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

Date
2019-07-05
Authors
Huang, Julie
Bushee, Brian
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Abstract
This paper examines whether analysts and investors efficiently incorporate the informational cues from managerial linguistic complexity (e.g. Fog) on conference calls into their forecasts and trading decisions. We predict that managers use linguistic complexity to obfuscate before poor future earnings growth, but use linguistic complexity to provide informative disclosure before good future earnings growth. We find that the obfuscation (information) component of managerial Fog on a conference call is negatively (positively) associated with future earnings growth, and that the relations are generally stronger when there is a higher potential for earnings management during the period. We find that analyst forecast revisions efficiently respond to these informational signals in managerial Fog. However, while stock returns around the call are negatively associated with obfuscatory Fog, they are unrelated to informative Fog, which leads to a delayed positive return reaction to informative Fog after the call. Thus, while both analysts and investors appear to process the negative signal of managerial obfuscation, only analysts correctly interpret the positive signal of greater linguistic complexity due to more informative disclosure.
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Conference call, Linguistic complexity, Informative disclosure, Analyst forecasts
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