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Computational Economics, Financial Markets and Policy

Course overview

(MSc) Master of Science
Computational Economics, Financial Markets and Policy
Current
University of Essex
University of Essex
Economics
Colchester Campus
Masters
Full-time
Economics
MSC N30612
http://www.essex.ac.uk/students/exams-and-coursework/ppg/pgt/assess-rules.aspx
25/07/2017

A degree with an overall 2.2 in a discipline related to economics such as: Economics, Maths, Engineering, Finance, Physics or any other degree with a strong maths component.

The Degree should contain some economics components including Macroeconomics; Microeconomics or Econometrics.

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.

External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment. External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course. They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards. External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.

eNROL, the module enrolment system, is now open until Monday 21 October 2019 8:59AM, for students wishing to make changes to their module options.

Key

Core You must take this module You must pass this module. No failure can be permitted.
Core with Options You can choose which module to study
Compulsory You must take this module There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Compulsory with Options You can choose which module to study
Optional You can choose which module to study

Exit awards

A module is given one of the following statuses: 'core' – meaning it must be taken and passed; 'compulsory' – meaning it must be taken; or 'optional' – meaning that students can choose the module from a designated list. The rules of assessment may allow for limited condonement of fails in 'compulsory' or 'optional' modules, but 'core' modules cannot be failed. The status of the module may be different in any exit awards which are available for the course. Exam Boards will consider students' eligibility for an exit award if they fail the main award or do not complete their studies.

Programme aims

The aim of this course is to give highly motivated and talented students a rigorous training in Economics and Finance, using primarily a multi-agent computational and simulation modelling approach to complement statistics and econometrics to investigate a wide array of economic phenomena and also aid in policy design.

The agent based computational economics (ACE) method is combined with a perspective that markets are complex adaptive systems in which macro-scopic outcomes are prone to problems of negative externalities, technology and regulatory arms races, fallacies of composition and economic disequilibria with boom and bust type extreme events.

There is a strong policy orientation and operational content to the MSc. It will focus on post 2007 crisis monetary and macro-economic policy issues to do with highly interconnected globalized markets, systemic risk, financial contagion and the design of micro and macro prudential policy.

This course will equip with analytical and operation skills to pursue careers in regulatory and policy related institutions, financial modelling, civil service and real world problem solving.

The Masters will also be an excellent stepping stone for those wishing to progress to further research.

Learning outcomes and learning, teaching and assessment methods

On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:

A: Knowledge and understanding

A1 Knowledge of the challenges faced by macro-economics, financial and monetary policy makers and regulators in a Post 2007 environment.
A2 Knowledge of the financial/banking institutions and macroeconomic inbalances.
A3 Training in new data based driven perspectives on macro-monetary transmission mechanisms
A4 Theoretical and empirical training in real time, electronic market microstructure
A5 Training in advanced economic principles to do with excessive leverage and negative externalities from poorly designed incentives, stability and transmission of financial shocks
A6 Training in complexity economics and challenges thereoff such as regulatory arbitrage and extreme events
A7 Training in cutting edge large scale multi-agent network models for macro-models and simulation platforms for stress testing
A8 Awareness of the significance of alternative theoretical and methodological approaches to macroeconomic and financial analysis
A9 Unique to this course is exposure to practitioner lectures and a real world project set by them
Learning Methods: Outcomes A1-A6 are acquired through lectures, hands on lab sessions classes, and related coursework.

Lectures are used to instigate investigations into new approaches, A1- A5, in macro and micro economics so that institutional details and operational tools can be explored.

A3- A5, A7 are achieved by the lab intensive features of the core compulsory modules which will enable students to implement and test theoretical perspectives.

Group projects in labs will help in team work and also enable model building to tackle real world problems rather than toy models.

This is enhanced by visiting practitioner lectures and the project guided by a visiting practitioner in the area of policy design, regulation and governance which is unique to this course, A9.

Classes and preparation for lectures, provide an opportunity for students to develop their knowledge and understanding of the content of the courses.

The development of the dissertation in consultation with a supervisor provides an additional opportunity for the acquisition of outcomes A1-A6.

Preparation for optional term papers and for examinations aids students in developing this knowledge and understanding.

The dissertation provides an opportunity for students to develop their knowledge and understanding further through undertaking a piece of independent, though supervised, advanced research.
Assessment Methods: Outcomes A1-A6 are assessed throughout the modules comprising the degree by means of written examinations with optional term papers and compulsory group projects for the core modules.

The MSc dissertation provides a further opportunity to assess outcomes A1-A6.

B: Intellectual and cognitive skills

B1 Logically analyse specified problems of macroeconomics, mechanism design, market microstructure and choose the most appropriate methods for their solution.
B2 Exercise critical judgement in assessing the weights of competing theories and methods and appraising their merits
B3 Formulate a coherent economic/financial argument and to model excessive financial leverage as a negative externality
B4 Construct reasoned, informed and concise descriptions and assessment of ideas at the forefront of macro and micro economics and financial policy
B5 Learn the art of operationalizing abstract models and testing hypothesis using virtual agent based models and simulations
B6 Training in accessing and modelling with large scale data bases such as the FDIC and the London real time electronic order book
B7 Critically evaluate and interpret empirical evidence
Learning Methods: Skills B1-B5 are acquired and enhanced primarily through the work that students do for their modules, although lectures provide a means for teachers to demonstrate these skills through example.

Demonstrations through lab exercises with virtual computational models are a key way in which students learn to operationalize abstract models, B5.

Automated access to large data bases such as the FDIC for US banking system and real time real build of the London Electronic SETS market will give students deep empirical understanding, B5, B6.

Student preparation involves the reading, interpretation and evaluation of the economics literature, including texts and research papers, and the analysis of empirical evidence.

Teachers provide feedback on student work through comment and discussion.

In addition, teachers engage students outside the classroom through office hours, appointments, and email.

The dissertation is additionally used to develop a student's mastery of the combined application of economic principles and empirical methods, as well as their analytical ability and understanding of the complete research process.
Assessment Methods: Skills B1-B5 are assessed throughout the modules comprising the degree by means of written examinations with optional term papers.

Lab based group projects based on large scale data bases will be used to enhance B5 and B6.

The MSc dissertation provides a further opportunity to assess skills B1-B5.

C: Practical skills

C1 Identify, select and gather information using relevant sources, including the library and online searches
C2 Operationalizing models using agent based and computer simulation methods
C3 Organise ideas in a systematic and critical fashion
C4 Present and critically assess advanced ideas and arguments using computational and simulation methods for macro and micro economics and financial modelling. Use and apply advanced terminology and concepts in these areas and also provide stress testing platforms in the design of robust policy
C5 Handling large scale macro economic and financial data sets
Learning Methods: Skills C1-C5 are acquired and enhanced primarily through the lab oriented work that students do for their courses.

Lectures also provide a means of teachers demonstrating these skills through example.

Skill C5 is acquired to a greater degree in courses that focus on econometrics.

This skill is reinforced or supplemented depending on the optional courses taken.

The dissertation is additionally used to provide an opportunity for students to acquire practical skills.
Assessment Methods: Skills C1-C5 are assessed throughout the modules, comprising the degree by means of lab sessions, group projects, written examinations with optional term papers.

Skills C1 and C2 are also informally assessed by student's preparation for each course.

The MSc dissertation provides a further opportunity to assess skills C1-C5.

D: Key skills

D1 Communication in writing, using appropriate terminology and technical language
D2 Programming using JAVA based JAS for agent based models and also Matlab
D3 Production of a word-processed research dissertation. Development of web-skills.
D4 Use of computational modelling and mathematical techniques to construct economic models for testing hypothesis or robustness of policy and the use of agent based and statistical/econometric methods to analyse economic data
D5 Group projects in core modules and application of economic/financial reasoning to address complex issues involving macro economic and financial phenomena
D6 Capacity to: (a) organise and implement a plan of independent study; (b) reflect on his or her own learning experience and adapt in response to feedback; and (c) recognise when he or she needs to learn more and appreciate the role of additional research
Learning Methods: Students are guided in acquiring skills D1-D5 through lectures, classes and individual advice from teachers.

The lab intensive sessions for the core models will equip students with D2-D4.

The Group project and the project for guided by visiting practitioner will help in D4-5.

These skills are further developed as students pursue the learning activities associated with their courses.

The dissertation enables students to acquire skill D2 and also assists them in acquiring skills D1, D4 and D5.

Students also have the opportunity to develop skills in working in groups through their participation in classes for courses, especially the applied ones.
Assessment Methods: Skills D1-D5 are assessed throughout the courses comprising the degree by means of examinations with optional term papers.

The dissertation also provides a particular further means for an overall assessment of communication D1, using IT D2, problem-solving skills D4, and self-learning D5.


Note

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 a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or 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 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.

Should you have any questions about programme specifications, please contact Course Records, Quality and Academic Development; email: crt@essex.ac.uk.