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<p>It is widely recognised that high-frequency traders (HFTs) rely on ultra-low-latency algorithmic systems that allow them to submit and withdraw orders at speeds far beyond human capability. The analysis presented in this study shows that a substantial share of HFT orders are cancelled within roughly 20 milliseconds of being placed. This behaviour enables traders to anticipate short-term price movements and exploit cross-market statistical arbitrage opportunities between the E-mini S&amp;P 500 futures contract and the SPDR S&amp;P 500 ETF. The evidence further indicates that these strategies generate economically meaningful profits even after accounting for transaction costs and that the resulting gains tend to persist over time. In contrast, traders without comparable low-latency infrastructure and advanced algorithmic systems are likely to face higher execution costs in such market environments. As a potential policy response, we advocate introducing batch auction mechanisms, which would introduce queuing risk for high-frequency traders and could ultimately improve overall market quality.</p>

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Speed, order cancellation, and market quality in electronic financial markets

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Viktor Manahov

摘要

It is widely recognised that high-frequency traders (HFTs) rely on ultra-low-latency algorithmic systems that allow them to submit and withdraw orders at speeds far beyond human capability. The analysis presented in this study shows that a substantial share of HFT orders are cancelled within roughly 20 milliseconds of being placed. This behaviour enables traders to anticipate short-term price movements and exploit cross-market statistical arbitrage opportunities between the E-mini S&P 500 futures contract and the SPDR S&P 500 ETF. The evidence further indicates that these strategies generate economically meaningful profits even after accounting for transaction costs and that the resulting gains tend to persist over time. In contrast, traders without comparable low-latency infrastructure and advanced algorithmic systems are likely to face higher execution costs in such market environments. As a potential policy response, we advocate introducing batch auction mechanisms, which would introduce queuing risk for high-frequency traders and could ultimately improve overall market quality.