Agent-based Simulation of Financial Market

Agent-based modeling (ABM) is a powerful tool for simulating the behavior of complex systems, including financial markets. The purpose of this study is to develop a robust ABM of financial markets to further investigate the impact of tick size on key market indicators: spread, price volatility, trading volume and number of trades. The model incorporates different types of agents, including fundamentalists, chartists and market maker, who interact within a double auction order book. To evaluate the impact of tick size, 250 simulations with different tick sizes were run. Pearson correlation coefficients and regression analysis were used to analyze the relationship between tick size and market indicators. The results indicate a very strong positive relationship between tick size and spread, a weak but significant positive relationship with price volatility, a moderate positive relationship with trading volume, and a weak negative relationship with the number of transactions. These results provide insight into how changes in market microstructure, such as tick size adjustments, can affect market dynamics.