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Misvaluation and Corporate Inventiveness

Published online by Cambridge University Press:  24 August 2020

Ming Dong Open the ORCID record for Ming Dong [Opens in a new window] ,
David Hirshleifer Open the ORCID record for David Hirshleifer [Opens in a new window]  and
Siew Hong Teoh Open the ORCID record for Siew Hong Teoh [Opens in a new window]
Ming Dong
Affiliation:
York University Schulich School of Businessmdong@schulich.yorku.ca
David Hirshleifer*
Affiliation:
University of California at Irvine Merage School of Business
Siew Hong Teoh
Affiliation:
University of California at Irvine Merage School of Businesssteoh@uci.edu
*
david.h@uci.edu (corresponding author)
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Abstract

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We test how market overvaluation affects corporate innovation. Estimated stock overvaluation is strongly associated with measures of innovative inventiveness (novelty, originality, and scope), as well as research and development (R&D) and innovative output (patent and citation counts). Misvaluation affects R&D more via a nonequity channel than via equity issuance. The sensitivity of innovative inventiveness to misvaluation increases with share turnover and overvaluation. The frequency of exceptionally high innovative inputs/outputs increases with overvaluation. This evidence suggests that market overvaluation may generate social value by increasing innovative output and encouraging firms to engage in “moon shots.”

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 56 , Issue 8 , December 2021 , pp. 2605 - 2633
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

For helpful comments, we thank Malcolm Baker, Itzhak Ben-David, Justin Birru, Tony Cookson, Richard Crowley, Peter DeMarzo, Robin Greenwood, Jarrad Harford (the editor), Michael Hirshleifer, Ming Huang, Mark Kamstra, Byoung Kang, Jung-Wook Kim, Dongmei Li, Chris Polk, Eric So, Xuan Tian (the referee), Sheridan Titman, John Wei, Mike Weisbach, and Zhaoxia Xu; conference discussants, Tao Chen, Henrik Cronqvist, Jody Grewal, Adrien Matray, Anywhere Sichochi, and Noah Stoffman; and conference and seminar participants at the 2015 China International Conference in Finance, 2017 Financial Accounting and Reporting Section meeting, 2017 National Bureau of Economic Research (NBER) Behavioral Finance meeting, 2017 Ohio State University Alumni conference, 2018 American Finance Association conference, 2018 Harvard Business School (HBS) Information, Markets, and Organizations (IMO) conference, City University of London, Hong Kong Polytechnic University, INSEAD, Laval University, McMaster University, Nanyang Technological University, National University of Singapore, Singapore Management University, University of Glasgow, University of Iowa, University of Notre Dame, University of Roma, University of Southern California, University of Texas Austin, University of Vienna, and Washington University. We thank Zheng Sun for help with the mutual fund flow measure. We thank the National Center for the Middle Market (USA) and the Social Science and Humanities Research Council of Canada (SSHRC) for financial support.

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