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Institutional Trading around Corporate News: Evidence from Textual Analysis

Author

Listed:
  • Alan Guoming Huang
  • Hongping Tan
  • Russ Wermers
  • Wei Jiang

Abstract

We examine institutional trading surrounding corporate news by combining a comprehensive database of newswire releases on U.S. firms with a high-frequency database of institutional trades. To identify the ability of institutions to predict or quickly interpret news, we form “news clusters” of related news about a particular firm that occurs in rapid succession. We find that institutions chiefly trade on the tone of news directly after the earliest news release in a cluster, and such news-motivated trading predicts returns over the following weeks. Our results suggest that institutional investors contribute to price efficiency through the speedy interpretation of public information.

Suggested Citation

  • Alan Guoming Huang & Hongping Tan & Russ Wermers & Wei Jiang, 2020. "Institutional Trading around Corporate News: Evidence from Textual Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 33(10), pages 4627-4675.
    • Handle: RePEc:oup:rfinst:v:33:y:2020:i:10:p:4627-4675.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhz136
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    Citations

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    Cited by:

    1. Aysan, Ahmet Faruk & Caporin, Massimiliano & Cepni, Oguzhan, 2024. "Not all words are equal: Sentiment and jumps in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    2. David Kreitmeir & Nathan Lane & Paul A. Raschky, 2020. "The Value of Names - Civil Society, Information, and Governing Multinationals on the Global Periphery," SoDa Laboratories Working Paper Series 2020-10, Monash University, SoDa Laboratories.
    3. Vinh Huy Nguyen & Suchismita Mishra & Pankaj K. Jain, 2022. "Institutional trading around repurchase announcements: An uphill battle," The Financial Review, Eastern Finance Association, vol. 57(3), pages 485-507, August.
    4. Zijia Du & Alan Guoming Huang & Russ Wermers & Wenfeng Wu, 2022. "Language and Domain Specificity: A Chinese Financial Sentiment Dictionary [The effects of analyst-country institutions on biased research: Evidence from target prices]," Review of Finance, European Finance Association, vol. 26(3), pages 673-719.
    5. Cunfei Liao & Guohao Tang & Xiaoying Xu, 2024. "Smart money or chasing stars: Evidence from northbound trading in China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1781-1803, April.
    6. Li, Yuanpeng & Shi, Haina & Zhou, Yi, 2021. "The influence of the media on government decisions: Evidence from IPOs in China," Journal of Corporate Finance, Elsevier, vol. 70(C).
    7. Onur Bayar & Emre Kesici, 2024. "The impact of social media on venture capital financing: evidence from Twitter interactions," Review of Quantitative Finance and Accounting, Springer, vol. 62(1), pages 195-224, January.
    8. Marshall A. Geiger & Sami Keskek & Abdullah Kumas, 2022. "Trading concentration and industry-specific information: an analysis of auto complaints," Review of Quantitative Finance and Accounting, Springer, vol. 59(3), pages 913-937, October.
    9. Akbari, Amir & Krystyniak, Karolina, 2021. "Government real estate interventions and the stock market," International Review of Financial Analysis, Elsevier, vol. 75(C).
    10. Fung, Scott & Obaid, Khaled & Tsai, Shih-Chuan, 2024. "Information acquisition and processing skills of institutions and retail investors around information shocks," Journal of Empirical Finance, Elsevier, vol. 77(C).
    11. Ben-Rephael, Azi & Cookson, J. Anthony & izhakian, yehuda, 2022. "Trading, Ambiguity and Information in the Options Market," SocArXiv ewunv, Center for Open Science.
    12. Huang, Alan Guoming & Wermers, Russ & Xue, Jinming, 2023. ""Buy the rumor, sell the news": Liquidity provision by bond funds following corporate news events," CFR Working Papers 23-07, University of Cologne, Centre for Financial Research (CFR).

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