This paper surveys learning-to-forecast experiments (LtFEs) with human subjects to test
theories of expectations and learning. Subjects must repeatedly forecast a market price …

This paper reviews the development of agent-based (computational) economics (ACE) from
an econometrics viewpoint. The review comprises three stages, characterizing the past, the …

In recent “learning to forecast” experiments (Hommes et al. 2005), three different patterns in
aggregate price behavior have been observed: slow monotonic convergence, permanent …

This book aims to answer two questions that are fundamental to the study of agent-based
economic models: what is agent-based computational economics and why do we need …

In this paper we address the question of how individuals form expectations and invent,
reinforce, and update their forecasting rules in a complex world. We do so by fitting a novel …

Recent turmoil on global financial markets has led to a discussion on which policy measures
should or could be taken to stabilize financial markets. One such a measure that resurfaced …

The traditional financial paradigm seeks to understand financial markets by using models in
which markets are perfect, which includes agents who are “rational” and update their beliefs …

An agent-based model (ABM) is a computational model which can simulate the actions and
interactions of individuals and organisations, in complex and realistic ways. Even a simple …

In this paper we investigate the effects of network topologies on asset price dynamics. We
introduce network communications into a simple asset pricing model with heterogeneous …

In this paper we explore how specific aspects of market transparency and agents' behavior
affect the efficiency of the market outcome. In particular, we are interested whether learning …