Phase transition in a foreign exchange market - Analysis based on an artificial market approach

In this study, we propose an artificial market approach, which is a new age nt-based approach to foreign exchange market studies. Using this approach, emergent phenomena of markets such as the peaked and fat-tailed distributio n of rate changes were explained. First, we collected the field data throug h interviews and questionnaires with dealers and found that the features of dealer interaction in learning were similar to the features of genetic ope rations in biology. Second, we constructed an artificial market model using a genetic algorithm. Our model was a multiagent system with agents having internal representations about market situations. Finally, we carried out c omputer simulations with our model using the actual data series of economic fundamentals and political news. We then identified three emergent phenome na of the market. As a result, we concluded that these emergent phenomena c ould be explained by the phase transition of forecast variety, which is due to the interaction of agent forecasts and the demand-supply balance. In ad dition, the results of simulation were compared with the field data. The fi eld data supported the simulation results. This approach therefore integrat es fieldwork and a multiagent model, and provides a quantitative explanatio n of micro-macro relations in markets.