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Our mispricing measure for a stock is constructed by combining its rankings on 11 anomaly variables computed at the end of each month. The data file contains items PERMNO, YYYYMM, and MISP, where MISP is the value of the mispricing measure for stock PERMNO at the end of month YYYYMM. The first month is 196507, the beginning of the sample period used in Stambaugh, Yu, and Yuan (2015). 1 For each anomaly, we assign a rank to each stock that reflects the sorting on that given anomaly variable, where the highest rank is assigned to the value of the anomaly variable associated with the lowest average abnormal return, as reported in the literature. For example, one documented anomaly is that high asset growth in the previous year is followed by a low return (Cooper, Gulen, and Schill (2008)). We therefore rank firms each month by asset growth, and those with the highest growth receive the highest rank. The higher the rank, the greater the relative degree of overpricing according to the given anomaly variable. A stock’s mispricing measure (MISP), ranging between 0 and 100, is the arithmetic average of its ranking percentile for each of the 11 anomalies. According to this measure, the stocks with the highest values of MISP are the most “overpriced,” and those with the lowest values are the most “underpriced.” Below we detail the construction of the 11 anomaly variables used to construct a stock’s composite mispricing measure. We exclude stocks with share prices less than $5, primarily to avoid micro-structure effects, and we use ordinary common shares (CRSP codes 10 and 11). When constructing a stock’s mispricing measure at …