Scale-Free Network Emerged in the Markets: Human Traders versus Zero-Intelligence Traders

Abstract

We design a Web-based prediction market platform to monitor the trading behavior among the human traders in real-time. Two experiments tied to the outcomes of mayoral election in Taiwan are performed in parallel for 30 days. From the accumulated transaction data, we reconstruct the so-called cash-flow networks. We observe that the network structure is hierarchical and scale-free with a power-law exponent of 1.15±0.07. Through carrying out a post-simulation, we also demonstrate that a simple double auction market with “zero intelligence” traders is capable of generating hierarchical and scale-free networks.