Artificial stock markets are built with diffuse priors in mind regarding trading strategies
and price formation mechanisms. Diffuse priors are a natural consequence of the
unknown relation between the various elements that drive market dynamics and the large
variety of market organizations, findings, however, might hold only within the specific market
settings. In this paper we propose a framework for building agent-based artificial stock
markets. We present the mechanism of the framework based on a previously identified list
of organizational and behavioural aspects. Within the framework experiments with arbitrary
many trading strategies, acting in various market organizations can be conducted in a
flexible way, without changing its architecture. In this way experiments of other artificial
stock markets, as well as theoretical models can be replicated and their findings compared.
Comparisons of the different experimental results might indicate whether findings are due
to traders’ behaviour or to the chosen market structure and could suggest how to improve
market quality