Sharks in the dark: Quantifying HFT dark pool latency arbitrage

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2023-11-07 DOI:10.1016/j.jedc.2023.104786
Matteo Aquilina , Sean Foley , Peter O'Neill , Thomas Ruf
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Abstract

We investigate stale reference pricing and liquidity provision in dark pools using proprietary, participant-level regulatory data. We show a substantial amount of stale trading occurs, imposing large costs on passive dark pool participants. Consistent with these costs, HFTs almost never provide liquidity in the dark, instead frequently consuming liquidity, in particular in order to take advantage of stale reference prices. Finally, we show that market design interventions randomizing dark execution times are successful at countering dark pool latency arbitrage, protecting passive providers of dark liquidity. Our results have substantial implications for practitioners and policymakers aiming to improve liquidity provision in dark pools.

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黑暗中的鲨鱼:量化高频交易暗池延迟套利
我们使用专有的、参与者级别的监管数据调查暗池中过时的参考定价和流动性供应。我们展示了大量过时交易的发生,给被动的暗池参与者带来了巨大的成本。与这些成本相一致的是,高频交易几乎从不在黑暗中提供流动性,而是经常消耗流动性,特别是为了利用过时的参考价格。最后,我们证明了随机化暗执行时间的市场设计干预能够成功地对抗暗池延迟套利,保护暗流动性的被动提供者。我们的研究结果对旨在改善暗池流动性供应的从业者和政策制定者具有重大意义。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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