The study found that in-sample tests of predictability are more reliable than out-of-sample tests in many cases. This is because in-sample tests have higher power, meaning they are better at detecting patterns in the data. The researchers ruled out data mining, model misspecification, and structural changes as reasons for this difference. Therefore, when it comes to predicting future outcomes, in-sample tests are generally more trustworthy than out-of-sample tests.