The Power of Voice: Managerial Affective States and Future Firm Performance

Authors

  • WILLIAM J. MAYEW,

  • MOHAN VENKATACHALAM

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    • Mayew and Venkatachalam are with the Fuqua School of Business, Duke University. Acting Editor: David Hirshleifer We acknowledge helpful comments and suggestions from two anonymous referees, Dan Ariely, Jim Bettman, Lauren Cohen, Patricia Dechow, Lisa Koonce, Feng Li, Mary Frances Luce, Greg Miller, Chris Moorman, Chris Parsons, Eddie Riedl, Katherine Schipper, Shyam Sunder, Paul Tetlock, T.J. Wong, and workshop participants at Barclays Global Investors, University of California at Berkeley, Chinese University of Hong Kong, University of Connecticut, Cornell University, Duke Finance Brown Bag, Financial Research Association 2008 conference, Fuqua Summer Brown Bag, Journal of Accounting Auditing and Finance 2008 Conference, Massachusetts Institute of Technology, University of Miami, Penn State University, Queens University, Rice University, University of Toronto, and Vanderbilt University. We also thank Amir Liberman and Albert De Vries of Nemesysco for helpful discussions and for assistance in extracting the LVA metrics into machine readable format for our academic use. Excellent research assistance was provided by Daniel Ames, Erin Ames, Jacob Ames, Patrick Badolato, Zhenhua Chen, Ankit Gupta, Sophia Li, Mark Uh, and Yifung Zhou.


ABSTRACT

We measure managerial affective states during earnings conference calls by analyzing conference call audio files using vocal emotion analysis software. We hypothesize and find that, when managers are scrutinized by analysts during conference calls, positive and negative affects displayed by managers are informative about the firm's financial future. Analysts do not incorporate this information when forecasting near-term earnings. When making stock recommendation changes, however, analysts incorporate positive but not negative affect. This study presents new evidence that managerial vocal cues contain useful information about a firm's fundamentals, incremental to both quantitative earnings information and qualitative “soft” information conveyed by linguistic content.

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