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Information and Investor Behavior Surrounding Earnings Announcements

Author

Listed:
  • C. José García
  • Begoña Herrero
  • Ana M. Ibáñez

Abstract

The goal of this paper is to analyze the impact of annual earnings announcements on the market through the order flow data in addition to the usual transaction data. In this respect, examining order flow data can potentially reveal valuable information that is not available from transaction data. In fact, the data allow us to test hypotheses about asymmetric information and investor behavior and to test if the behavior varies with investor sophistication. In addition, the paper tries to identify the determinants of the impact on a firm's value using assumptions about investor behavior.

Suggested Citation

  • C. José García & Begoña Herrero & Ana M. Ibáñez, 2014. "Information and Investor Behavior Surrounding Earnings Announcements," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 15(2), pages 133-143, April.
    • Handle: RePEc:taf:hbhfxx:v:15:y:2014:i:2:p:133-143
    DOI: 10.1080/15427560.2014.908882
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    Cited by:

    1. Siyi Liu & Xin Liu & Chuancai Zhang & Lingli Zhang, 2023. "Institutional and individual investors' short‐term reactions to the COVID‐19 crisis in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4333-4355, December.
    2. Banerjee, Ameet Kumar & Pradhan, H.K., 2022. "Intraday analysis of macroeconomic news surprises, and asymmetries in Indian benchmark bond," Finance Research Letters, Elsevier, vol. 45(C).
    3. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).

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