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Predictability and underreaction in industry-level returns: Evidence from commodity markets

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journal contribution
posted on 25.04.2017, 11:27 by Victor J. Valcarcel, Andrew VivianAndrew Vivian, Mark Wohar
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.

Publisher

© Elsevier

Version

AM (Accepted Manuscript)

Publisher statement

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

15/02/2017

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

ISSN

2405-8513

Language

en