Evolving market design in zero-intelligence trader markets

Abstract

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.