Artificial software agents on thin double auction markets: a human trader experiment

This paper studies how software agents influence the market behavior of human traders. Software agents with a passive arbitrage seeking strategy are introduced in a double auction market experiment with human subjects in the laboratory. As a treatment variable, the influence of information on the existence of software agents is investigated. We found that common knowledge about the presence of software agents triggers more efficient market prices in the presence of the programmed strategy whereas an effect of the information condition on behavioral variables could not be observed. Surprisingly, the introduction of software agents results in lower market efficiency in the no information treatment when compared to the baseline treatment without software agents.