Using realistic trading strategies in an agent-based stock market model

Abstract

The use of agent-based models (ABMs) has increased in the last years to simulate social systems and, in particular, financial markets. ABMs of financial markets are usually validated by checking the ability of the model to reproduce a set of empirical stylised facts. However, other common-sense evidence is available which is often not taken into account, ending with models which are valid but not sensible. In this paper we present an ABM of a stock market which incorporates this type of common-sense evidence and implements realistic trading strategies based on practitioners literature. We next validate the model using a comprehensive approach consisting of four steps: assessment of face validity, sensitivity analysis, calibration and validation of model outputs.