An agent-based model for designing a financial market that works well

TL;DR

This paper introduces an agent-based artificial market model to aid in designing effective financial markets, addressing complex interactions and impacts of rule changes through simulation.

Contribution

It presents a novel agent-based model specifically aimed at designing financial markets that function effectively, building on previous models and case studies.

Findings

Model helps explain impacts of rule changes on market behavior

Simulation results support effective market design strategies

Case study on tick size reduction demonstrates model's utility

Abstract

Designing a financial market that works well is very important for developing and maintaining an advanced economy, but is not easy because changing detailed rules, even ones that seem trivial, sometimes causes unexpected large impacts and side effects. A computer simulation using an agent-based model can directly treat and clearly explain such complex systems where micro processes and macro phenomena interact. Many effective agent-based models investigating human behavior have already been developed. Recently, an artificial market model, which is an agent-based model for a financial market, has started to contribute to discussions on rules and regulations of actual financial markets. I introduce an artificial market model to design financial markets that work well and describe a previous study investigating tick size reduction. I hope that more artificial market models will contribute to designing financial markets that work well to further develop and maintain advanced economies.