Pure Factor Portfolios and Multivariate
Regression Analysis

Abstract

Linking factor portfolio construction to cross-sectional regressions of security returns on standardized factor exposures leads to a transparent and investable perspective on factor performance. Under capitalization weighting, multivariate regression coefficients translate to portfolio returns that are benchmark relative and cleared of secondary factor exposures. The methodological contributions in this article are illustrated using a 50-year data set of 1,000 large U.S. stocks and five factor exposures: value, momentum, small size, low beta, and profitability. Using two case studies in factor portfolio analysis, the authors focus on cheapness, as measured by earnings yield, and interest rate risk, as measured by sensitivity to the 10-year Treasury bond return.