Evolving Market Design in Zero-Intelligence Trader Markets

The Continuous Double Auction (CDA) is one of the most popular of all auction market-mechanisms in the world. Some of the biggest trade markets in the world including the New York Stock Exchange (NYSE) and the Chicago Mercantile Exchange are organised as CDAs. Previous work using Genetic Algorithms (GAs) for automated mechanism design by Cliff has shown that previously unknown ‘hybrid’ variants of the traditional CDA can lead to the most desirable 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 as well as the ZIP agent parameters. The exclusive use of the ZIP trading algorithm in all his work raises questions about the robustness of his results to any change in the trading algorithm used. In this paper 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 hybrid CDAs are still preferred over traditional variants and our results provide the first demonstration that hybrid variants of the CDA can provide favourable dynamics for trading strategies other than ZIP.