The scheme of simultaneously testing many profitable strategies may conceal the hazard of data-snooping bias. However, certain portfolio returns are also more likely to exhibit codependency because of their same investment styles. Aiming at the phenomena of stock return anomalies, we consider two multiple testing approaches: one ignores the classification of portfolios and the other utilizes such information. The results based on grouped multiple testing suggest that the implied adjusted critical values for t-statistics may vary across investment styles, and several statistically significant portfolios may be unidentified under the pooled setup.

中文翻译：

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投资风格与横截面股票收益可预测性的多重检验

同时测试许多有利可图的策略的方案可能会掩盖数据窥探偏见的危险。然而，某些投资组合的回报也更可能表现出相互依赖，因为它们的投资风格相同。针对股票收益异常现象，我们考虑了两种多重测试方法：一种忽略投资组合的分类，另一种利用此类信息。基于分组多重检验的结果表明，t统计量的隐含调整临界值可能因投资风格而异，并且在合并设置下可能无法识别几个具有统计意义的投资组合。