Fundamental Factor Models and Macroeconomic Risks - An Orthogonal Decomposition

Multiple, often competing, characteristic factor models have been proposed to explain the cross-section of stock returns, but with limited economic interpretation of the factors. In this paper, we employ an optimal orthogonalization approach to examine the proportion of explained variation in factor returns, while retaining economic intuition. Findings indicate that a small number of dominant explanatory variables account for much of the explained variation in fundamental factor returns, but pronounced dynamics in exposure attribution are evident. Using quantile regression, we provide evidence of heterogeneous exposures of fundamental factors to macroeconomic variables at extremes of the return distribution. Our results highlight that the majority of characteristic factors proxy for macroeconomic variables, but that relationships may be more intricate than previously thought