits)
Note: Module selection must be approved by the module coordinator.

You can find the full academic content for this programme at University Calendar (Financial & Computational Mathematics).

Modules
Further details on the modules listed above can be found in our book of modules. Any modules listed above are indicative of the current set of modules for this course but are subject to change from year to year.

University Calendar
You can find the full academic content for the current year of any given course in our University Calendar.

Duration

1 year

Enrolment dates

Start Date 7 September 2020

Post Course Info

Skills and Careers Information
Graduates will be prepared for quantitative roles in the financial services sector and particularly in investment banking, including roles in financial engineering, quantitative finance, investment analysis, and fund management. The programme also serves as a route to further study in this area.

Career Opportunities
Past graduates of this programme have been recruited to roles in quantitative finance (China Reinsurance Corporation, Quaternion Risk Management/Acadia Inc., Kroll Bond Ratings Agency), and some have moved on to SFI-funded study at PhD level in the application of machine learning to finance. This programme will prepare you for a broad selection of roles in the financial services sector and particularly in quantitative finance, financial engineering, and investment analysis.

More details
  • Qualification letters

    MSc

  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Full time,Daytime

  • Apply to

    Course provider