Designing agent-based market models

In light of the growing interest in agent-based market models, we bring together several earlier works in which we considered the topic of selfconsistent market modelling. Building upon the binary game structure of Challet and Zhang, we discuss generalizations of the strategy reward scheme such that the agents seek to maximize their wealth in a more direct way. We then examine a disturbing feature whereby such reward schemes, while appearing microscopically acceptable, lead to unrealistic market dynamics (e.g. instabilities). Finally, we discuss various mechanisms which are responsible for re-stabilizing the market in reality. This discussion leads to a ‘toolbox’ of processes from which, we believe, successful market models can be constructed in the future. Oxford Center for Computational Finance working paper: OCCF/010702