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Algorithmic trading and intra-industry information transfer

Xiaori Zhang et al.

Review of Accounting Studies2026https://doi.org/10.1007/s11142-026-09954-3article
FT50AJG 4ABDC A*
Weight
0.50

Abstract

We examine the role of algorithmic trading in transmitting intra-industry information. Using a comprehensive U.S. sample, we find that algorithmic trading amplifies the stock price reactions of non-announcing firms to the earnings announcements of industry peers that report earlier in the same fiscal quarter. Further analyses reveal that sector exchange-traded funds serve as an important channel through which algorithmic trading facilitates the diffusion of industry information. Moreover, the effect of algorithmic trading strengthens when peers’ information is more relevant to the focal firm and of higher reporting quality. Finally, our evidence suggests that these effects reflect enhanced price discovery rather than temporary overreaction. Overall, our findings illuminate the informational role of algorithmic trading and its implications for market efficiency.

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https://doi.org/https://doi.org/10.1007/s11142-026-09954-3

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@article{xiaori2026,
  title        = {{Algorithmic trading and intra-industry information transfer}},
  author       = {Xiaori Zhang et al.},
  journal      = {Review of Accounting Studies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s11142-026-09954-3},
}

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Algorithmic trading and intra-industry information transfer

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.