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

doi:10.1145/3677052.3698634

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 proceeding › Conference contribution

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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
Title of host publication	ICAIF'24: The 5th ACM International Conference on AI in Finance
DOIs	https://doi.org/10.1145/3677052.3698634
Publication status	Published - 2024

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10.1145/3677052.3698634

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Cite this

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title = "The Effect of Liquidity on the Spoofability of Financial Markets",

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{\textquoteright}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.",

author = "Anri Gu and Yongzhao Wang and Chris Mascioli and Mithun Chakraborty and Rahul Savani and Turocy, {Theodore L.} and Wellman, {Michael P.}",

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language = "English",

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AU - Gu, Anri

AU - Wang, Yongzhao

AU - Mascioli, Chris

AU - Chakraborty, Mithun

AU - Savani, Rahul

AU - Turocy, Theodore L.

AU - Wellman, Michael P.

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

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DO - 10.1145/3677052.3698634

M3 - Conference contribution

BT - ICAIF'24: The 5th ACM International Conference on AI in Finance

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