Intangible Assets, Information Complexity, and Analysts’ Earnings Forecasts

Authors

  • Feng Gu,

    Corresponding author
      Feng Gu, Department of Accounting & Law, Jacobs Management Center, State University of New York at Buffalo, NY 14260-4000, USA.
      e-mail: gu@bu.edu and fgu@buffalo.edu
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  • Weimin Wang

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       The authors are respectively from the State University of New York at Buffalo and Tulane University, USA.


Feng Gu, Department of Accounting & Law, Jacobs Management Center, State University of New York at Buffalo, NY 14260-4000, USA.
e-mail: gu@bu.edu and fgu@buffalo.edu

Abstract

Abstract:  We examine the relation between analysts’ earnings forecasts and firms’ intangible assets, including technology-based intangibles, brand names, and recognized intangibles. We predict that high information complexity of intangible assets increases the difficulty for analysts to assimilate information and increases analysts’ forecast error of intangibles-intensive firms. We find a positive association between analysts’ forecast error and the firm's intangible intensity that deviates from the industry norm. We also find that analysts’ forecast errors are greater for firms with diverse and innovative technologies. In contrast, analysts’ forecast errors are smaller for biotech/pharmaceutical and medical equipment firms that are subject to intangibles-related regulation.

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