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On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling.
We enable you to attain an understanding of financial markets at the level of individual trades occurring over sub-millisecond timescales, and apply this to the development of real-time approaches to trading and risk-management.
The course includes hands-on projects on topics such as order book analysis, VWAP & TWAP, pairs trading, statistical arbitrage, and market impact functions. You have the opportunity to study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms.
In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas:
Statistical and computational methods
Modelling trading strategies and predictive services that are deployed by hedge funds
Algorithmic trading groups
Derivatives desks
Risk management departments
Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation. We are supported by Essex’s highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School. That's why we are ranked 6th in the UK for research power in computer science (Times Higher Education research power measure, Research Excellence Framework 2021).
This course is available to study part-time.
Why we're great.
Develop the essential operational skills needed for state-of-the-art computational methods for financial modelling
Study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms
Our Employability and Careers Centre is on hand to help with careers advice and planning. You will also have opportunities to present your research and travel to international conferences
Our expert staff
This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.
Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.
More broadly, our research covers a range of topics, from materials science and semiconductor device physics, to the theory of computation and the philosophy of computer science, with most of our research groups based around laboratories offering world-class facilities.
Specialist facilities
We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
All computers run either Windows 10 or are dual boot with Linux
Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
Use Matlab to implement quantitative methods in finance and economics, and their application to investment, risk management and trading, as well as Python to model and develop machine learning algorithms with emphasis on the financial industry
Your future
We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.
Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
HSBC
Mitsubishi UFJ Securities
Old Mutual
Bank of England
We also work with the University’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.
Entry requirements
UK entry requirements
Applicants with a 2:2 degree in one of the following subjects (with no module requirements):
Computer Science
Computer Engineering
Computer Networks
Computer Games
Computing
Software Engineering
Finance
Economics
Physics
Mathematics
We will consider applicants with any other 2:2 degree or above which include one or more modules from this list:
At least one Maths modules such as:
Mathematics
Calculus
Statistics
Differential Equations
Probability
Stochastic Processes
AND at least one Programme module, such as:
C
C#
C++
Java
Python
MATLAB
Object Oriented Programming aka "OOP"
Introduction to Programming
Programming Languages
Advanced Programming
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 select
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where you'll find this information.
English language requirements
IELTS 6.0 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.
Structure
Course structure
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. However, if we need to make material changes, for example due to significant disruption, or in response to COVID-19, 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.
This module is a mix of theory and practice with big data cases in finance. Algorithmic and data science theories will be introduced and followed by a thorough introduction of data-driven algorithms for structures and unstructured data. Modern machine learning and data mining algorithms will be introduced with particular case studies on financial industry.
The module introduces students to financial markets as well as providing a detailed introduction to the quantitative methods that are a pre-requisite to other CCFEA modules. Students will be introduced to financial markets such as equities, bonds, interest rates, forwards, futures and foreign exchange. Applications of calculus and statistical methods to finance are also presented.
This module focuses on quantitative methods in finance and economics and their application to investment, risk management and trading. The module will introduce students to state-of-the-art statistical modelling of financial markets and will give an overview of the quantitative framework that is necessary to advance to other CCFEA modules.
The modules introduces students to computational thinking in economics and finance by looking at different relevant models and theories, such as agent-based modelling and game theory. Students will also be introduced to various applications, such as financial forecasting, automated bargaining and mechanism design.
Computational Market Microstructure for FinTech and the Digital Economy
(20 CREDITS)
Equip yourself with principles of allocation and mechanism design from an operational perspective. Auction design and market microstructure of the stock market, liquidity provision in electronic financial markets such as dark pools, and capital adequacy of centralized clearing platforms are some of the specific applications that will be studied in the first part of this module. During the second part, you will be introduced to complexity economics of self-organisation, network modules, and strategic proteanism. Finally, you'll use network models to study economic interactions.
This module aims to prepare students for conducting an independent research project leading to a dissertation and to provide them with an appreciation of research and business skills related to their professional career. As a precursor to their project students, individually select an area of Computer Science, or Electronic Engineering, or Computational Finance and perform the necessary background research to define a topic and prepare a project proposal under the guidance of a supervisor. The module guides them by a) introducing common research methods b) creating an understanding of basic statistics for describing and making conclusions from data c) helping to write a strong proposal including learning how to perform literature search and evaluation and d) giving an in-depth view into the business enterprise, financial and management accounting and investment appraisal.
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
Home to 15,000 students from more than 130 countries, our Colchester Campus is the largest of our three sites, making us one of the most internationally diverse campuses on the planet - we like to think of ourselves as the world in one place.
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 the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.
Exhibitions
Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.
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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