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One Vol to Rule Them All: Common Volatility Dynamics in Factor Returns

Published online by Cambridge University Press:  14 April 2023

Nishad Kapadia
Affiliation:
Tulane University A. B. Freeman School of Business nkapadi@tulane.edu
Matthew Linn
Affiliation:
University of Massachusetts at Amherst Isenberg School of Management mlinn@isenberg.umass.edu
Bradley Paye*
Affiliation:
Virginia Tech Pamplin College of Business
*
bpaye@vt.edu (corresponding author)

Abstract

We show that a common component governs volatility dynamics across a wide range of traded equity factors. This “common factor volatility” (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. CFV allows us to characterize stochastic discount factor (SDF) volatility dynamics in a very general sense and we show that many popular models imply SDFs with time-varying volatility that correlates strongly with CFV.

Type
Research Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

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Footnotes

We are particularly grateful for the many thoughtful comments provided by an anonymous reviewer. We thank Tim Bollerslev, John Y. Campbell, Fousseni Chabi-Yo, Ing-Haw Cheng (2020 SFS Cavalcade discussant), Kim Christensen, Andrew Detzel, Gregory Kadlec, Nikunj Kapadia, Guilherme Salome, Yinan Su (2020 EFA discussant), Stijn Van Nieuwerburgh, Lai Xu (2020 FMA discussant) and conference and seminar participants at the 2019 International Workshop on Financial Econometrics, the 2020 SFS Cavalacade North America, the 2020 European Finance Association Annual Meeting, the 2020 Financial Management Association Annual Meeting, the 2019 Duke University Financial Econometrics Workshop, Binghamton University, University of Denver, Oklahoma State University, and Virginia Tech for helpful comments.

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