We develop a methodology to estimate dynamic factor loadings using cross-sectional risk characteristics, which is especially useful when factor loadings significantly vary over time. In comparison, standard regression approaches assume the factor loadings are constant over a particular window. Applying the methodology to a dataset of U.S.-domiciled mutual funds we distinguish the components of...