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Short-term price volatility and reversion rate in mineral commodity markets

Author

Listed:
  • Diego García

    (Universidad Técnica Federico Santa María)

  • Juan Ignacio Guzmán

    (Pontificia Universidad Católica de Chile)

Abstract

The commodity price volatility is a critical characteristic of mineral markets, since it has planning as well as financial implications for different market participants such as governments, producers, investors, and consumers. This paper inquiries into the price volatility of mineral commodity markets by filling the gap between two main explanations available in the economic literature: the view of mineral economists, who establish that short-term price volatility arises mainly because in this time horizon supply cannot adjust to demand (which is associated with a very small speed of adjustment to market equilibrium), and the view of neoclassic microeconomic theorists, who affirm that supply adjusts instantly to demand (which is related with a high speed of adjustment to market equilibrium). We developed a conceptual model based on the current understanding of mineral economics, but where time to adjust to equilibrium plays a significant role into setting prices. Based on this, we posit that mineral commodity markets with larger reversion rates (i.e., the time necessary to achieve a long-term equilibrium price) have a smaller price volatility. By using a cross-sectional econometric model for 50 mineral commodities in the period 1900–2015, we found statistical support for an inverse relationship between short-term price volatility and reversion rates, which supports our hypothesis.

Suggested Citation

  • Diego García & Juan Ignacio Guzmán, 2020. "Short-term price volatility and reversion rate in mineral commodity markets," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 33(1), pages 217-229, July.
    • Handle: RePEc:spr:minecn:v:33:y:2020:i:1:d:10.1007_s13563-019-00190-7
    DOI: 10.1007/s13563-019-00190-7
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    References listed on IDEAS

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    1. Prokopczuk, Marcel & Symeonidis, Lazaros & Wese Simen, Chardin, 2017. "Variance risk in commodity markets," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 136-149.
    2. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    3. Boland, Lawrence A., 2017. "Equilibrium Models in Economics," OUP Catalogue, Oxford University Press, number 9780190274337, Decembrie.
    4. David S. Jacks & Kevin H. O'Rourke & Jeffrey G. Williamson, 2011. "Commodity Price Volatility and World Market Integration since 1700," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 800-813, August.
    5. Auger, Felipe & Ignacio Guzmán, Juan, 2010. "How rational are investment decisions in the copper industry?," Resources Policy, Elsevier, vol. 35(4), pages 292-300, December.
    6. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    7. Robert S. Pindyck, 2004. "Volatility and commodity price dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(11), pages 1029-1047, November.
    8. Brunetti, Celso & Gilbert, Christopher L., 1995. "Metals price volatility, 1972-1995," Resources Policy, Elsevier, vol. 21(4), pages 237-254, December.
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