Do Analysts and Investors Efficiently Respond to Managerial Linguistic Complexity during Conference Calls?

• 成果类型: Article
• 署名作者: Bushee, Brian J.; Huang, Ying (Julie)
• 署名单位: University of Pennsylvania; Pennsylvania Medicine; University of Louisville
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/TAR-2019-0358
• 发表日期: 2024
• 页码: 143-168
• 关键词: financial statement complexity; earnings conference calls; information-content; institutional investors; Textual analysis; management; disclosure; determinants; decreases; fd

摘要

This paper examines whether analysts and investors efficiently incorporate the informational signals from managerial linguistic complexity (e.g., Fog) into their forecasts and trading decisions. We predict that a manager's Fog during a conference call provides a signal of their private information through their willingness to engage with analyst questions. We find that informative (obfuscatory) managerial Fog provides a positive (negative) signal of future earnings growth. We also find that analysts efficiently revise their forecasts to both positive and negative signals, whereas investors only correctly interpret obfuscation during the call; there is a delayed price reaction to informative Fog. However, when buy-side investors ask questions during a call, we find an efficient price reaction to informative Fog. Our findings highlight an important benefit of two-way interactive disclosures and underline the importance of active call participation for efficiently incorporating linguistic signals of managers' private information.