MSc Quantitative Finance (MSc QF)
A one-year cross-faculty masters combining probability, statistics and finance with computing. The compulsory core covers financial stochastic processes and big data technologies, with electives spanning derivatives, portfolio theory, econometrics and machine learning, followed by a research project.
What you’ll study
Core
- Foundations of Probability & Statistics
- Principles of Finance
- International Financial Markets & Banking
- Big Data Technologies
- Financial Stochastic Processes
- Quantitative Finance Research Project
Electives
- Behavioural Finance
- Fixed Income Analysis
- Equity Analysis
- Portfolio Theory & Management
- Derivatives & Treasury Management
- Financial Econometrics
- Statistical Machine Learning
- Database & Web Systems Development
- Machine Learning for Data Analytics
- Evolutionary Computation for Finance
Source: strath.ac.uk ↗
Before you apply
- Background
- Minimum second-class Honours in engineering, science or business subjects (maths/statistics graduates should contact the course director)
- Maths
- calculus; linear algebra; differential equations; probability; statistics
- English
- IELTS 6.0 overall, no component below 5.5
- Other
- Relevant experience or professional qualifications also considered
Source: strath.ac.uk ↗
After graduation
- Typical first roles
- Risk Officer, Trainee Actuarial Analyst, Business Change Consultant, Management Trainee
- Employers
- Deloitte, PwC, Bank of Ireland, BlackRock
Source: strath.ac.uk ↗
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What students and graduates say
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- University of Strathclyde - MSc in Quantitative Finance (QuantNet resource page, no review text) (QuantNet)
Page currently shows September 2027 entry. No programming prerequisite published. No employment rate or salary published (page includes only a generic 2023 data-role salary table).
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.