Automatic Summarization of Corporate Disclosures

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Abstract

In practice, key disclosures such as earnings releases and MD&A often include summaries.
These manager-provided summaries, however, may be prone to strategic tone and content
management compared to the underlying disclosures they summarize. In contrast, automatic,
algorithm-based summaries have the potential to provide useful summary information with less
bias than management summaries. We provide archival evidence on the use of summaries in
practice and conduct three experiments to investigate how management and automatic
summaries compare on several dimensions (e.g., bias, usefulness), and how summaries affect
investor information processing, beliefs about firm fundamentals (e.g., performance, risk), and
valuation judgments. Our results suggest that automatic summaries compare favorably to
management summaries for earnings releases, but fare less well for MD&A. Importantly,
investors who receive an earnings release accompanied by an automatic summary arrive at more
conservative (i.e., lower) valuation judgments, and are more confident in those judgments,
compared to investors who receive the same earnings release with a management summary. Our
findings provide important input to recent discussions by policy makers on the use of summaries
for corporate disclosures.

Author

• Stephan Hollander, Tilburg University