The MSc Finance and Trading programme equips you with the skills needed for investing in financial markets. You will gain expertise in financial theory, quantitative analysis, and trading strategies, using professional-grade tools. Students will learn about how to price assets, manage risk, and the structures involved with trading in stock markets, derivative exchanges, and in foreign exchange.
Queen’s University is ranked third in the UK for Graduate Prospects in Finance.
(Times and Sunday Times Good University Guide 2025)
Finance and Trading highlights
World Class Facilities
Queen’s Business School (QBS) has recently undergone an innovative expansion that establishes a benchmark of global excellence for one of the top business schools in the UK and Ireland. A stunning new 6,000 square metre building, adjacent to the listed red-brick Riddel Hall has been designed with the latest digital infrastructure for media lecture capture, TED Talk provision and collaborative breakout sessions.
Fostering an enhanced social and educational experience the new state-of-the-art QBS venue boasts a 250-seat tiered educational space; 120-seat Harvard style lecture theatre; 150-seat computer laboratory; breakout study spaces; FinTrU Trading Room; a café, and a Business Engagement and Employability Hub.
The FinTrU Trading Room, which replicates New York and London trading environments, provides students with access to 26 Bloomberg terminals, trading simulations and other financial software.
The FinTrU Trading Room is embedded into taught programmes allowing students to relate real world news and market activity to economic and financial theory. The facility is also vital for supporting extra-curricular activities. https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/fintru-trading-room/
Career Development
Students may wish to join the Queen’s Student Managed Fund (QSMF) which provides students with the opportunity to manage and operate a real-money investment portfolio. Established in 2012, the fund transitioned to a real money fund in April 2016. Students currently manage funds of around £60,000 to £70,000 through one of our Gold Sponsors, Davy Group, Ireland's leading provider of wealth management, asset management, capital markets and financial advisory services. QSMF is also generously supported by Citco, the world's largest hedge fund administrator. https://www.qub.ac.uk/schools/queens-business-school/student-opportunities/qsmf/
Student Experience
Students will use and have access to software such as Bloomberg, CRSP, Compustat, DataStream and S&P Global Market Intelligence.
Students have the opportunity to hear from industry professionals who regularly deliver guest lectures. Students have the opportunity to network afterwards.
The MSc Finance and Trading is a full-time postgraduate programme primarily designed for students with undergraduate degrees in finance, mathematics, statistics, or other quantitatively intensive disciplines.
This programme offers an extensive array of in-depth modules, providing core knowledge of financial markets and financial instruments. Through eight taught modules, students acquire the essential skillset for responsible decision-making and promoting sustainable economic growth. These modules are aligned with the U.N. Sustainable Development Goals, directly mapping to selected goals to ensure a holistic and impactful educational experience.
Semester 1
Asset Pricing - FIN7026
This module offers an introduction to the field of financial economics and provides an understanding of the development of advanced pricing theory. The module starts by examining rational investor behaviour; how investors allocate resources both in certain and uncertain environments, building towards an understanding of how prices are rationally determined in asset markets. Apparent violations of rational behaviour and pricing are then examined to understand better how traders and markets function. Students will also explore portfolio allocation and examine a range of anomalies including the equity premium puzzle. The course concludes with an examination of the efficient market hypothesis and throughout, we shall critique key financial models and economic theory.
Financial Data Analytics - FIN9008
The purpose of this course is to provide a comprehensive introduction to econometric techniques used in finance. It contains a treatment of classical regression and an introduction to time series techniques. There will be an emphasis on applied work using econometric packages. The course is designed to give students both theoretical and practical experience of statistical and econometric techniques. A wide range of topics is typically covered including the basic regression model, which includes a discussion of the classical violations of this model and methods for their correction. Students will learn a computer statistical software package (R).
Financial Market Structure - FIN7027
The first part of this module provides a detailed analysis of the contemporary structure of global finance including key market participants and markets, focusing on fixed income and foreign exchange markets. We will then explore the economic issues and structures underlying trading on these markets. The aim of this module is to ensure that students understand the structure, dynamics and trading mechanisms of global financial markets, as well as appreciate the role of key institutions involved in these markets.
Foundations of Risk Management - FIN7021
This module considers both risk and regulation in financial services. With regard to risk the module introduces students to the risks that institutions must take if they are to survive and prosper including market risk, credit risk, liquidity risk and operational risk. Emphasis is on the quantification of these risks, decisions about what level of such risks are acceptable and the action required to mitigate unacceptable levels of risk
Semester 2
Derivatives - FIN9007
The aim of this course is to develop in students a theoretical and practical knowledge of derivative instruments. The learning outcomes include understanding the mechanisms of futures and forward markets, pricing futures and forward instruments, constructing hedges using futures, and understanding the mechanisms of option markets. Additionally, the concepts of stochastic processes and its applications in financial modelling is addressed.
International Finance - FIN9004
The main goal of this course is to understand the complexities involved in conducting finance across more than one country. It aims to provide students with both practical skills for working in this area and a broader understanding of the role of finance within the international economy. The majority of the course will involve the description of key analytical concepts and theories involved in international finance. These theories are then used to help understand the international elements of important economic and financial phenomena.
Advanced Financial Data Analytics - FIN7028
Statistics is the science of uncertainty and variation. Econometrics is the application of statistics to economic and finance problems. The aim of this course is to teach students to apply time series financial econometrics techniques sensibly in the context of real-world empirical problems. Using the R statistical programming software and RStudio, students will be taught statistical techniques which underpin quantitative investigation in finance.
AI & Trading - FIN7030
This module will introduce the modern practices in finance of using algorithms to extract computer-age statistical inference. The goal is to introduce the emerging field of Financial Machine Learning as a complement to traditional financial research techniques.
Semester 3
Choose 1 of:
Applied Research Project – FIN9100
For those pursuing roles in the financial industry, the applied research project will be of significance. The module will review methods of company analysis, financial analysis, and various approaches to equity valuation. Students will have the opportunity to conduct independent research, undertake a valuation exercise, present their findings in a written report of industry standard and articulate their views in a presentation.
Dissertation – FIN9098
For those intending to pursue an academic career or a research focused role the dissertation is an appropriate choice. For high performing students. The aim of the dissertation is to provide students with the skills needed for conducting theoretical and/or empirical research in finance. Meanwhile, students will be assigned an academic supervisor and will complete an independent piece of academic scholarship.
The program will equip you with cutting-edge quantitative and computational analytical skills demanded by leading firms worldwide. It prepares you for future careers in quantitative finance, trading, general finance, FinTech, and business consulting environments. Bridging the gap between quantitative models and financial decision-making, many modules emphasize learning through simulation. This approach ensures that you gain practical, hands-on experience, aligning theoretical knowledge with real-world applications, and making you adept at navigating the complexities of the global financial landscape.
Assessment
Assessments associated with the course are outlined below:
Assessment is by a variety of methods,
including individual coursework, group work, presentations, simulations, case studies,
class tests, examinations and a dissertation
or applied research project.
The information provided in this Course Finder reflects the module details for the current year of study (2025/26). Please note that modules are subject to annual review and changes may occur in response to various factors, including student feedback and academic developments. Prospective students will be notified of any significant changes to module offerings before the start of the new academic year.
The applied research project provides students with the opportunity to utilise the knowledge and skills acquired over the previous two semesters to plan, develop and produce a substantial piece of original, independent applied research.
Lectures and computer-based workshops will cover the following areas:
1. Research Methodology
2. Fundamental analysis and strategy analysis
3. Data Management, Analysis, Visualisation and Inference
4. Financial analysis [ratios/cash flows], forecasting profit & EPS.
5. Valuation 1: DDM and DCF approach
6. Valuation 2: EVA and Price- multiples
7. Critical assessment of model adequacy
8. Presenting Information and Data
Learning Outcomes
Upon successful completion of this project, students will:
1. Demonstrate an ability to design and manage a piece of individual research.
2. Apply knowledge and skills developed in previous modules to contemporary issues in financial markets.
3. Establish links between financial theory and financial practice.
4. Exhibit intellectual discipline in identifying and critique the appropriate information.
5. Identify appropriate econometric methods for critically analysing a contemporary issue in finance.
6. Critically evaluate the appropriateness of modelling assumptions.
7. Present their thinking in a professional industry-style research paper.
Skills
This applied research project provides opportunities for the student to acquire or enhance the following skills:-
· Subject-specific skills
-Use of computer-based packages to analyse and evaluate relevant data
-Ability to critically read and evaluate finance and risk-related academic literature
-Appreciation, construction and analysis of financial and economic models of practical risk situations
· Cognitive Skills
-Problem solving
-Logical reasoning
-Independent enquiry
-Critical evaluation and interpretation
-Self-assessment and reflection
-Intellectual humility
-Intellectual discipline
· Transferable Skills
-The ability to synthesis information/data from a variety of sources
-Preparation and communication of ideas in both written and presentational forms
-Ability to work both independently
-Organisation and Time Management
-Use of IT
The purpose of this course is to provide an introduction to econometric techniques used in finance. It contains a treatment of classical regression and an introduction to time series techniques. There will be an emphasis on applied work using econometric packages.
The course is designed to give students both theoretical and practical experience of statistical and econometric techniques. A wide range of topics is typically covered including the basic regression model, which includes a discussion of the classical violations of this model and methods for their correction. Students will learn a computer statistical software package (R).
Learning Outcomes
Upon successful completion of this course students will have an understanding of:-
• the main issues relating to the appropriate econometric modelling of financial and economic time series;
• and have gained experience in the use of econometric software and be able to demonstrate their software skills in completing assignments;
• and be able to discuss, applied econometric research topics in finance;
• and have improved their data management, programming and research skills.
Skills
Subject-specific Skills
• The ability to construct arguments and exercise problem solving skills in finance
• The ability to use computer-based mathematical/statistical/econometric packages to analyse and evaluate relevant data
• The ability to read and evaluate finance and risk-related academic literature
Cognitive Skills
• Problem solving
• Logical reasoning
• Independent enquiry
• Critical evaluation and interpretation
• Self-assessment and reflection
Transferable Skills
• The ability to synthesise information/data from a variety of sources
• The preparation and communication of ideas in finance, information economics and risk management
• Organisation and time management
• Problem solving and critical analysis
• Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages
• The ability to communicate quantitative and qualitative information together with analysis, argument and commentary
The aim of this course is to develop in students a theoretical and practical knowledge of derivative instruments.
This module provides participants with an exhaustive coverage of widely used derivative products stressing pricing and uses for financial engineering and risk management. The module provides an overview of derivative instruments, markets, participants and uses. It focuses on the pricing and uses of futures, forwards and options. The cost of carry relationship, the binomial approach, the Black-Scholes model and its variants are detailed to equip participants with the basic tools for pricing derivatives. The module examines practical uses of derivative securities as risk management tools for corporations and financial institutions.
Areas to be covered include:
THE MOVEMENT OF FUTURES PRICES: some basic facts. CTAs, managed futures, hedge funds. Financialization of Commodity Markets. Time series momentum.
MEAN VARIANCE APPROACHES TO HEDGE RATIO DETERMINATION, STOCK INDEX FUTURES AND HEDGING EFFECTIVENESS: The mean-variance approach to hedge ratio construction. Hedging with stock index futures. Hedging effectiveness and hedge ratio estimation - OLS, ECM and GARCH procedures. Duration and Expiration effects.
THE STOCHASTIC PROCESS OF ASSET PRICES AND THE DERIVATION OF THE BLACK-SCHOLES MODEL:The Wiener process and rare events in financial markets; Ito processes; Ito's lemma; generalised Ito's lemma; Black-Scholes differential equation; Black-Scholes pricing formula; options on stocks paying known dividends; pseudo-American model; option on stock indices, currency options and options on futures;
VOLATILITY: Estimating volatility: historical; implied - application of Newton-Raphson. Empirical characteristics of volatility: smiles; term structure skew; mean reversion; Forecasting volatility: application of GARCH; empirical evidence of volatility forecasts - implied versus historical; Bisection.
EXOTIC OPTIONS: Types of exotic options - barrier options; lookback options; strike options; binary or digital options; compound options; and chooser options.
INTEREST RATE DERIVATIVES: The standard market models; models of short rate; HJM and LMM models.
RISK AND REGULATION WITH EMPHASIS ON VALUE AT RISK: Regulation of Financial Institutions; value at risk and forecast accuracy; capital adequacy and value at risk; value at risk and the variance covariance approach; value at risk and non-parametric methods such as historical simulation and bootstrapping; value at risk and linear and non-linear positions.
REAL OPTIONS: The option to expand, contract, default, abandon and switch. The valuation of real options in the face of compoundness, interaction between options and ownership. Real options and the valuation of internet companies.
Learning Outcomes
Upon successful completion of this module, students will have an understanding of:-
1. understand the mechanisms of futures and forward market
2. price futures and forward instruments
3. understand the mechanisms of options markets
4. understand concepts of stochastic processes and its application in financial modelling
5. understand and derive binomial tree model
6. understand and derive Black-Scholes-Merton model
7. estimate historical and implied volatility
8. construct hedges using futures and options
Skills
This module provides opportunities for the student to acquire or enhance the following skills:
Subject-specific Skills
• The ability to construct arguments and exercise problem solving skills in the context of theories of finance and risk management
• The ability to use computer-based mathematical / statistical / econometric packages to analyse and evaluate relevant data
• The ability to read and evaluate finance and risk-related academic literature
• The ability to appreciate, construct and analyse mathematical, statistical, financial and economic models of practical risk situations
• The ability to connect business problems with risk management
• The ability to marry regulatory structure with the principles of risk sharing and risk mitigation
Cognitive Skills
• Problem solving
• Logical reasoning
• Independent enquiry
• Critical evaluation and interpretation
• Self assessment and reflection
Transferable Skills
• The ability to synthesise information/data from a variety of sources including from databases, books, journal articles and the internet
• The preparation and communication of ideas in finance, information economics and risk management in both written and presentational forms
• The ability to work both independently and in groups
• Organisation and time management
• Problem solving and critical analysis
• Work-based skills; use of IT, including word-processing, email, internet and statistical/econometric/risk management packages
• The ability to communicate quantitative and qualitative information together with analysis, argument and commentary in a form appropriate to different intended audiences
The aim of this module is to ensure that students understand the structure, dynamics and trading mechanisms of global financial markets, as well as appreciate the role of key institutions involved in these markets.
Areas to be covered:
1. Firstly, we analyse the role, structure and economic principles of the key players participating in financial markets.
2. Secondly, we examine the function and characteristics of two key markets: fixed income and foreign exchange.
3. Thirdly, we will analyse the trading mechanics of financial markets, and in doing so, we will examine the development and organisation of major exchanges.
Learning Outcomes
Upon successful completion of this module, students will have an understanding of:-
1. The structure and strategy of key participants in financial markets
2. The trading structures of financial markets
3. Development and organisation of major exchanges
4. How market structure will be reflected in pricing of securities, trading behaviour, trading mechanisms and market design
5. The role of information in financial markets and how it is processed in practice
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Ability to critically read and evaluate the academic microstructure literature
o Appreciation, construction and analysis of trading strategies
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Critical evaluation and interpretation
o Self-assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o The ability to present and communicate complex ideas to a non-specialist audience
o Ability to work in groups
o Organisation and Time Management
(i) provide students with the conceptual and analytical framework required for understanding how international financial conditions influence the investment decision process;
(ii) provide students with the necessary theoretical and analytical tools which explain and forecast the exchange rate dynamics.
Areas to be covered include:
Foreign Exchange Markets
Organization of foreign exchange market; Currency quotes and prices; Bid-ask spread; Forward premium and discount.
Balance of Payment
Capital account; Current account; Official reserve account; Dynamics of balance of payment
Purchasing Power Parity
Price level; Purchasing power of a currency; Absolute PPP; Relative PPP; Empirical evidence of purchasing power parity.
International Equity and Debt Markets
Global sources of funds; World bond markets; International bank loans; World stock markets; International cross-listing and ADR.
International CAPM
International diversification; Risk and return of international investment; World CAPM; International CAPM; Integrated and segmented markets.
Cross-border Valuation
Adjusted net present value; Withholding tax and tax credits; Cross-border choice of cost of capital; Forecasting exchange rate in valuation.
Learning Outcomes
Learning Outcomes
Upon successful completion of this module, students will:
1. analyze and discuss international macroeconomics and institutional environment
2. articulate determinants of foreign exchange rate and interpret the impact of economic events on foreign exchange rate
3. forecast foreign exchange rates with international parity conditions
4. discuss the operation of capital and foreign exchange markets
5. identify risks relating to exchange rate and develop risk management strategies
6. identify and describe methods of international capital raising
7. discuss, identify and evaluate foreign direct investment and its risk management
Skills
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Ability to critically evaluate the exchange rate movement
o Ability to critically read and evaluate finance academic literature
o Appreciation, construction and analysis of international financial models of practical risk situations
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Critical evaluation and interpretation
o Self-assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organization and Time Management
o Use of IT.
This course will introduce the modern practices in finance of using algorithms to extract computer-age statistical
inference. The purpose of this course is not to introduce students to the vast array of machine learning
algorithms. Instead, the goal is to introduce the emerging field of Financial Machine Learning as a complement to
traditional financial research techniques.
This course presents machine learning as a non-linear extension of various topics in quantitative economics,
such as financial econometrics. This course will introduce best practice techniques in financial data science,
which can help illicit economically meaningful signals and answer recent financial research questions.
Learning Outcomes
On successful completion of the course, students will be able to:
1. Evaluate fundamental financial machine learning principles
2. Synthesize theory to build investment strategies
3. Formulate code to solve problems encountered in finance
Skills
This module provides opportunities for the student to acquire or enhance the following skills:
1. Problem solving – innovative ability to design and develop algorithms
2. Logical reasoning – developing code to implement solutions
3. Digital Proficiency – ability to write code
4. Practice Ready – building empirical investment strategies
5. Critical Thinking – understanding how to create robust test plans
The aims of this module are to:
Deepen participants' understanding of financial predictions and decision-making by exploring the revolutionary
impact of combining econometrics and machine learning in financial analytics.
Integrate machine learning and classical financial time series econometrics to tackle complex financial problems
characterised by uncertainty and conflicting objectives.
Explore the role of machine learning in processing large datasets and accurately modelling the complexities of
financial markets.
Advocate for adopting a growth mindset for learning advanced financial data analytics, emphasising embracing
challenges, persisting through setbacks, leveraging criticism, and finding lessons in others' success.
Equip participants with the necessary insights and tools to navigate the sophisticated realm of financial analytics,
encouraging a lifelong commitment to learning and development in the field.
Learning Outcomes
Upon successful completion of this module students will be able to:
1. Extract meaning from noisy financial data
2. Critique stylised facts of financial data for economic inference
3. Evaluate the output of statistical tests
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
1. Problem solving – innovative ability to implement statistical tests
2. Logical reasoning – analysing data
3. Digital Proficiency – ability to write code
4. Abstraction – developing generic re-usable solutions
5. Critical Thinking – applying and interpreting statistics
The aims of this module are to:
(i) provide students with the necessary theoretical and analytical tools which underpin the pricing of assets;
(ii) familiarize students with the environment of a trading room
Areas to be covered include:
Financial markets
Overview of main markets; how firms and governments raise finance; financial instruments; trading securities.
Valuation
Valuing stocks.
Asset returns and portfolio theory
Measuring asset returns; theory of choice under uncertainty; mean-variance portfolio theory.
Asset-pricing models
Assessing the theoretical and empirical validity of various asset pricing models.
Upon successful completion of this module, students will:
1. Be familiar with the various theories on individuals’ investment decision making
2. apply techniques for formally assessing risk.
3. understand the methodologies employed in investigating asset pricing behaviour in the capital market
4. be able to critically evaluate the various asset pricing models in terms of both theory and empirical evidence
5. be able to critically appraise the EMH, anomalies and behavioural finance.
6. be familiar with the trading-room environment and the Bloomberg database.
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Use of computer-based packages to analyse and evaluate relevant data
o Ability to criticially read and evaluate finance and risk-related academic literature
o Appreciation, construction and analysis of financial and economic models of practical risk situations
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Criticial evaluation and interpretation
o Self-assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organisation and Time Management
o Use of IT.
This module considers both risk and regulation in financial services. With regard to risk the module introduces students to the risks that institutions must take if they are to survive and prosper including market risk, credit risk, liquidity risk and operational risk. Emphasis is on the quantification of these risks, decisions about what level of such risks are acceptable and the action required to mitigate unacceptable levels of risk.
MODULE AIMS
(i) to offer a rigorous and intellectually demanding course of study of the techniques, principles and underpinning theories behind effective financial regulation
(ii) to offer a rigorous and intellectually demanding course of study of risk assessment and risk mitigation techniques applicable to financial institutions
(iii) to provide students with an understanding of current thoughts on financial market reform.
With regard to regulation the emphasis is on identifying the objectives of the regulatory system. The course stresses that being clear about the objectives of regulation is essential from the point of view of ensuring that the system is operated efficiently, that priorities are correctly assigned and weighted, and that the spirit as well as the letter of regulatory requirements is observed.
Learning Outcomes
Upon successful completion of this module students will have an understanding of:
1. the economics of information and its importance in financial regulation
2. the calculation of market risk, credit risk, liquidity risk and operational risk for financial institutions
3. the relationship between the capital requirements faced by financial institutions and their levels of credit risk, market risk and operational risk.
4. obstacles to efficient supervision and resolution
5. working in small groups and making tutorial presentations
6. how to use journal articles to build knowledge of the subject material
Skills
This module provides opportunities for the student to acquire or enhance the following skills:-
• Subject-specific skills
o Ability to critically read and evaluate finance and risk-related academic literature;
o Appreciation, construction and analysis of maths/statistical, financial and economic models of practical risk situations;
o Ability to connect business problems with risk management;
o Ability to marry regulatory structure with the principles of risk sharing and risk mitigation
• Cognitive Skills
o Problem solving
o Logical reasoning
o Independent enquiry
o Criticial evaluation and interpretation
o Self assessment and reflection
• Transferable Skills
o The ability to synthesis information/data from a variety of sources
o Preparation and communication of ideas in both written and presentational forms
o Ability to work both independently and in groups
o Organisation and Time Management
o Use of IT.
Course Contents
This course covers individual dissertation supervision for each Masters student. Students are given guidance in regard to all aspects of writing their dissertation, including financial modelling, collecting and compiling data and econometric testing.
Learning Outcomes
Learning Outcomes
Students will learn how to write a dissertation to professional level, including how to formulate a well-defined hypothesis, write a literature review, and how to collect and test data.
Skills
Skills
Writing and data compilation as well as econometric skills.
Normally a strong 2.2 Honours degree or equivalent qualification acceptable to the University in Finance, Mathematics, Economics, or in another relevant quantitative subject. Performance in relevant modules must be of the required standard.
Applicants are advised to apply as early as possible and ideally no later than 14th August 2026 for courses which commence in late September. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal prior to the deadline stated on course finder. Notifications to this effect will appear on the application portal against the programme application page.
Please note: international applicants will be required to pay a deposit to secure a place on this course.
International Students
Our country/region pages include information on entry requirements, tuition fees, scholarships, student profiles, upcoming events and contacts for your country/region. Use the dropdown list below for specific information for your country/region.
English Language Requirements
Evidence of an IELTS* score of 6.5, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required.
*Taken within the last 2 years.
International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.
If you need to improve your English language skills before you enter this degree programme, Queen's University Belfast International Study Centre offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.
Academic English: an intensive English language and study skills course for successful university study at degree level
Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.
Successful students will have the necessary skills to have career opportunities in finance, including investment banking, commercial banking, investment management, or other financial intermediaries.
Graduate prospects from the MSc Finance and Trading degree are excellent; culminating in Queen’s being ranked highly in the UK for Graduate Prospects in Accounting and Finance (Times and Sunday Times Good University Guide).Graduates from this programme have secured roles with employers such as Morgan Stanley, Citi, Bank of China, BDO, Deloitte, PwC, Davy Group, and many others. Typical graduate roles include portfolio analyst, investment analyst, equity research analyst, energy trader, and financial consultant. https://www.qub.ac.uk/directorates/sgc/careers/
Graduate Plus/Future Ready Award for extra-curricular skills
In addition to your degree programme, at Queen's you can have the opportunity to gain wider life, academic and employability skills. For example, placements, voluntary work, clubs, societies, sports and lots more. So not only do you graduate with a degree recognised from a world leading university, you'll have practical national and international experience plus a wider exposure to life overall. We call this Graduate Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.
1EU citizens in the EU Settlement Scheme, with settled status, will be charged the NI or GB tuition fee based on where they are ordinarily resident. Students who are ROI nationals resident in GB will be charged the GB fee.
2 EU students who are ROI nationals resident in ROI are eligible for NI tuition fees.
3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.
All tuition fees quoted relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.
Terms and Conditions for Postgraduate applications:
1.1 Due to high demand, there is a deadline for applications.
1.2 International applicants will be required to pay a deposit to secure their place on the course. The current mandatory tuition fee deposit payment is £1000 International (Non- EU & EU except ROI).
1.3 This condition of offer is in addition to any academic or English language requirements.
Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.
Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £75 per year for photocopying, memory sticks and printing charges.
Students undertaking a period of work placement or study abroad, as either a compulsory or optional part of their programme, should be aware that they will have to fund additional travel and living costs.
If a programme includes a major project or dissertation, there may be costs associated with transport, accommodation and/or materials. The amount will depend on the project chosen. There may also be additional costs for printing and binding.
Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen.
There are also additional charges for graduation ceremonies, examination resits and library fines.
How do I fund my study?
The Department for the Economy will provide a tuition fee loan of up to £6,500 per NI / EU student for postgraduate study. Tuition fee loan information.
A postgraduate loans system in the UK offers government-backed student loans of up to £11,836 for taught and research Masters courses in all subject areas (excluding Initial Teacher Education/PGCE, where undergraduate student finance is available). Criteria, eligibility, repayment and application information are available on the UK government website.
