Agent-based models: Herd instinct in single-asset financial markets

In financial markets, herd behavior is defined as the tendency of investors to mimic the actions of other investors instead of relying on their individual analyses. This study utilizes an agent-based model to investigate the dynamics of such collective behaviors and their effects on financial markets. Agent-based models simulate each investor as an independent decision-maker while also considering the interactions among these individuals. These interactions are critically important in demonstrating how herd behaviors can initiate in the market and potentially transform market dynamics. The model employed in the research simulates decision-making processes of each investor agent based on their own set of information and market observations, while also taking into account the decisions of other agents. This interactive process illustrates how herd behaviors can emerge over time and how market trends can spread rapidly. The study highlights the potential of agent-based models in understanding phenomena such as sudden price movements and market bubbles. The findings underscore the importance of such models in developing risk management and regulatory strategies within financial markets.