Financial & Computational Mathematics
Our postgraduate Financial and Computational Mathematics programme equips graduates with the skills necessary to pursue a successful career in quantitative finance.
| Award Name | Degree - Masters (Level 9 NFQ) |
|---|---|
| NFQ Classification | Major |
| Awarding Body | National University of Ireland |
| NFQ Level | Level 9 NFQ |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
|---|---|---|---|
| Degree - Masters (Level 9 NFQ) | Major | National University of Ireland | Level 9 NFQ |
Duration
1 year full-time.
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 Coordinator.
Careers / Further progression
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.
Further information
Start Date 9 September 2024
Closing Date
Rolling deadline. Open until all places have been filled. Early application is advised.
Course Outline
Our postgraduate Financial and Computational Mathematics programme equips graduates 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. This course provides a solid grounding in computational finance along with machine learning techniques and includes a team-based research project with opportunities to work with our industry partners.
Programme Structure
Part I (60 credits)
Core Modules (45 credits)
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 (30 credits)
MF6016 Dissertation in Financial and Computational Mathematics (30 credits)
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.
Contact details for this course
Dr Cónall Kelly
conall.kelly@ucc.ie
+353 (0)21 420 5819
https://www.ucc.ie/en/matsci/
Dr Tom Carroll
t.carroll@ucc.ie
+353 (0)21 420 5819