The Effect of Liquidity on the Spoofability of Financial Markets

Anri Gu, Yongzhao Wang, Chris Mascioli, Mithun Chakraborty, Rahul Savani, Theodore L. Turocy, Michael P. Wellman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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4 Downloads (Pure)

Abstract

We investigate the relationship between market liquidity and spoof- ing, a manipulative practice involving the submission of deceptive orders aimed at misleading other traders. Utilizing an agent-based market simulator, we model markets with varying levels of liquidity, adjusting the spread and intervals of a market maker’s orders to control liquidity. Within these simulated markets, we evaluate the effectiveness of two novel spoofing strategies against a benchmark approach. Our experiments show that in high-liquidity markets, spoofing is substantially less profitable and less detrimental to other traders compared to their low-liquidity counterparts. Additionally, we identify two distinct spoofing behavior regimes based on liq- uidity, each of which employ drastically different profit-making strategies. Finally, building on our quantitative findings, we iden- tify and expound upon the mechanisms through which liquidity mitigates market manipulation.
Original languageEnglish
Title of host publicationICAIF 2024 - 5th ACM International Conference on AI in Finance
Pages239-247
Number of pages9
ISBN (Electronic)9798400710810
DOIs
Publication statusPublished - 14 Nov 2024

Keywords

  • Agent-Based Simulation
  • Liquidity
  • Market Manipulation
  • Spoofing

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