This paper finds significant evidence that commodity log price changes can predict industry-level returns for horizons of up to six trading weeks (30 days). We find that for the 1985-2010 period, 40 out of 49 U.S. industries can be predicted by at least one commodity. Our findings are consistent with Hong and Stein’s (1999) “underreaction hypothesis.” Unlike prior literature, we pinpoint the length of underreaction by employing daily data. We provide a comprehensive examination of the return linkages among 25 commodities and 49 industries. This provides a more detailed investigation of underreaction and investor inattention hypotheses than most related literature. Finally, we implement data-mining robust methods to assess the statistical significance of industry returns reactions to commodity log price changes, with precious metals (such as gold) featuring most prominently. While our results indicate modest out-of-sample forecast ability, they confirm evidence that commodity data can predict equity returns more than four trading weeks ahead.
History
School
Business and Economics
Department
Business
Published in
Journal of Commodity Markets
Volume
6
Pages
I - I5
Citation
VALCARCEL, V.J., VIVIAN, A.J. and WOHAR, M.E., 2017. Predictability and Underreaction in Industry-Level Returns: Evidence from Commodity Markets. Journal of Commodity Markets, 6, pp. 1-15.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2017-02-15
Publication date
2017-02-17
Copyright date
2017
Notes
This paper was accepted for publication in the journal Journal of Commodity Markets and the definitive published version is available at http://dx.doi.org/10.1016/j.jcomm.2017.02.003