Automatic summarization of earnings releases: attributes and effects on investors’ judgments

Abstract

Firms often include summaries with earnings releases. However, manager-generated summaries may be prone to strategic tone and content management, compared to the underlying disclosures they summarize. In contrast, computer algorithms can summarize text without human intervention and may provide useful summary information with less bias. We use multiple methods to provide evidence regarding the characteristics of algorithm-based summaries of earnings releases compared to those provided by managers. Results suggest that automatic summaries are generally less positively biased, often without sacrificing 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 and that these effects differ for management and automatic summaries.