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For many of the world's major financial markets, the proportion of market activity that is due to the actions of “automated trading” software agents is rising: in Europe and the USA, major exchanges are reporting that 30%—75% of all transactions currently involve automated traders. This is a major application area for artificial intelligence and autonomous agents, yet there have been very few controlled laboratory experiments studying the interactions between human and software-agent traders. In this paper we report on results from new human-agent experiments using the OpEx experimental economics system first introduced at ICAART-2011. Experiments explore the extent to which the performance of the traders, and of the market overall, is dependent on the speed at which the agents operate. Surprisingly, we found that slowing down the agents increased the market's overall ability to settle to a competitive equilibrium, and that slow-agent markets were more efficient.
Cartlidge et al. (Sun,) studied this question.