Analysis of the Impact of High-Frequency Trading on Artificial Market Liquidity

TL;DR

This study uses agent-based simulations to analyze how high-frequency trading influences key market liquidity indicators, revealing improvements and proposing execution rate as a new measure.

Contribution

It systematically examines the relationship between high-frequency trading and liquidity indicators, introducing execution rate as a novel metric for market liquidity assessment.

Findings

HFT participation improves liquidity indicators more than no HFT.

Market liquidity correlates with execution rate, suggesting its use as a new indicator.

Simulation results align with empirical literature findings.

Abstract

Many empirical studies have discussed market liquidity, which is regarded as a measure of a booming financial market. Further, various indicators for objectively evaluating market liquidity have also been proposed and their merits have been discussed. In recent years, the impact of high-frequency traders (HFTs) on financial markets has been a focal concern, but no studies have systematically discussed their relationship with major market liquidity indicators, including volume, tightness, resiliency, and depth. In this study, we used agent-based simulations to compare the major liquidity indicators in an artificial market where an HFT participated was compared to one where no HFT participated. The results showed that all liquidity indicators in the market where an HFT participated improved more than those in the market where no HFT participated. Furthermore, as a result of investigating the correlations between the major liquidity indicators in our simulations and the extant empirical literature, we found that market liquidity can be measured not only by the major liquidity indicators but also by execution rate. Therefore, it is suggested that it could be appropriate to employ execution rate as a novel liquidity indicator in future studies.