The role of information in a continuous double auction: An experiment and learning model

Abstract

We analyze trading in a modified continuous double auction market. We study how more or less information about trading in a prior round affects allocative and informational efficiency. We find that more information reduces allocative efficiency in early rounds relative to less information but that the difference disappears in later rounds. Informational efficiency is not affected by the information differences. We complement the experiment with simulations of the Individual Evolutionary Learning model which, after modifications to account for the CDA, seems to fit the data reasonably well.