The Differential Information Content Of Unexpected Permanent And Temporary Components Of Quarterly Earnings Announcements PDF Download

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The Information Content of Guidance and Earnings

The Information Content of Guidance and Earnings
Author: Jonathan A. Milian
Publisher:
Total Pages:
Release: 2019
Genre:
ISBN:

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I compare the information content of quarterly earnings guidance and quarterly earnings by examining their associations with current and future stock returns when the two signals are bundled at earnings announcements. At the bundled announcement, I find a significantly stronger association between announcement returns and guidance news. From the day after the bundled announcement through the next earnings announcement, both signals generate abnormal return drifts of about 200 basis points. However, the timing of the post-announcement returns differs considerably. For guidance, about 50% of the post-announcement drift occurs at the next earnings announcement. In contrast, for earnings, about 20% of the preceding drift reverses at the next earnings announcement. Investor ignorance of the drift following guidance news coupled with a fixation on post-earnings announcement drift potentially explains this surprising difference in the timing of the post-announcement returns. Overall, this study indicates that bundled quarterly earnings guidance contains more information than quarterly earnings and that investors incorrectly overweight the earnings news and underweight the guidance news during the post-announcement period until the next earnings announcement.


Beyond the Numbers

Beyond the Numbers
Author: Angela K. Davis
Publisher:
Total Pages: 31
Release: 2011
Genre:
ISBN:

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Earnings press releases are the primary mechanism by which managers announce quarterly earnings and make other concurrent disclosures to investors and other stakeholders. A largely unexplored element of earnings press releases is the language that managers use throughout the press release, which we argue provides a unifying framework for these disclosures and an opportunity for managers to signal, both directly and more subtly, their expectations about future performance. We analyze the full texts of approximately 23,000 earnings press releases issued between 1998 and 2003 and examine whether the language used in these earnings press releases provides a signal about expected future firm performance and whether the market responds to this signal. Using categories derived from linguistic theory, we count words characterized as optimistic and pessimistic and construct a measure of managers' net optimistic language for each earnings press release. We find that this measure is positively associated with future ROA and generates a significant market response in a short window around the earnings announcement date. We include in our models the earnings surprise as well as other quantifiable, concurrent disclosures identified in prior research as associated with the market's reaction to earnings press releases. Our results support the premise that earnings press release language provides a signal regarding managers' future earnings expectations to the market and that the market responds to this signal. We interpret our evidence to suggest that managers use language in earnings press releases to communicate credible information about expected future firm performance.


Earnings Management

Earnings Management
Author: Joshua Ronen
Publisher: Springer Science & Business Media
Total Pages: 587
Release: 2008-08-06
Genre: Business & Economics
ISBN: 0387257713

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This book is a study of earnings management, aimed at scholars and professionals in accounting, finance, economics, and law. The authors address research questions including: Why are earnings so important that firms feel compelled to manipulate them? What set of circumstances will induce earnings management? How will the interaction among management, boards of directors, investors, employees, suppliers, customers and regulators affect earnings management? How to design empirical research addressing earnings management? What are the limitations and strengths of current empirical models?