What is the MSc Finance and Data Analytics degree?
The MSc Finance and Data Analytics is a one-year full-time degree that combines financial knowledge with data analysis, preparing you to work with the large and complex datasets increasingly used across the financial sector.
Finance and data analytics bring together an understanding of financial markets with the quantitative and statistical techniques used to interpret data. You'll explore how data can be used to understand markets, assess investments and support financial decision-making.
The course develops the quantitative, statistical and technical skills needed for specialist roles across finance, investment and business analytics.
Why this course
Develop an understanding of financial markets alongside the analytical skills needed to work with increasingly large and complex sources of data.
You'll explore how financial and statistical modelling can be used to analyse data and support investment and business decisions.
You'll also consider how different sources of data, including social networks and search engine analytics, can provide insight into financial markets and investments.
Who should apply
Those interested in finance, big data and data analysis
Those looking to develop quantitative, statistical and technical skills
Those interested in how data can inform financial and investment decisions
Those looking to pursue specialist roles within finance, investment or business analytics
What you'll learn
Big data: Explore how large and complex datasets can be used to understand financial markets and support decision-making
Portfolio analysis: Develop your understanding of how investment portfolios can be analysed and managed
Financial modelling: Use quantitative techniques to examine financial information and market behaviour
Data analytics: Develop techniques for analysing and interpreting financial and business data
Global markets: Explore financial markets and how data can inform trading and investment decisions
Your learning experience
Quantitative analysis: Develop the statistical and analytical skills needed to work with financial data
Financial decision-making: Explore how data and financial analysis can support informed decisions
Data interpretation: Build your ability to analyse complex datasets and identify useful insights
Financial modelling: Apply quantitative techniques to financial problems and market data
Practical application: Develop skills that can be applied to challenges across finance and business analytics
Careers and outcomes
The MSc Finance and Data Analytics develops financial, quantitative and analytical skills that can support careers across finance and business analytics.
Career opportunities can include areas such as:
Financial analysis
Data and business analytics
Investment analysis
Management
Public administration
Accountancy
Where Essex Business School graduates work
Graduates from Essex Business School have progressed to organisations including:
They can help you find work experience, internships, placements and voluntary opportunities, as well as providing access to employer talks on campus.
We also work closely with the Essex Startups team to support students looking to develop their own business ideas.
Why we're great.
Our Financial Market Labs give you access to market-leading Bloomberg business data so you can test your financial models.
The perfect course if you have an interest in big data and data analysis and want to work in specialist roles within the finance and investment sector.
Hear from guest speakers from industry to advance your professional knowledge.
“I decided to study at Essex Business School because of the data analytics part of the course. I wanted to learn how to invest and the best way to price assets, but I also wanted to learn ways of harnessing modern big data in finance and using it to make it work for me. Big data is the new kid on the block and MSc Finance and Data Analytics taught me ways of befriending and handling this kid. Not only did we learn theory, but we also got the chance to get into a lab and learn everything first-hand. The Bloomberg suite located in the business school gave me first-hand experience of how trading in the real world looks and we also learnt different programming languages that taught us how to handle finance data and get information out of it. I still make use of everything I learnt whilst at Essex even today.”
Laone Maphane, MSc Finance and Data Analytics
Course content
Course structure
We offer a flexible course structure with a mixture of core/compulsory modules, and optional modules chosen from lists. Please be aware that we are planning changes to our first year to make it more relevant to your chosen course.
Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The following modules are based on the current course structure and may change in response to new curriculum developments and innovation.
We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.
Components and modules explained
Components
Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.
Each component has a status and carries a certain number of credits towards your qualification.
Status
What this means
Core
You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options
You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory
You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options
You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional
You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.
Modules
Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.
In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.
Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:
HR
100
4
FY
The department or school the module will be taught by.
In this example, the module would be taught by the Department of History.
Your dissertation is the culmination of your Masters programme, where you apply the knowledge gained on your course to produce a 10,000 word independent piece of work. You generate an original idea, analyse literature and current knowledge and produce a coherent argument that shows your ability to relate theory to practice. Your dissertation will help you develop vital skills for the workplace, as well as the ability to analyse real problems through an academic lens. You're assigned a supervisor for the duration of your project.
This module equips you with the econometric tools and necessary experience to conduct empirical research in finance. You review statistical and basic econometric models and learn to apply econometric techniques in finance by considering topics such as (G)ARCH models, unit roots and cointegration.
Big data - where datasets are so large they cannot be processed using traditional techniques – is useful to financial organisations. This module explores how to analyse big data and covers areas such as predictive analytics, risk modelling and corporate finance. You also learn about the application of data analytics in high frequency finance, fraud and personal finance.
Understand the process of portfolio management. You cover the main concepts such as efficient diversification, managing risk exposures, and the valuation of financial assets that are at the core of managing investment portfolios, and pay special attention to the practicalities of the implementation of these concepts.
This course will provide you with a thorough grounding in both the theory and practice of time series econometrics with applications to topics relevant to finance. This knowledge, along with training in industry standard computing software, will be highly beneficial to students undertaking further study or wishing to work in the financial sector.
Data Analysis: Cross Sectional, Panel and Qualitative Data Methods
(20 CREDITS)
This module provides you with an understanding of non-time-series data analytic approaches in finance. It covers methods for cross-sectional, panel and qualitative analysis and their applications whereby all topics are illustrated with relevant examples.
Cross-sectional data are organised over individual groups (eg households, firms or countries) and have no time dimension. They may include discontinuous data (eg binary), qualitative or categorical data and are essentially non-numerical. Examples include: survey responses, textual analysis of social media or interviews. Panel data or longitudinal data are multi-dimensional data streams involving measurements over time. As such, panel data consists of researcher's observations of numerous phenomena that were collected over several time periods for the same group of units or entities. For example, a panel data set may be one that follows a given sample of individuals over time and records observations or information on each individual in the sample. The nature and advantages of panel data has led to numerous applications in finance and economics research.
This module covers topics in mathematics that are required in Masters-level finance courses at the University of Essex. You focus on the basics of linear algebra, differential calculus including optimisation and dynamics.
Build the academic, research and professional skills needed to succeed at postgraduate level and beyond. This module supports your transition to master’s study by developing independent learning, research and critical thinking skills, alongside ethical and effective use of AI as a learning tool. You’ll also enhance your employability and professional practice, gaining the confidence and capabilities required for graduate-level roles and advanced academic work.
Quantitative methods (e.g. Data Analytics, Econometrics, Financial Modelling, Statistics)
We will also consider applicants who hold a CFA Institute Programme Level One, Two or Three (pass or above).
Applicants from any other background will be considered on a case by case basis, dependent on the content of their undergraduate degree and at least one year of relevant work experience in the field of economics, finance, banking, investment, financial engineering, risk management entrepreneurship, accounting or quantitative analysis (please include your CV with your application).
International & EU entry requirements
We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.
Sorry, the entry requirements for the country that you have selected are not available here. Please contact our Graduate Admissions team at pgquery@essex.ac.uk to request the entry requirements for this country.
English language requirements
If English is not your first language, we require IELTS 6.5 overall with a minimum component score of 5.5.
If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.
Additional Notes
The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.
We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:
tour our campus and accommodation
find out answers to your questions about our courses, student finance, graduate employability, student support and more
meet our students and staff
If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing tours@essex.ac.uk and we’ll arrange an individual campus tour for you.
We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.
For information on our deadline to apply for this course, please see our ‘how to apply' information.
Visit Colchester Campus
Set within 200 acres of award-winning parkland - Wivenhoe Park and located two miles from the historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.
If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360-degree virtual tour allows you to explore our University from the comfort of your home. Check out our Colchester virtual tour to see accommodation options, facilities and social spaces.
At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.
The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and
Ordinances and in the University Regulations, Policy and Procedures.
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