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.