Navigating the Stock Market: Modeling Wealth Exchange and Network Interaction with Loss Aversion, Disposition Effect and Anchoring and Adjustment Bias

This study aims to integrate meta-analysis into agent-based models and provide foundational insights into biased agent interactions. It delves deeply into the effects of various behavioral biases such as anchoring, disposition effect, loss aversion, and others on market dynamics and investor decisions. Using agent-based models, it presents simulations of market scenarios and investor behaviors, emphasizing the impact of individual decisions on market dynamics. The innovative approach of this study lies in integrating behavioral finance theories with real market data, offering a nuanced analysis of market behaviors. This work contributes a new perspective to behavioral finance and encourages the use of agent-based models to deepen our understanding of market dynamics and investor behaviors, which can be helpful in financial market analysis and policy-making. This study aims to provide a foundational framework for those looking to integrate meta-analysis into agent-based models and explore biased agent behaviors. The findings demonstrate the ability to model the interactions of loss aversion, disposition effect, and anchoring and adjustment bias taking into account agents' socio-demographic and psychological factors, as close to the real world as possible. The results offer highly favorable forecasts for modeling human behaviors more accurately in portfolio optimizations and for expanding the applications of Generalized Artificial Intelligence in financial market implementations.