- Start date: September
- Study mode and duration: 12 months full-time
Placements: industry placement possible during semester 3
Study with us
- gain an understanding of financial theory and analysis, financial markets, numerical methods in finance, and programming for financial applications
- designed with input from the finance industry
- opportunity to undertake industry-based project
Why this course?
The MSc in Quantitative Finance has been developed to address the demand for market-aware graduates who can demonstrate an understanding of mathematical models used in financial tools, products and software.
The course is an innovative cross-faculty alliance between Strathclyde Business School and the Faculty of Science. It's been designed for those with a strong aptitude for mathematics, statistics and computing who haven't studied these topics in detail in their undergraduate degree. The course allows students with different degree backgrounds to learn the necessary skills to move into the financial industry.
The programme will prepare you for a career in financial engineering and risk management leading to roles as a hedge fund manager or financial analyst.
What you’ll study
The curriculum provides a balance between finance and mathematical theory, computer implementations of this theory, and practical skills and knowledge.
Core classes in Semester 1 address themes such as principles of finance and quantitative methods for finance, as well as foundation classes in mathematics, statistics and computing science. In Semester 2, you choose three optional classes.
On the programme you'll gain:
- good understanding of financial theory and analysis
- appreciation of financial markets
- practical understanding of numerical methods in finance
- introduction to programming for financial applications
- understanding of the role of computers in business processes
You may be able to undertake an industrial-based MSc project between June and September. The placement can be based in the UK or in another country and are typically paid internships.
Learning & teaching
Teaching is student-focused – we encourage you to take responsibility for your own learning and development. Classes are supported by web-based materials. We ensure class sizes allow for good contact between students and teaching staff.
Classes are delivered by a number of teaching methods:
- lectures (using a variety of media including electronic presentations and computer demonstrations)
- computer laboratories
The form of assessment varies from class to class and normally involves both coursework and examinations.
The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and access to University computing laboratories with all necessary software available.
You'll also have access to a common room which can be used for individual and group study work and is also a relaxing social space.
Students appreciate the fact that the cohort is small enough so that each of them receive a good service from our staff. They're also very happy with the facilities provided by the University.
Lecturer, Quantitative Finance
Foundations of Mathematical & Statistical Finance
The educational intention of this class is to bring all of the students up to the same level of mathematical and statistical training so that they can then undertake the financial theory classes in semester 2.
Principles of Finance
This class provides an introduction to the basic principles of financial decision taking and the theory of finance. It will develop the basic principles of valuation, the nature of risk and uncertainty, and the relationship between risk and returns. While the analysis will be developed in the context of corporate finance, looking at companies’ decisions on the investments in assets and how these investments will be funded and the nature of the markets in which they take place, it will also consider the principles underlying financial reasoning that can be applied on a more general basis.
Find out more in the class outline for Principles of Finance.
International Financial Markets & Banking
The aim of the class is to provide you with an understanding of the financial system and the roles and functions of financial markets and institutions. A particular emphasis is placed on understanding the roles of intermediaries such as banks and investment firms.
You'll develop an understanding of the various characteristics and roles of fixed income, equity, and foreign exchange markets. While some attention will be given to the UK financial markets, the global nature of financial markets will be widely discussed. This class aims to equip you with an awareness and understanding of financial markets and institutions in the context of the global economy. Particular emphasis will be placed on the role and contribution of the banking sector.
This class covers the reasons for, and nature of, of financial markets and institutions with a particular focus on banking, the global nature of these markets and their regulation.
Find out more in the course outline for International Financial Markets & Banking.
Big Data Technologies (20)
In this class you will learn to:
- understand the fundamentals of Python to enable the use of various big data technologies
- understand how classical statistical techniques are applied in modern data analysis
- understand the potential application of data analysis tools for various problems and appreciate their limitations
- be familiar with a number of different cloud NoSQL systems and their design and implementation, showing
- how they can achieve efficiency and scalability while also addressing design trade-offs and their impacts
- be familiar with the Map-Reduce programming paradigm
You're required to take 60 credits of optional classes from those listed below – 20 credits from each list.
The aim of the class is to provide you with an understanding of the main ideas of behavioural finance. A particular emphasis is placed on understanding the roles of non-rational actions and the development of new financial models that incorporate these ideas.
You'll engage with up to date research and develop a critical view of existing and new finance theories and models. It aims to introduce you to the rapidly evolving area of behavioural finance. You'll develop an understanding of behavioural finance and an appreciation of its possible implications and applications.
This class introduces you to behavioural finance and provides you with an understanding of the main flaws of 'traditional' finance theory from a behavioural finance viewpoint. It will allow you to develop the ability to discuss issues arising from violations of the rationality assumption and will enable you to evaluate new theoretical models based on research in psychology.
The course will allow you to appreciate the role of new developments in finance and their possible implications for established views of the functioning of financial markets.
Find out more in the class outline for Behavioural Finance.
The aim of this class is to develop an appreciation of the investment characteristics of different types of securities, particularly bonds and shares, and to develop an understanding of how such securities are valued. This class will build on the analysis developed in the first semester class, Principles of Finance. It will consider the determination of interest rates, the valuation of bonds, the management of bond portfolios, and the valuation of equities.
Find out more in the class outline for Security Analysis.
Portfolio Theory & Management
The aim of this class is to examine the Markowitz (1952) approach to optimal portfolio selection. The class explores issues relating to optimal portfolio choice and issues in practical fund management.
Find out more in the class outline for Portfolio Theory & Management.
Derivatives & Treasury Management
The aim of this class are to provide a strong grounding in derivatives that may be used to manage the financial risks faced by individuals, financial institutions and business corporations. It places an emphasis on corporate treasury management and the role of derivatives in managing treasury risk.
Find out more in the class outline for Derivatives & Treasury Management.
Database & Web Systems Development
This module aims to provide conceptual and practical understanding of data modelling, database design and database technology. It also aims to give practical experience of developing web-based applications that integrate database server interaction.
Machine Learning for Data Analytics
The aim of this class is to equip students with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how and when to apply the techniques. On completion of this class students will:
- understand the aims and fundamental principles of machine learning
- understand a range of the key algorithms and approaches to machine learning
- be able to apply the algorithms covered and interpret the outcomes
- understand the applicability of the algorithms to different types of data and problems along with their strengths and limitations
Evolutionary Computation for Finance
This module will help you to understand (a) nature of evolutionary computing (b) suitability of evolutionary computing for financial applications. It will provide practical experience in developing and operating evolutionary computing approaches for financial applications.
Financial Stochastic Processes
The class aims to expose you to a number of diverse topics in stochastic processes that can be used to model real systems, with an emphasis on the valuation of financial derivatives. In additional to theoretical analysis, appropriate computational algorithms using R are introduced.
You'll be exposed to a number of diverse topics in econometrics that can be used to model real financial data, with an emphasis on the analysis of financial time series. The statistical software R is introduced for financial modelling.
Networks in Finance
This module will introduce you to a number of diverse topics in game theory and its applications to financial problems as well as giving a sound background on network theory at both theoretical and applied level.
Compulsory module for students enrolled on the MSc.
Chat to a student ambassador
If you want to know more about what it’s like to be a Strathclyde Business School student at the University of Strathclyde, a selection of our current students are here to help!
Our Unibuddy ambassadors can answer all the questions you may have about their course experiences and studying at Strathclyde, along with offering insight into life in Glasgow and Scotland.Chat now!
Tran Ha Dung
The course has exactly what I was looking for, equipping myself with knowledge in finance, math, computer sciences as well as a quantitative set of skills to become a future quant.
Our programme leader helps us with everything. I feel very well prepared for entering the job market when I finish.
|Academic requirements / experience|
Minimum second-class Honours degree or international equivalent in:
Mathematics/statistics graduates should contact the course director to discuss their application.
Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply.
For Australia and Canada, normal degrees in relevant disciplines are accepted.
|Mathematical knowledge |
This MSc requires some prior mathematical knowledge for example:
If possible, please provide evidence of this in your application (eg transcript, certificate, etc)
Any queries, please email us: firstname.lastname@example.org
|English language requirements|
You must have an English language minimum score of IELTS 6.0 (with no component below 5.5).
We offer comprehensive English language courses for students whose IELTS scores are below 6.0. Please see ELTD for full details.
As a university, we now accept many more English language tests in addition to IELTS for overseas applicants, for example, TOEFL and PTE Cambridge. View the full list of accepted English language tests here.
Pre-Masters preparation course
The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non EU/UK) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.
Upon successful completion, you will be able to progress to this degree course at the University of Strathclyde.
We've a thriving international community with students coming here to study from over 100 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.Visit our international students' section
Fees & funding
All fees quoted are for full-time courses and per academic year unless stated otherwise.
|England, Wales & Northern Ireland|
Textbooks vary in price from around £40 to £100. The majority are provided free in the library or through MyPlace, our Virtual Learning Environment. We recommend that you allow £200 per academic year for books.
Students may be required to make hardcopy submissions for some assignments and will cover the cost of printing. Students are required to print and soft bind their project submission. An average cost would be in the region of £10.
Please note: the fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my course?
Scottish postgraduate students
Scottish postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.
Students coming from England
Students ordinarily resident in England may be to apply for postgraduate support from Student Finance England. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Wales
Students ordinarily resident in Wales may be to apply for postgraduate support from Student Finance Wales. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Northern Ireland
Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. The support is a tuition fee loan of up to £5,500. Find out more about the support and how to apply.
We've a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.
Glasgow is Scotland's biggest & most cosmopolitan city
Our campus is based in the very heart of Glasgow, Scotland's largest city. National Geographic named Glasgow as one of its 'Best of the World' destinations, while Rough Guide readers have voted Glasgow the world’s friendliest city! And Time Out named Glasgow in the top ten best cities in the world - we couldn't agree more!
We're in the city centre, next to the Merchant City, both of which are great locations for sightseeing, shopping and socialising alongside your studies.
Find out what some of our students think about studying in Glasgow!Find out all about life in Glasgow
We work closely with the University's Careers Service, which offers advice and guidance on career planning, and looking for and applying for jobs. In addition, they administer and publicise graduate and work experience opportunities.
Our graduates have gone on to find careers with companies such as Deloitte, PWC, Bank of Ireland and BlackRock, among others.
Job titles include:
- Business Change Consultant
- Advisor to CEO
- Manager Transfer Pricing Economist
- Risk Officer
- Trainee Actuarial Analyst
- Management Trainee
Entry level salaries for potential graduate roles
The table below shows average entry level salaries for potential graduate roles. Salaries shown are based on permanent roles and taken from analysis in the Harnham annual UK Data and Analytics salary guide for 2018 (download required).
|Big Data Engineering||£41K||£32K|
Professional network of graduates
We encourage Quantitative Finance students to join our closed group on LinkedIn. Graduates who are part of this group are able to take advantage of a read-made a professional network. We post jobs on the page, encourage interactions within the group and keep them up-to-date with relevant industry news.
This is a fantastic platform for someone starting out in the finance industry, with advice and networking opportunities from like-minded, established professionals at their fingertips. It's also a great way for you to keep in contact with others from your course.
Start Date: Sep 2021
Mode of Attendance: full-time
Have you considered?
We've a range of postgraduate taught and Masters courses similar to this one which may also be of interest.