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

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 wit...

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Main Authors:	Victor J. Valcarcel, Andrew Vivian, Mark Wohar
Format:	Default Article
Published:	2017
Subjects:	Other commerce, management, tourism and services not elsewhere classified Asset pricing Commodity markets Equity markets Industry-level returns Information and market efficiency Predictability Out-of-sample forecast ability Underreaction Business and Management not elsewhere classified
Online Access:	https://hdl.handle.net/2134/24796
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id	rr-article-9504290
record_format	Figshare
spelling	rr-article-95042902017-02-17T00:00:00Z Predictability and underreaction in industry-level returns: Evidence from commodity markets Victor J. Valcarcel (7199774) Andrew Vivian (1254615) Mark Wohar (1248486) Other commerce, management, tourism and services not elsewhere classified Asset pricing Commodity markets Equity markets Industry-level returns Information and market efficiency Predictability Out-of-sample forecast ability Underreaction Business and Management not elsewhere classified 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. 2017-02-17T00:00:00Z Text Journal contribution 2134/24796 https://figshare.com/articles/journal_contribution/Predictability_and_underreaction_in_industry-level_returns_Evidence_from_commodity_markets/9504290 CC BY-NC-ND 4.0
institution	Loughborough University
collection	Figshare
topic	Other commerce, management, tourism and services not elsewhere classified Asset pricing Commodity markets Equity markets Industry-level returns Information and market efficiency Predictability Out-of-sample forecast ability Underreaction Business and Management not elsewhere classified
spellingShingle	Other commerce, management, tourism and services not elsewhere classified Asset pricing Commodity markets Equity markets Industry-level returns Information and market efficiency Predictability Out-of-sample forecast ability Underreaction Business and Management not elsewhere classified Victor J. Valcarcel Andrew Vivian Mark Wohar Predictability and underreaction in industry-level returns: Evidence from commodity markets
description	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.
format	Default Article
author	Victor J. Valcarcel Andrew Vivian Mark Wohar
author_facet	Victor J. Valcarcel Andrew Vivian Mark Wohar
author_sort	Victor J. Valcarcel (7199774)
title	Predictability and underreaction in industry-level returns: Evidence from commodity markets
title_short	Predictability and underreaction in industry-level returns: Evidence from commodity markets
title_full	Predictability and underreaction in industry-level returns: Evidence from commodity markets
title_fullStr	Predictability and underreaction in industry-level returns: Evidence from commodity markets
title_full_unstemmed	Predictability and underreaction in industry-level returns: Evidence from commodity markets
title_sort	predictability and underreaction in industry-level returns: evidence from commodity markets
publishDate	2017
url	https://hdl.handle.net/2134/24796
_version_	1797465015992713216

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

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