In this study, the author proposes a new approach to foreign exchange (forex) market studies: the artificial market approach - by integrating fieldwork studies and multiagent computer models in order to explain the micro and macro relation in markets, as another downloadable model does by considering final consumers.

The proposed artificial market approach is constituted by three steps:

First, in order to investigate the learning patterns of actual dealers, the author 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 facts with other dealers’ opinion.

Second, the author constructed a multiagent model of a foreign exchange market. Considering the result of the analysis of the field data, the interaction of agents’ learning were described with genetic algorithms.

Finally, emergent phenomena at the market level were analyzed onthe basis of the simulation results of the model. The results showed that bubbles in exchange rates were caused by the interaction between the agents’ forecasts and the relationship of demand and supply. Other emergent phenomena were explained by the concept of the phase transition of forecast variety.

The simulation results were supported by further empirical data.

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