Research on fat-tail phenomenon via artificial stock market modeling

As a typical stylized fact in stock market, fat-tail phenomenon has been widely concerned and applied to risk management practice, while the mechanism of its production has been a mystery for a long time. Based on the discussion of the modeling paradigms of the emerging agent-based computational finance, classical finance and behavioral finance, this paper deems that the later two models cannot study fat-tail phenomenon. The agent-based computational finance model has great potential, but its ability to solve financial problems is impeded by the confused modeling solutions. In this paper, an agent-based modeling approach for computational finance is presented. According to the new approach, a simple and analysable model is established. The evidence that market microstructure can produce fat-tail phenomenon has been found, and its mechanism has been analyzed. Results and conclusions of this study will influence ideas of applying fat-tail phenomenon to risk management.