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The Effects of Concurrent Earnings Releases and Calendar-Time Clustering on the Information Content of Periodic SEC Filings
Edward Xuejun Li,
Michigan State University
K. Ramesh, Michigan State University
ABSTRACT. We explore the phenomenon of concurrent earnings releases in the EDGAR period and find that, on average, 10-Q, 10-KSB and 10-QSB filings do not have statistically significant information content once we control for the effect of concurrent earnings releases. In addition, we find that the information content of 10-K filings is confounded by the turn-of-the-quarter effects documented in the extant finance research that suggests that quarter-end trading volume and price movements are influenced by the performance-based incentives of institutional investors and other traders. Our results indicate that the statistically significant market reactions for 10-K filings are limited to those filed around calendar quarter ends. Furthermore, we find that, while earnings releases explain roughly 70 percent of the calendar-time variation in analyst forecast revisions, analysts merely react to the release of periodic SEC filings.
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