6.1 Introduction

One universal practice in any asset pricing test is to sort stocks into portfolios based on a particular attribute of the stocks. Size, estimated beta and book-to-market ratio are some of the most common attributes used in sorting stocks (see e.g. Fama and French (1992, 1993); Gibbons et al. (1989); Jagannathan and Wang (1996). There are two reasons for sorting stocks into portfolios to implement asset pricing tests: first, grouping stocks into portfolios diversifies away idiosyncratic risks of individual stocks. Second, the cross-section of individual stocks is very often larger than the number of time-series observations available. To make estimation feasible, it is necessary to group stocks into portfolios. The theoretical implication of using an attribute correlated with stocks return has been examined by Berk (2000) and Lo and MacKinlay (1990). Lo and MacKinlay (1990) point out that sorting without regard to the data generating process may lead to spurious correlation between the attributes and the estimated pricing errors. They advocate using data from a different sampling period to avoid data-snooping bias. Berk (2000) shows that sorting assets into portfolios using an attribute can lead to bias toward rejecting the model when asset pricing tests are implemented within the portfolio. Since grouping of stocks is unavoidable in an empirical context, this chapter studies whether different attributes used in sorting the same pool of stocks would lead to different asset pricing inference ^[1]. This issue is important because if different attributes used in sorting leads...