Effect of investor inattention on price drifts following analyst recommendation revisions

Abstract

The study explores stock price dynamics after analyst recommendation revisions. Following the previous literature that documents significant post‐recommendation stock price drifts and attributes them to investor inattention to company‐specific events, I hypothesize that if on the day when a recommendation revision with respect to a stock was issued, the sign of the stock's abnormal return was opposite to the direction of the revision, then it means that investors were especially inattentive to the revision and that the subsequent price drift should be more pronounced. Analysing a large sample of analyst recommendation revisions, I document that recommendation revisions accompanied by the opposite‐sign event‐day abnormal returns are followed by significantly greater post‐event price drifts in the direction of the revision, the magnitude of the drifts increasing for longer post‐event periods. This effect is stronger for small and more volatile stocks and remains robust after accounting for additional company‐specific (size, Market Model beta, and historical volatility) and event‐specific (number of recommendation categories changed in the revision and analyst experience) factors.

Investor Inattention to All-Cash Acquisition Announcements: A Joint Day-Time Analysis in the Spanish Market

“…Reyes [23] observed a negative-positive attention asymmetry because retail investors are more attracted to negative stock market performance than to comparably positive performance. Kudryavtsev [24] analyzed the incorporation of analyst recommendation revisions on prices and confirmed the presence of investor inattention principally for low capitalization firms and more volatile stocks. Peres and Schmidt [25] showed that distracting news affects the limited attention of retail traders and determines their trading decision-making process.…”

Industry-specific stock valuation methods – a literature review

“…1.1 Analysts' use of valuation models Unsurprisingly, analyst's behavior has caught the attention of many academic studies. It is widely recognized that the stock market reacts to analysts' revisions of earnings forecasts (Givoly and Lakonishok, 1979;Stickel, 1991Stickel, , 1992Gleason and Lee, 2003;Hilary and Hsu, 2013), analysts' stock recommendations (Womack, 1996;Loh and Stulz, 2011;Bradley et al, 2014;Kudryavtsev, 2019;Berkman and Yang, 2019) and target prices (Bilinski et al, 2013;Bradshaw et al, 2013Bradshaw et al, , 2019Da et al, 2016). It is also documented that analysts' forecasts are superior to time-series models (Fried and Givoly, 1982;Brown et al, 1987a;Givoly et al, 2009;Bradshaw et al, 2012) and analysts' forecasts are often used as a proxy for market expectations in capital markets research (Fried and Givoly, 1982;Brown et al, 1987b;Hughes et al, 2008;So, 2013;Ashton and Trinh, 2018;Kim, 2018).…”