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Predictability Puzzles

Published online by Cambridge University Press:  24 April 2024

Bjørn Eraker
Bjørn Eraker*
Affiliation:
Wisconsin School of Business, Department of Finance
*
bjorn.eraker@wisc.edu
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Abstract

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Dynamic equilibrium models based on present value computation not only imply that returns are predictable but also generate particular short-term patterns of predictability in asset returns. I take advantage of this to construct a set of tests of equilibrium generated predictability (EGP). I apply the tests to document two puzzles: First, option-implied or realized measures of volatility ought to predict returns but do not; and second, the variance risk premium (VRP) predicts returns but only at long horizons. VRP fails the tests of EGP as the term structure of predictable variation is inconsistent with an equilibrium interpretation.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 42
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

I thank Hendrik Bessembinder (the editor) and Andrea Tamoni (the referee) for valuable comments. I also thank Andrew Chen, Mikhail Chernov, Dobrislav Dobrev, Mohammad Jahan-Parvar, Dmitriy Muravyev, Neil Pearson, Cisil Sarisoy, Ivan Shaliastovich, Sang Byung Seo, Paul Whelan, Michelle Harasimowicz, Hao Zhou, and seminar participants at the 2020 Virtual Derivatives Workshop, Tsinghua University, Federal Reserve Board of Governors, University of Wisconsin–Madison, 2017 Boston University Conference on Financial Econometrics, and 2017 Midwest Finance Association Annual Meeting for helpful comments.

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