Earnings announcement return extrapolation

• 成果类型: Article
• 署名作者: Ertan, Aytekin; Karolyi, Stephen A.; Kelly, Peter W.; Stoumbos, Robert
• 署名单位: University of London; London Business School; Carnegie Mellon University; University of Notre Dame; Columbia University
• 刊物名称: REVIEW OF ACCOUNTING STUDIES
• ISSN/ISSBN: 1380-6653
• DOI: 10.1007/s11142-021-09593-w
• 发表日期: 2022
• 页码: 185-230
• 关键词: information; investor; IMPACT; news; attention; patterns; driven

摘要

We propose that extrapolative beliefs about earnings announcement (EA) returns may contribute to the understanding of EA return patterns. We construct a theoretically motivated measure of extrapolative investors' expectations based on a stock's recent history of EA returns. We then show that this measure explains cross-sectional variation in stock returns and investor behavior around EAs. Stocks expected to have high EA returns, according to our measure, experience predictable increases in prices before EAs and predictable decreases afterward. These patterns are economically significant: investors that buy (sell) a portfolio that is long firms with high recent EA returns and short firms with low recent EA returns in the pre-EA (post-EA) period earn daily five-factor abnormal returns of 16.1 bps (18.3 bps). Using individual investor trades data and a measure of institutional trading, we find that individual and institutional investors are more likely to purchase stocks with high recent EA returns, consistent with at least a subset of investors forming extrapolative beliefs about EA returns.