An Artificial Market Model of a Foreign Exchange Market

In this study, we proposed a new approach to foreign exchange market studies, an artificial market approach. The artificial market approach integrated fieldwork studies and multiagent models in order to explain the micro and macro relation in markets. The artificial market approach has the three steps: First, in order to investigate the learning patterns of actual dealers, we carried out both interviews and questionnaires. These field data made it clear that each dealer improved his or her prediction method by replacing (a part of) his or her opinions about factors with other dealers’ opinion which can forecast more accurately. Second, we constructed a multiagent model of a foreign exchange market. Considering the result of the analysis of the field data, the interaction of agents’ learning is described with genetic algorithms in our model. Finally, the emergent phenomena at the market level were analyzed on the basis of the simulation results of the model. The results showed that rate bubbles were caused by the interaction between the agents’ forecasts and the relationship of demand and supply. The other emergent phenomena were explained by the concept of the phase transition of forecast variety. The filed data also supported this simulation results. This approach therefore integrates the fieldwork and the multiagent model, and provides quantitative explanation of the micro-macro relation in markets.