We develop a theoretical model to evaluate settings of artificial markets considering a realistic pricing mechanism. We show the model can evaluate the settings in an environment in which a dynamic micro mechanism plays an important role, for example, a price rebound after a sharp fall in stock markets. Styled facts, which are statistics for long term, can not evaluate such a dynamic situation. We emphasis that such a dynamic situation which the styled facts can not evaluates is very important to analyze market crush and/or market regulations.
2012 JSAI (The Japanese Society for Artificial Intelligence)