Foundations for a Framework for Multiagent-Based Simulation of Macrohistorical Episodes in Financial Markets

Abstract

Questions about methodology and model design are subject to constant debate in the emerging field of agent-based modelling and simulation. This article intends to make progress on some of the more foundational aspects affecting method and design. Our primary focus is on a much neglected area of agent-based modelling, namely that of large-scale, spatio-temporal phenomena in financial markets. We argue that multiagent-based models are ideally suited to tackle this class of problems, but that as of yet simulation research has not delivered the methods and tools necessary for this task. The lack of a methodological framework tailored to this complex research object, due in part to a persistent coloration of research questions and interests in positivist shades, is an evident obstacle to progress. We hold that simulation research in finance should set its own methodological agenda, and propose that the mechanism-centric philosophy of critical realism is moved to the centre stage. Our framework encourages researchers to be mindful of existing knowledge and insight in finance without being kept hostage to it and to embrace the historic turn and look out for synergies in qualitative research.