In this study, an artificial market approach, which is a new agent-based approach to investigate foreign exchange markets, is proposed. Using this approach, three emergent phenomena of markets were explained. First, in order to investigate the learning patterns of actual dealers, we held an interview with a dealer. Second, based on the field data acquired, we constructed a multiagent model of a market using genetic algorithms. Finally, the emergent phenomena of markets were analyzed using the simulation results of the model. The results showed that the interaction between the agents' forecasts and the relationship of demand and supply caused the phase transition of forecast variety. The three emergent phenomena were explained by the phase transition. This approach, therefore, integrates the fieldwork and the multiagent model, and provide quantitative explanation of the micro-macro relation in markets.