Agent-Human Interactions in the Continuous Double Auction

Abstract

The Continuous Double Auction (CDA) is the dominant market institution for real-world trading of equities, commodities, derivatives, etc. We describe a series of laboratory experiments that, for the first time, allow human subjects to interact with software bidding agents in a CDA. Our bidding agents use strategies based on extensions of the Gjerstad-Dickhaut and Zero-Intelligence-Plus algorithms. We find that agents consistently obtain significantly larger gains from trade than their human counterparts. This was unexpected because both humans and agents have approached theoretically perfect efficiency in prior all-human or allagent CDA experiments. Another unexpected finding is persistent far-from-equilibrium trading, in sharp contrast to the robust convergence observed in previous all-human or all-agent experiments. We consider possible explanations for our empirical findings, and speculate on the implications for future agent-human interactions in electronic markets.