Managers’ Body Expansiveness, Investor Perceptions, and Firm Forecast Errors and Valuation

Abstract

We examine the relation between a measure of managers’ physical display—body expansiveness—and favorable reporting practices (in firm forecasts and valuation information) and performance (survival and funding success). We videotape 154 entrepreneurs pitching their business ideas, and use computer vision software to obtain information about speakers’ movements. We show that physical expansiveness correlates with higher forecast errors and proposed firm valuations and lower survival rates yet higher likelihood of funding success. We argue that investors may incorrectly interpret nonverbal communication in their assessments of entrepreneurs and propose a behavioral explanation. We further corroborate the proposed mechanism by studying investor perceptions of entrepreneurs’ personal characteristics. Overall, we shed light on an overlooked source of information—nonverbal behavior—and relate it to firm forecasting, valuation, survival, and financing success, which are important factors in the assessment of investment opportunities, deal structure, and monitoring.

Behavioral Economics of Accounting: A Review of Archival Research on Individual Decision Makers*

“…Dávila and Guasch (2021) study nonverbal behavior in videotapes of entrepreneurs pitching their business ideas. Specifically, they measure body expansiveness using OpenPose, an algorithm developed by the CMU Perceptual Computing Lab.…”

Renewing the resource‐based view: New contexts, new concepts, and new methods

“…These models have been applied to a variety of different sources of unstructured data, including letters to shareholders (Gamache, Neville, Bundy, & Short, 2020), earnings calls (Benton, Cobb, & Werner, 2022; Crilly, 2017; Guo, Sengul, & Yu, 2021), patent descriptions (Kaplan & Vakili, 2015; Kuhn, Younge, & Marco, 2020; Miric, Jia, & Huang, 2023), and online comments (Corritore, Goldberg, & Srivastava, 2020; Marchetti & Puranam, 2020), among others. More recently, scholars have also used machine learning techniques to analyze visual data, studying facial images (Choudhury, Wang, Carlson, & Khanna, 2019), body language (Dávila & Guasch, 2022), and even eye movements (Meißner & Oll, 2019) to quantify non‐verbal cues.…”

Machine learning methods in finance: Recent applications and prospects

“…Then, this novel measure enables the authors to study firm-CEO assignment frictions Choudhury et al (2019). construct a measure of executives' communication style by applying ML to transcripts and videos from interviews of emerging market CEOs Dávila and Guasch (2022). construct a measure of entrepreneurs' non-verbal communication style during pitch presentations with ML-based computer vision software and analyze its relation to firm valuations and funding success rates.The study byErel et al (2021) uses ML to measure director quality.…”