Earnings Autocorrelation and the Post-Earnings-Announcement Drift – Experimental Evidence

2020
Post-earnings-announcement drift (PEAD) is one of the most solidly documented asset pricing anomalies. We use the controlled conditions of an experimental lab to investigate whether earnings autocorrelation is the driving cause of this anomaly. We observe PEAD in settings with uncorrelated and correlated earnings surprises, implying that earnings autocorrelation is not a necessary condition for PEAD. It rather is a moderator, as the PEAD is stronger when earnings surprises are serially correlated. We further show that market prices underadjust to fundamental value changes, and that trading strategies can profitably exploit the PEAD. Besides offering new results regarding the PEAD-phenomenon, we thus provide a proof-of-concept for the ability of experiments to generate valuable insights into this asset pricing anomaly.
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