This paper presents a novel, practical approach to risk management for multifactor equity investment strategies. Our approach lies in the construction of a cross-sectional risk model using the stock return betas and a small number of style factors and macro-sector indicator functions as explanatory variables in a cross-sectional regression. The model leads to a covariance structure that incorporates in an intuitive fashion both the stocks’ characteristics and good conditioning properties that lead to robust optimization problems. Various portfolio constructions are analyzed in detail, and some concrete examples are provided.