Article contents
Misvaluation and Corporate Inventiveness
Published online by Cambridge University Press: 24 August 2020
Abstract
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
- 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.
References
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