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Publication - Professor Dave Cliff

    Modelling complex financial markets using real-time human-agent trading experiments

    Citation

    Cartlidge, J & Cliff, D, 2018, ‘Modelling complex financial markets using real-time human-agent trading experiments’. in: Shu-Heng Chen, Ying-Fang Kao, Ragupathy Venkatachalam, Ye-Rong Du (eds) Complex Systems Modeling and Simulation in Economics and Finance. Springer International Publishing AG, pp. 35-69

    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.

    Full details in the University publications repository