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What Drives Commodity Returns? Market, Sector or Idiosyncratic Factors?

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  • Jun Ma
  • Andrew Vivian
  • Mark E. Wohar

Abstract

This paper examines the relationship between 43 commodity returns using a dynamic factor model with time varying stochastic volatility. The dynamic factor model decomposes each commodity return into a common (market), sector‐specific and commodity‐specific component. It enables the variance attributed to each component to be estimated at each point in time. We find the return variation explained by the common factor has increased substantially for the recent period and is statistically significant for the vast majority of commodities since 2004 (at each point in time) This phenomenon is the strongest for non‐perishable products. We link the amount of variation explained by the common factor to economic variables.

Suggested Citation

  • Jun Ma & Andrew Vivian & Mark E. Wohar, 2020. "What Drives Commodity Returns? Market, Sector or Idiosyncratic Factors?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(2), pages 311-330, April.
    • Handle: RePEc:bla:obuest:v:82:y:2020:i:2:p:311-330
    DOI: 10.1111/obes.12334
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    Cited by:

    1. Elgammal, Mohammed M. & Ahmed, Walid M.A. & Alshami, Abdullah, 2021. "Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    2. Philip Bertram & Teresa Flock & Jun Ma & Philipp Sibbertsen, 2022. "Real Exchange Rates and Fundamentals in a new Markov‐STAR Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 356-379, April.
    3. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.

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