Estimating Time-Varying Factor Exposures (Corrected October 2017)

Andrew Ang, Ananth Madhavan and Aleksander Sobczyk

Financial Analysts Journal, 2017, vol. 73, issue 4, 41-54

Abstract: 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. Disclosure: The views expressed in this article are those of the authors and do not necessarily reflect the views of BlackRock, Inc. Editor’s Note The original version had an error in Equation 5 and Note 5, which have been corrected in this version.This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Jason Hsu and Timothy Loughran, CFA, were the reviewers for this article. Submitted 2 December 2016 Accepted 28 April 2017 by Stephen J. Brown Disclaimer:This material is not intended to be relied upon as a forecast, research, or investment advice and is not a recommendation, offer, or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed are those of the authors and may change as subsequent conditions vary. Individual portfolio managers for BlackRock may have opinions and/or make investment decisions that, in certain respects, may not be consistent with the information contained in this document. Past performance is no guarantee of future results. Indexes are unmanaged and one cannot invest directly in an index.

Date: 2017
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DOI: 10.2469/faj.v73.n4.6

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