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Predictability in commodity markets: Evidence from more than a century

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  • Hollstein, Fabian
  • Prokopczuk, Marcel
  • Tharann, Björn
  • Wese Simen, Chardin

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.

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  • Hollstein, Fabian & Prokopczuk, Marcel & Tharann, Björn & Wese Simen, Chardin, 2021. "Predictability in commodity markets: Evidence from more than a century," Journal of Commodity Markets, Elsevier, vol. 24(C).
  • Handle: RePEc:eee:jocoma:v:24:y:2021:i:c:s2405851321000052
    DOI: 10.1016/j.jcomm.2021.100171
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    Cited by:

    1. Cotter, John & Eyiah-Donkor, Emmanuel & Potì, Valerio, 2023. "Commodity futures return predictability and intertemporal asset pricing," Journal of Commodity Markets, Elsevier, vol. 31(C).
    2. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
    3. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    Commodities; Return predictability; Derivatives introduction; Business cycle; Volatility predictability;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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