A Brief Review of Recent Artificial Market Simulation (Agent-Based Model) Studies for Financial Market Regulations and/or Rules

Abstract

This working review shows recent agent-based models for financial market (artificial market simulations) to discuss financial regulations and/or rules. This review aimed to introduce recent papers as many as possible. For more details of importance of discussion into design financial markets with artificial market models, contribution to society and how to build and use such models, see below:

https://ssrn.com/abstract=3403461.

It is very difficult to discuss about changing financial market regulations and/or rules by only using results of empirical studies. An artificial market, which is a kind of an agent-based model, can isolate the pure contribution of changing the regulations to the price formation and can treat situations that have never occurred. These are strong points of the artificial market simulation study. Recently, some artificial market studies contributed to discussion what financial regulations and rules should be, for example, price variation limits and short selling regulation whether preventing bubbles and crushes or not, tick size, usage rate of dark pools, rules for investment diversification, speed of order matching systems on financial exchanges, frequent batch auctions, how active funds that trade infrequently make a market more efficient, an interaction between leveraged ETF markets and underlying markets and micro-foundation of price variation model using intelligence of artificial market simulation studies:

https://ssrn.com/abstract=2710457.

I will review those studies.

Keywords: Artificial Market Simulation, Multi-Agent Model, Agent-Based Model, Financial Market Regulation

JEL Classification: G1, G18