Details
| Original language | English |
|---|---|
| Article number | 100171 |
| Journal | Journal of Commodity Markets |
| Volume | 24 |
| Early online date | 19 Jan 2021 |
| Publication status | Published - Dec 2021 |
Abstract
Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of business cycle variables for risk and return in commodity spot markets. We find that industrial production growth and inflation are the strongest predictors for future commodity returns. Several further variables help predict future commodity volatilities. The introduction of derivatives generally reduces the predictability in the most active commodity markets but increases the predictability in others. Thus, derivatives likely make markets more efficient, but also attract most of the price discovery activity. Commodity spot volatilities generally rise after futures introduction.
Keywords
- Business cycle, Commodities, Derivatives introduction, Return predictability, Volatility predictability
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Finance
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
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In: Journal of Commodity Markets, Vol. 24, 100171, 12.2021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Predictability in Commodity Markets: Evidence from More Than a Century
AU - Hollstein, Fabian
AU - Prokopczuk, Marcel
AU - Tharann, Björn
AU - Wese Simen, Chardin
N1 - Funding Information: We are grateful to two anonymous referees, Fabian B?tje, Maik Dierkes, David Florysiak, Christian Leschinski, Steffen Meyer, Jo?lle Miffre (discussant), Frederik Middelhoff (discussant), Sebastian Schr?n, and Philipp Sibbertsen as well as seminar participants at the 2017 Commodity and Energy Markets Association Annual Meeting, 2018 Swiss Society for Financial Market Research Annual Conference, and Leibniz University Hannover for helpful comments and suggestions. We thank Lasse Homann for excellent research assistance.
PY - 2021/12
Y1 - 2021/12
N2 - Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of business cycle variables for risk and return in commodity spot markets. We find that industrial production growth and inflation are the strongest predictors for future commodity returns. Several further variables help predict future commodity volatilities. The introduction of derivatives generally reduces the predictability in the most active commodity markets but increases the predictability in others. Thus, derivatives likely make markets more efficient, but also attract most of the price discovery activity. Commodity spot volatilities generally rise after futures introduction.
AB - Using more than 140 years of data, we comprehensively analyze the predictive power of a broad set of business cycle variables for risk and return in commodity spot markets. We find that industrial production growth and inflation are the strongest predictors for future commodity returns. Several further variables help predict future commodity volatilities. The introduction of derivatives generally reduces the predictability in the most active commodity markets but increases the predictability in others. Thus, derivatives likely make markets more efficient, but also attract most of the price discovery activity. Commodity spot volatilities generally rise after futures introduction.
KW - Business cycle
KW - Commodities
KW - Derivatives introduction
KW - Return predictability
KW - Volatility predictability
UR - http://www.scopus.com/inward/record.url?scp=85102418585&partnerID=8YFLogxK
U2 - 10.1016/j.jcomm.2021.100171
DO - 10.1016/j.jcomm.2021.100171
M3 - Article
VL - 24
JO - Journal of Commodity Markets
JF - Journal of Commodity Markets
SN - 2405-8513
M1 - 100171
ER -