The field of artificial economics (AE) embraces a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The overarching principle of AE is the analysis of aggregate properties of artificial economies populated by...

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering) of financial markets have a possible explanation in the interactions among agents. However, the complexity, originating from the presence of non-linearity and interactions, often...

A growing body of recent literature allows for heterogenous trading strategies and limited rationality of agents in behavioral models of financial markets. More and more, this literature has been concerned with the explanation of some of the stylized facts of financial markets. It now seems that...

We derive microscopic foundations for a well-known probabilistic herding model in the agent-based finance literature. Lo and behold, the model is quite robust with respect to behavioral heterogeneity, yet structural heterogeneity, in the sense of an underlying network structure that describes...

In this chapter we present a stylized financial agent-based model able to reproduce some important regularities emerging in financial time series . Following Tedeschi et al. (Eur Phys J B, 71(4), 489–497, 2009) and Tedeschi et al. (J Econ Behav Organ, 81(1), 82–96, 2012c), we show how an...