Module Details

EC911-7-SP-CO: Computational Market Micro-Structure And Complexity Economics

Year: 2016/17
Department: Economics
Essex credit: 20
ECTS credit: 10
Available to Study Abroad / Exchange Students: No
Full Year Module Available to Study Abroad / Exchange Students for a Single Term: No
Outside Option: No
Pre-requisites: EC910

Supervisor: Professor Sheri Markose
Teaching Staff: Professor Sheri Markose and Visiting Lecturer
Contact details: For further information, send a message to

Module is taught during the following terms
Autumn Spring Summer

Module Description

The objective of this module is to equip the student with principles of market microstructure, especially in terms of electronic stock market environments and to comprehend the challenges posed by complexity in socio-economic systems. The module is made up of 4 parts.

Part 1 starts with an introduction to the key concepts of market microstructure and to the use of agent based artificial stock market models. Here the focus is on the canonical Santa Fe Institute stock market model which identifies endogenous heterogeneity in trading strategies and boom bust dynamics with contrarian payoff structures.

Part II will cover high frequency financial market modelling that includes algorithmic trading and the full rebuild of the London Stock Exchange electronic limit order book (aka London Stock Exchange Electronic Trading System, SETS).

In Part III, a second application of the computational approach to market micro-structure is covered in the design of centralized clearing platforms (CCPs) to reduce systemic risk in over-the-counter (OTC) derivatives markets.

In Part IV, an introduction is made to complexity economics which involves self-organization, reflexivity, incompleteness and strategic proteanism which is accompanied by Red Queen arms races in novelty and surprises. The latter characterize the Schumpeterian technology arms races and structure changing dynamics of creative destruction in capitalism. The student is introduced to new thinking arising from the neuro-physiology of mirror neurons as the basis of memetic coordination (herding) and anti-coordination behaviours which are germane to complex socio-economic interactions.

Feedback for this module will occur through class meetings where we will go over the answers to problem sets and where you will be able to ask questions about your own method of solution; answers that will be posted on the website for the module that will give you written guidance on the appropriate method to approach the problems, assignments, and tests; and office hours where any additional questions can be addressed. You should be sure that you use these methods to understand how to improve your own performance.

Learning and Teaching Methods

Ten 2 hour lectures and lab sessions


Whichever is the Greater: EITHER 50 per cent Coursework Mark, 50 per cent Exam Mark OR 100 per cent Exam Mark


Term Paper

Exam Duration and Period

2:00 during Summer Examination period.

Other information

Compulsory for MSc Computational Economics, Financial Markets and Policy.


  • Joel Hasbrouck , 2007, Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading, Oxford University Press (Selected Chapters)
  • D. Easley, M. Lopez de Prado, & M. O'Hara (2011). The Microstructure of the Flash Crash: Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading. The Journal of Portfolio Management, 37(2):118-128.
  • Cliff, D., Brown, D., Treleavan, P. (2011) "Technology Trends in the financial markets: A 2020 vision"
  • Markose, S., Computability and Evolutionary Complexity: Markets as Complex Adaptive Systems, Economic Journal June 2005, Vol. 115 , F159-F192.

Further information