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Corporate jets and private meetings with investors

Journal of Accounting and Economics 2018 65(2-3), 358-379
We use corporate jet flight patterns to identify private meetings with investors that are ex ante unobservable to non-participants. Using approximately 400,000 flights, we proxy for private meetings with “roadshows,” defined as three-day windows that include flights to money centers and to non-money centers in which the firm has high institutional ownership. Roadshows exhibit greater abnormal stock reactions, analyst forecast activity, and absolute changes in local institutional ownership than other flight activity. We also find positive trading gains in firms with more complex information and infrequent private meetings, suggesting that roadshows provide participating investors an advantage over non-participating investors.

Linguistic Complexity in Firm Disclosures: Obfuscation or Information?

Journal of Accounting Research 2018 56(1), 85-121
ABSTRACT Prior research generally interprets complex language in firms’ disclosures as indicative of managerial obfuscation. However, complex language can also reflect the provision of complex information; for example, informative technical disclosure. As a consequence, linguistic complexity commingles two latent components—obfuscation and information—that are related to information asymmetry in opposite directions. We develop a novel empirical approach to estimate these two latent components within the context of quarterly earnings conference calls. We validate our estimates of these two latent components by examining their relation to information asymmetry. Consistent with our predictions, we find that our estimate of the information component is negatively associated with information asymmetry while our estimate of the obfuscation component is positively associated with information asymmetry. Our findings suggest that future research on linguistic complexity can construct more powerful tests by separately examining these two latent components of linguistic complexity.