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"n general, anomaly signals exhibit positive serial correlation—stock returns follow predictable patterns prior to the publication of anomaly trading signals. For example, for the average anomaly, they found that most stocks in the anomaly portfolio in the third quarter remained in the portfolio at the end of the fourth quarter—66% of the annual portfolio’s stocks were holdovers from the portfolio at third quarter. Thus, by simply assuming persistence in accounting numbers from third to fourth quarter, a trader would make the correct portfolio assignment two thirds of the time, making it possible to trade before financial statements are released.
...for both the asset turnover and the profit margin anomalies, 85% of the stocks in the annual portfolio were holdovers from the third quarter. Thus, their prediction models performed strongly with accuracy of more than 91%. On the other hand, only 25% of the stocks in the earnings surprise anomaly portfolio at fourth quarter were also in the portfolio at third quarter. As a result, the prediction models performed poorly for this anomaly, with an accuracy rate of just 28%. (Similarly poor results were found for the revenue surprise anomaly.) predicting anomalies can still be profitable, but you need to act earlier in event time... "

https://www.morningstar.com/markets/how-find-capit...

Thanks for the link.

They show mighty good empirical evidence for what we already suspected, too:

<Investor Takeaways
These studies show how markets become more efficient over time, as information becomes faster and cheaper to access. As findings are published, anomaly returns tend to shrink, and when the anomalies are behavioral-based, they are often eliminated once trading costs are considered. In other words, the markets are becoming increasingly efficient as large databases and faster computers enable arbitragers to uncover anomalies and learn how to exploit them.>

:-)Shawn

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