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Modelling Complex Financial Markets Using Real-Time Human–Agent Trading Experiments

  • John Cartlidge
  • Dave Cliff
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

To understand the impact of high-frequency trading (HFT) systems on financial-market dynamics, a series of controlled real-time experiments involving humans and automated trading agents were performed. These experiments fall at the interdisciplinary boundary between the more traditional fields of behavioural economics (human-only experiments) and agent-based computational economics (agent-only simulations). Experimental results demonstrate that: (a) faster financial trading agents can reduce market efficiency—a worrying result given the race towards zero-latency (ever faster trading) observed in real markets; and (b) faster agents can lead to market fragmentation, such that markets transition from a regime where humans and agents freely interact to a regime where agents are more likely to trade between themselves—a result that has also been observed in real financial markets. It is also shown that (c) realism in experimental design can significantly alter market dynamics—suggesting that, if we want to understand complexity in real financial markets, it is finally time to move away from the simple experimental economics models first introduced in the 1960s.

Keywords

Agent-based computational economics Automated trading Continuous double auction Experimental economics High-frequency trading Human–agent experiments Robot phase transition Trading agents 

Notes

Acknowledgements

The experimental research presented in this chapter was conducted in 2011–2012 at the University of Bristol, UK, in collaboration with colleagues Marco De Luca (the developer of OpEx) and Charlotte Szostek. They both deserve a special thanks. Thanks also to all the undergraduate students and summer interns (now graduated) that helped support related work, in particular Steve Stotter and Tomas Gražys for work on the original ExPo platform. Finally, thanks to Paul Dempster and the summer interns at UNNC for work on developing the ExPo2 platform, and the pilot studies run during July 2016. Financial support for the studies at Bristol was provided by EPSRC grants EP/H042644/1 and EP/F001096/1, and funding from the UK Government Office for Science (Go-Science) Foresight Project on The Future of Computer Trading in Financial Markets. Financial support for ExPo2 development at UNNC was provided by FoSE summer internship funding.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of BristolBristolUK

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