Earnings Announcements: Market (In)Attention; The Strategic Scheduling & Timing via SSRN
Stanford University – Graduate School of Business
University of California-Irvine
Jacob R. Thornock
University of Washington – Michael G. Foster School of Business
March 3, 2015
Journal of Accounting & Economics (JAE), Forthcoming
Rock Center for Corporate Governance at Stanford University Working Paper No. 201
Stanford University Graduate School of Business Research Paper No. 15-8
Abstract:
We investigate whether managers “hide” bad news by announcing earnings during periods of low attention, or by providing less forewarning of an upcoming earnings announcement. Our findings are consistent with managers reporting bad news after market hours, on busy days, and with less advance notice, and with earnings receiving less attention in these settings. Paradoxically, our findings indicate that managers also report bad news on Fridays, but we do not find lower attention on Fridays. Further, we find negative returns when the market is notified of an upcoming Friday earnings announcement, which is consistent with investors inferring forthcoming bad news.
Earnings Announcements: Market (In)Attention; The Strategic Scheduling & Timing – Introduction
In this paper, we revisit a long-standing but still unresolved question: do managers “hide” bad earnings news by announcing during periods of low market attention? Or, conversely: do managers “highlight” good earnings news by announcing earnings during periods of high market attention? We posit three necessary conditions for an effective hiding/highlighting strategy. First, to be able to hide bad news, managers must change their earnings announcement (“EA”) timing somewhat frequently. A deviation from a long-standing pattern of earnings announcements timing could attract attention to the very news the manager is trying to hide. Second, there must be variation in market attention that is predictable to the manager ex-ante—random variation in attention would not allow for strategic timing of bad or good news. Third, we must observe that managers do tend to announce more negative (positive) earnings news during periods of lower (higher) market attention. We also examine an additional potential strategy for reducing attention to bad news: by scheduling earnings announcements with less advance notice or “lead-time.”
We construct a novel database of over 120,000 precise EA dates and times to investigate the timing of earnings announcements by hour and by weekday.1 We find that firms frequently change the timing of their earnings announcements: for example, within any given year, 81.6% of firms change their quarterly EA weekday at least once, and 25.6% change whether they report before, during, or after market hours. Although just 7.6% of all earnings announcements happen on Fridays, 51.4% of firms have at least one Friday announcement during our sample period. Managers’ intent is unobservable, but the majority of these changes in EA times are likely made for administrative, scheduling, or other benign reasons. The high frequency of benign changes is precisely the camouflage needed for managers to occasionally switch their EA timing for strategic purposes without raising alarm, consistent with the first condition.
We turn next to the second condition: that lulls and peaks in market attention must be exante predictable in order for managers to shift bad (good) news into times where the market is paying less (more) attention. We examine three specific times during which prior research has speculated that market attention differs: before versus after the close of regular trading hours; on Mondays through Thursdays versus Fridays; and on “slow” versus “busy” news days, based on the total number of firms that are reporting earnings. We employ four empirical proxies to investigate temporal variation in market attention: (i) the number of earnings-related news articles; (ii) the speed with which analysts incorporate the earnings news into future earnings forecasts; (iii) EDGAR 8-K downloads; and (iv) abnormal Google search volume. The advantage of these attention measures is that they are user-oriented, related to information processing, and measured on a timely basis.
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