This paper describes intermediate results on the analysis of micro- and macro- structures of a financial market. Instead of using conventional behavioral financial models, which consist of homogeneous decision making agents, we employ agent-based simulation approaches to the analysis. Our simulation model is characterized by 1) rational and non-rational agents with decision making strategies about trading the assets of either individual stocks or riskless assets; 2) an artificial market, in which the benefits or losses will occur based on the Brownian motion, and each agent trades its asset based on its benefits/losses and past pricing information. Using the model, the objective of the research is to investigate the effects of 1) the value at risk (VaR), 2) the concepts of portfolio insurance, and 3) the effects of herding behaviors among agents with decision making strategies. The simulation model have shown that 1) conventional risk management techniques in the literature are effective in the usual cases, 2) dynamics of asset pricing techniques so far are coincide with the theoretical results, however, 3) the market prices would become too worse compared with the theoretical ones, if i) risk management strategies would be too sensitive, or ii) there would exist so many investors with herding characteristics. The results implies that the agent-based approach is promising when the assumptions of the analysis are realistic and/or complex.
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