Value versus Glamour
研究基于排序策略的交易策略如何因数据窥探而夸大公司特征与股票收益之间的关系，发现单变量排序中数据窥探可解释高达50%的样本内关系，多变量排序偏差更大。
Abstract The fragility of the CAPM has led to a resurgence of research that frequently uses trading strategies based on sorting procedures to uncover relations between firm characteristics (such as “value” or “glamour”) and equity returns. We examine the propensity of these strategies to generate statistically and economically significant profits due to our familiarity with the data. Under plausible assumptions, data snooping can account for up to 50 percent of the in‐sample relations between firm characteristics and returns uncovered using single (one‐way) sorts. The biases can be much larger if we simultaneously condition returns on two (or more) characteristics.