The Predictive Power of Zero Intelligence in Financial Markets

Standard models in economics are based on intelligent agents that maximize utility. However, there may be situations where constraints imposed by market institutions are more important than intelligent agent behavior. We use data from the London Stock Exchange to test a simple model in which zero intelligence agents place orders to trade at random. The model treats the statistical mechanics of the interaction of order placement, price formation, and the accumulation of stored supply and demand, and makes predictions that can be stated as simple expressions in terms of measurable quantities such as order arrival rates. The agreement between model and theory is excellent, explaining 96% of the variance of the bid-ask spread across stocks and 76% of the price diffusion rate. We also study the market impact function, describing the response of prices to orders. The nondimensional coordinates dictated by the model collapse data from different stocks onto a single curve, suggesting a corresponding understanding of supply and demand. Thus, it appears that the price formation mechanism strongly constrains the statistical properties of the market, playing a more important role than the strategic behavior of agents.