Mathematics & Statistics - Financial Mathematics

MSc Financial Mathematics
Graduate Taught (level 9 NFQ, credits 90)
The MSc Financial Mathematics (PT) is designed for students who wish to gain a competitive advantage in the financial sector by acquiring the background demanded by upper-level quantitative roles. The programme will provide high-level instruction in the mathematical theory underlying finance and associated computational and statistical methods.

It features an inter-disciplinary suite of traditional and online modules that address contemporary topics in financial mathematics. It concludes with a summer work placement opportunity that enables students to apply their newfound theoretical knowledge and digital skills, and develop key professional and transversal skills.

In the Autumn and Spring Trimesters, you will take a mixture of face-to-face and online modules (indicative module list below). In the Summer Trimester, you will have the opportunity to take up a summer work placement with a Dublin-based financial firm, or a dissertation supervised by a member of faculty. Upon completion of the programme, you will be able to understand, critique and judge the suitability of a number of advanced financial mathematical models, manipulate, analyse and discern the reliability of financial data sets, and be acquainted with industry practice.

Who should apply?
Part Time option suitable for:

Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes

Subjects taught

Core modules:

Stochastic Calculus
Advanced Financial Models
Counterparty Credit Risk
Computational or Advanced Computational Finance

Optional modules include

Financial Risk Measurement and Management
Statistical Machine Learning
Time Series Analysis
Data Programming with Python
Data Programming with R
Categorical Data Analysis
Measure Theory and Integration
PDEs in Financial Maths
Microeconomics in Business
Foundations of Finance
Behavioural Economics
Energy Economics and Policy

Stage 1 Options

Computational FinanceACM30070
PDEs in Financial MathsACM30080
Scientific Programming Concepts (ICHEC)ACM40660
Optimisation in MLACM40990
Introduction to Relational Databases and SQL ProgrammingCOMP40725
Big Data ProgrammingCOMP47470
Energy Economics and PolicyECON42360
Behavioural EconomicsECON42560
Advanced Econometrics: Time SeriesECON42710
Measure Theory & IntegrationMATH40430
Stochastic CalculusMATH40690
Fin.Risk Measurement & MngmtMATH40720
Counterparty Credit RiskMATH40730
Advanced Financial ModelsMATH40740
Financial Work PlacementMATH40750
Financial DissertationMATH40760
Data Programming with R (Online)STAT40730
Statistical Machine Learning (online)STAT40750
Data Prog with Python (online)STAT40800
Bayesian Analysis (online)STAT40850

Entry requirements

The minimum entry requirement will be a 2:1 (or equivalent grade) BSc in Financial Mathematics, Mathematics, Applied and Computational Mathematics, or Statistics.

Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element), or equivalent.

Students meeting the programme's academic entry requirements but not the English language requirements, may enter the programme upon successful completion of UCD's Pre-Sessional or International Pre-Master's Pathway programmes.

Please see the following link for further information

Application dates

The following entry routes are available:

MSc Financial Mathematics PT (T349)
Duration 2 Years
Attend Part Time
Deadline Rolling*

* Courses will remain open until such time as all places have been filled, therefore early application is advised


2 years part-time

Post Course Info

Graduates with training in Financial Mathematics can cover upper-level quantitative roles in
several sub-sectors such as:
- Quantitative analysis in financial firms and hedge funds
- Risk modelling in banking and insurance
- Computational modelling in fintech
- Research and academia

More details
  • Qualification letters


  • Qualifications

    Degree - Masters (Level 9 NFQ)

  • Attendance type

    Part time

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    Course provider