Variability of Mispricing Characteristics and Future Stock Returns

This study explores the time series variability of the Stambaugh et al. (2012) aggregate mispricing score as well as its eleven individual components. We find that the predictive power of the mispricing score for future stock returns improves significantly when the mispricing score has been more variable. In a double sort, a long-short portfolio of mispricing score in the high variability quintile earns an average monthly risk-adjusted return of three times its low variability counterpart. The eleven individual components of the score produce qualitatively similar results. Our results are economically large and statistically significant after controlling for various risk factors