Factor Modeling: The Benefits of Disentangling Cross-Sectionally for Explaining Stock Returns

More than three decades ago, Jacobs and Levy introduced in the Financial Analysts Journal the idea of disentangling returns across numerous factors via cross-sectional analysis, and examined the benefits of using the time-series of returns to disentangled factors for return forecasting. The disentangling approach has since been employed by several studies and implemented by a number of investment firms. Recently, Fama and French found that models using cross-sectional factors are better able to explain equity returns than models using time-series factors. This article revisits disentangling, critically compares the explanatory power of models that use cross-sectional factors with those that use time-series factors, and discusses the several benefits of the cross-sectional approach for investment management.