Selection Bias and Pseudo Discoveries on the Constancy of Stock Return Anomalies

There are now a large and rapidly growing number of studies that test the constancy of stock return anomalies. In this study, we produce new and convincing evidence that the standard constancy test is heavily influenced by selection bias. Backed by a carefully designed Monte Carlo simulation, we show that selection bias predisposes the standard constancy test to reject the null by a factor of five to 12 times more than normally expected. Failure to recognize this bias can result in publication of the type of pseudo discoveries that Harvey (2017) warns about in his Presidential Address to the American Finance Association. We then describe the Quandt/Andrews test, a correct and unbiased test for anomalies and changes in anomalies, and apply it to test the constancy of 15 well-known stock return anomalies