Competition in Intermediated Markets: Statistical Signatures and Critical Densities

Abstract

In conventional economic theory, competition is an unmodelled process that is claimed to drive all economic actors to behave as if they were constrained optimisers. What is actually modelled in conventional economic theory is either a competitive equilibrium that is said to capture the result of the unmodelled competitive process or a game between two or, occasionally, among three agents. The common element in these approaches is the absence of any consideration of the effect of interaction among more than three economic actors at any one time. This is despite the natural presumption that such interaction is essential to any process of competition. The purpose of this paper is to demonstrate that the interaction excluded from conventional economic theory gives rise to the distributions of data observed in real markets. The well known fat-tailed (leptokurtic) distributions found in high frequency time series data for financial markets is shown to characterise high frequency retail market data as well. This and other statistical signatures of real markets are replicated in an abstract simulation model of markets in which intermediaries (brokers or jobbers) can function. It is shown that a high density of agents in the social network is necessary for intermediation to be viable and for the preponderance of demands to be satisfied. Moreover, the leptokurtic statistical signature characterises only markets satisfying that density condition.