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<p>The rapid growing of algorithmic trading (AT) has been playing an increasingly important role in shaping financial market in recent years. Although many scholars have studied the impact of AT on market volatility, the evidence they provided is inconsistent. Whether and how AT influence on market volatility is still not clear, especially for emerging markets. In this paper, using level 2 quotations from Chinese market, we answered the question. By introducing multiple mediator model, we found that AT can significantly reduce market volatility. In addition to the influence of AT itself, the sentiment effect accounts for approximate 1/4 of the influence, and a very small portion, about 4%, of the influence can be explained by herd effect. Besides, it also illustrated that the influences of AT are more sensitive in main board, rather than in GEM board. Nevertheless, the sentiment effect has been playing plays more important role in the influence of AT in GEM board. These findings provide new insights into previous inconsistent evidence regarding the influence of AT on market volatility. They also have important implications for investment strategies and market regulations.</p>

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Research on the impact of algorithmic trading on market volatility

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月17日

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  • Dan Yang,
  • Yang Yang,
  • Jia Luo,
  • Zeming Wang,
  • Haowei Sha

摘要

The rapid growing of algorithmic trading (AT) has been playing an increasingly important role in shaping financial market in recent years. Although many scholars have studied the impact of AT on market volatility, the evidence they provided is inconsistent. Whether and how AT influence on market volatility is still not clear, especially for emerging markets. In this paper, using level 2 quotations from Chinese market, we answered the question. By introducing multiple mediator model, we found that AT can significantly reduce market volatility. In addition to the influence of AT itself, the sentiment effect accounts for approximate 1/4 of the influence, and a very small portion, about 4%, of the influence can be explained by herd effect. Besides, it also illustrated that the influences of AT are more sensitive in main board, rather than in GEM board. Nevertheless, the sentiment effect has been playing plays more important role in the influence of AT in GEM board. These findings provide new insights into previous inconsistent evidence regarding the influence of AT on market volatility. They also have important implications for investment strategies and market regulations.