Estimating Time-Varying Factor Exposures with Cross-Sectional Characteristics with Application to Active Mutual Fund Returns

Posted: 21 Dec 2016  

Ananth Madhavan

BlackRock, Inc.

Aleksander Sobczyk

BlackRock, Inc

Andrew Ang

BlackRock, Inc

Date Written: October 31, 2016

Abstract

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 active returns attributable to (1) constant factor exposures, for example, a tilt to value stocks; (2) time-varying factor exposures; and (3) security selection. The decomposition of active returns into these three components yields valuable insight into how managers generate excess returns. We show that there is diversity in factor concentration across managers and styles. For example, large-cap growth funds show the greatest concentration in two factors, momentum and quality, whereas large-cap blend funds have the most factor diversity. Finally, common measures to gauge manager skill may be misleading. For example, we find no evidence that active share is associated with larger active returns; rather the opposite is true across the whole sample when controlling for factors such as fund size and fees.

Suggested Citation

Madhavan, Ananth and Sobczyk, Aleksander and Ang, Andrew, Estimating Time-Varying Factor Exposures with Cross-Sectional Characteristics with Application to Active Mutual Fund Returns (October 31, 2016). Available at SSRN: https://ssrn.com/abstract=2879071

Ananth Madhavan

BlackRock, Inc. ( email )

400 Howard Street
San Francisco, CA 94105
United States

Aleksander Sobczyk

BlackRock, Inc ( email )

55 East 52nd Street
New York City, NY 10055
United States

Andrew Ang (Contact Author)

BlackRock, Inc ( email )

55 East 52nd Street
New York City, NY 10055
United States

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