Estimating Time-Varying Factor Exposures (Corrected October 2017)

We develop a methodology to estimate dynamic factor loadings using cross-sectional risk characteristics. Applying it to a dataset of US-domiciled mutual funds, we distinguish the components of active returns attributable to (1) constant factor exposures (e.g., a tilt to value stocks), (2) time-varying factor exposures, and (3) security selection. We find that large-cap growth funds tend to be concentrated in two factors (momentum and quality) whereas large-cap blend funds have the most factor diversity. We also find that common measures to gauge manager skill may be misleading.