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Commodity price excess co-movement from a historical perspective: 1900–2010

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  • Fernandez, Viviana

Abstract

Pindyck and Rotemberg (1990)'s excess co-movement hypothesis states that commodity prices move together beyond what fundamentals can explain, reflecting possibly traders' herding or liquidity constraints. We test for price excess co-movement in 12 commodities — 11 non-energy ones and oil — spanning over a hundred years: 1900–2010. To this end, we approximate commodity demand/supply factors by their apparent consumption. We carry out several tests and find some evidence in favor of excess co-movement, but its nature appears to be time-dependent. In particular, we conclude that excess co-movement with oil is generally present, particularly in the industrial metal class. We also explore the interdependence between portfolio investment decisions and excess co-movement for three unrelated assets: cotton, copper, and petroleum. Based on Conditional Value-at-Risk (CVaR) optimization, we found some correlations between the two, when short sales are excluded, during 1971, 1999–2004, and 2008.

Suggested Citation

  • Fernandez, Viviana, 2015. "Commodity price excess co-movement from a historical perspective: 1900–2010," Energy Economics, Elsevier, vol. 49(C), pages 698-710.
  • Handle: RePEc:eee:eneeco:v:49:y:2015:i:c:p:698-710
    DOI: 10.1016/j.eneco.2015.04.003
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    Cited by:

    1. Neil A. Wilmot, 2019. "Heavy Metals: Might as Well Jump," IJFS, MDPI, vol. 7(2), pages 1-14, June.
    2. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.
    3. Zhang, Tianding & Du, Tianwen & Li, Jie, 2020. "The impact of China's macroeconomic determinants on commodity prices," Finance Research Letters, Elsevier, vol. 36(C).
    4. Wu, Fei & Zhao, Wan-Li & Ji, Qiang & Zhang, Dayong, 2020. "Dependency, centrality and dynamic networks for international commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 118-132.
    5. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    6. Awaworyi-Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2022. "Breaks, trends and correlations in commodity prices in the very long-run," Energy Economics, Elsevier, vol. 108(C).
    7. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).

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    More about this item

    Keywords

    Real commodity prices; Excess co-movement; Portfolio investment decisions;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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