A bright future for financial agent-based models

TL;DR

This paper discusses the potential of integrating neuropsychology and machine learning into agent-based financial models to enhance their realism and address previous criticisms, promising a significant advancement in computational economics.

Contribution

It proposes a novel approach combining cognitive biases and machine learning in agent-based models to improve realism in financial simulations.

Findings

Enhanced realism in financial agent-based models.

Integration of neuropsychological insights and machine learning.

Potential to address prior empirical criticisms.

Abstract

The history of research in finance and economics has been widely impacted by the field of Agent-based Computational Economics (ACE). While at the same time being popular among natural science researchers for its proximity to the successful methods of physics and chemistry for example, the field of ACE has also received critics by a part of the social science community for its lack of empiricism. Yet recent trends have shifted the weights of these general arguments and potentially given ACE a whole new range of realism. At the base of these trends are found two present-day major scientific breakthroughs: the steady shift of psychology towards a hard science due to the advances of neuropsychology, and the progress of artificial intelligence and more specifically machine learning due to increasing computational power and big data. These two have also found common fields of study in the form of computational neuroscience, and human-computer interaction, among others. We outline here the main lines of a computational research study of collective economic behavior via Agent-Based Models (ABM) or Multi-Agent System (MAS), where each agent would be endowed with specific cognitive and behavioral biases known to the field of neuroeconomics, and at the same time autonomously implement rational quantitative financial strategies updated by machine learning. We postulate that such ABMs would offer a whole new range of realism.