Evolving market design in zero-intelligence trader markets

The Continuous Double Auction (CDA) is one of the most popular of market-mechanisms. Previous work using genetic algorithms (GAs) for automated mechanism design by Cliff has shown that previously unexplored ´hybrid´ variants of the traditional CDA can lead to preferable market dynamics. Cliff ´s results were based on experiments conducted using a computational simulation of the CDA populated by electronic Zero Intelligence Plus (ZIP) traders and his work uses a GA to co-evolve the market mechanism with the ZIP agent parameters. We use a self-adaptive evolutionary strategy (ES) to explore the space of possible auction types in a CDA populated by Gode and Sunder´s cognitively simple Zero Intelligence Constrained (ZI-C) traders. We show that non-standard CDAs are still preferred over traditional variants and our results provide the first demonstration that non-standard variants of the CDA can provide favorable dynamics for trading strategies other than ZIP.