Agent based models of financial markets - rationality and social networks

In the thesis we focus on involving Agent-based models in modeling financial markets. In Agent-based models of economical systems, often called Agent-based computational economics (ACE), market price is established by actions and interactions of autonomous agents using heuristics or simple decision-making rules. This approach to modeling of financial markets provide us with better understanding of establishing market price then aggregate economical models which focuses exclusively on societally "optimal" equilibria assuming that they are achieved by informed and rational behavior of people. The thesis consists of two main parts. The first one, theoretical, is an introduction to agent based modeling, bounded rationality and social network Our concern in the second part of the thesis is a model of volatility on financial markets. This model is interesting example of agent based approach to creating economical models. However it contains some non-realistic assumption from which the most controversial is the space where agents interacts -- two dimensional lattice. In this part of the work the model is converted from two dimensional lattice to the networks which better corresponds to real social networks but we also experiment with another extension of the agent's decision-making function. The intended outcome of the work is verifying the quality of the model, to learn the effect of our model extensions on price volatility, overview of attributes of the particular networks and discussion whether such models could provide some valuable information to the economist which are interested in financial markets.