This paper presents results from an experiemtal computer simulated stock market. In this market artificial intelligence algorithms take on the role of traders. They make predictions about the future, and buy and sell stock an indicated by their expectations of future risk and return.

There is reliable evidence that simple rules used by traders have some predictive value over the future momoment of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictabiliy.

We propose a theory of asset pricing based on heterogeneous agents who continually adapt their expectations to the market that these expectations aggregatively create. And we explore the implications of this theory computationally using our Santa Fe artificial stock market.