Using a sample of 97 stock return anomalies, we find that anomaly returns are 50% higher on corporate news days and are 6 times higher on earnings announcement days. These results could be explained by dynamic risk, mispricing via biased expectations, and data mining. We develop and conduct unique tests to differentiate between these three frameworks. Our results are most consistent with the idea that anomaly returns are the result of biased expectations, which are at least partially corrected upon news arrival.
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