Network Topology of an Experimental Futures Exchange

TL;DR

This study analyzes the network topology of an experimental futures exchange, revealing scale-free, hierarchical, and small-world properties, with power-law distributions in incomes, transaction intervals, and community sizes, providing insights into market participant interactions.

Contribution

It provides the first empirical analysis of a futures exchange network, uncovering its hierarchical, scale-free, and community structures, and linking network features to trading outcomes.

Findings

Network is hierarchical, disassortative, and scale-free with a power law exponent of ~1.02.

Small-world properties emerge early in the trading process.

Power law distributions observed in net incomes, transaction intervals, and community sizes.

Abstract

Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth is one of the examples. To better understand the working behind the complexity, we undertook an empirical study measuring the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled to event outcomes. After free registration, participants started trading to compete for the money prizes upon maturity of the futures contracts at the end of the experiment. The evolving `cash' flow network was reconstructed from the transactions between players. We show that the network topology is hierarchical, disassortative and scale-free with a power law exponent of 1.02+-0.09 in the degree distribution. The small-world property emerged early in the experiment while the number of participants was still small. We also show power law distributions of the net incomes and inter-transaction time intervals. Big winners and losers are associated with high degree, high betweenness centrality, low clustering coefficient and low degree-correlation. We identify communities in the network as groups of the like-minded. The distribution of the community sizes is shown to be power-law distributed with an exponent of 1.19+-0.16.