Automatic Summaries of Earnings Releases: Attributes and Effects on Investors’ Judgments

Firms often include summaries with earnings releases. However, manager-generated summaries may be prone to strategic tone and content management compared to the disclosures they summarize. In contrast, computer algorithms can summarize large amounts of text without human intervention, and may provide useful summary information with less bias. We use multiple methods to provide evidence regarding the characteristics of automatic, algorithm-based summaries of earnings releases compared to summaries provided by managers. Results suggest that automatic summaries are generally less positively biased than management summaries, without sacrificing the extent to which the summaries capture relevant information. We then conduct an experiment to test whether these differing attributes of automatic and management summaries affect individual investors’ judgments. We find that 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. Overall, our results suggest that summaries affect investors’ judgments, but that such effects can differ for management and automatic summaries.