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What do measures of real-time corporate sales say about earnings surprises and post-announcement returns?

Author

Listed:
  • Froot, Kenneth
  • Kang, Namho
  • Ozik, Gideon
  • Sadka, Ronnie

Abstract

We develop real-time proxies of retail corporate sales from multiple sources, including ∼50 million mobile devices. These measures contain information from both the earnings quarter (“within quarter”) and the period between the quarter-end and the earnings announcement date (“post quarter”). Our within-quarter measure is powerful in explaining quarterly sales growth, revenue surprises, and earnings surprises, generating average excess announcement returns of 3.4%. However, our post-quarter measure is related negatively to announcement returns and positively to post-announcement returns. When post-quarter private information is positive, managers, at announcement, provide pessimistic guidance and use negative language. This effect is more pronounced when, post-announcement, management insiders trade. We conclude that managers do not fully disclose their private information and instead bias their disclosures down when in possession of positive private information. The data suggest that they could be motivated in part by subsequent personal stock-trading opportunities.

Suggested Citation

  • Froot, Kenneth & Kang, Namho & Ozik, Gideon & Sadka, Ronnie, 2017. "What do measures of real-time corporate sales say about earnings surprises and post-announcement returns?," Journal of Financial Economics, Elsevier, vol. 125(1), pages 143-162.
    • Handle: RePEc:eee:jfinec:v:125:y:2017:i:1:p:143-162
    DOI: 10.1016/j.jfineco.2017.04.008
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    Keywords

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    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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