A company’s industry affiliation is commonly used to construct homogeneous stock groupings for portfolio risk management, relative valuation, and peer-group comparisons. A variety of industry classification systems have been adopted, however, creating disagreements as to companies’ industry assignments. This analysis of the Global Industry Classification System (GICS) and Fama–French system indicates that common movement in returns and operating performance resulting from industry effects is stronger for stocks of large companies than for those of small companies. Also, increasingly fine levels of disaggregation improve discrimination up to six-digit GICS codes, after which the benefits tail off. Stock groupings based on industry exhibit stronger out-of-sample homogeneity than groups formed from statistical cluster analysis.