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 language | English |
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Title of host publication | ICAIF 2024 - 5th ACM International Conference on AI in Finance |
Pages | 239-247 |
Number of pages | 9 |
ISBN (Electronic) | 9798400710810 |
DOIs | |
Publication status | Published - 14 Nov 2024 |
Keywords
- Agent-Based Simulation
- Liquidity
- Market Manipulation
- Spoofing