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Co-movements in commodity prices: A note based on network analysis

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  • David Matesanz Gomez
  • Guillermo J. Ortega
  • Benno Torgler
  • German Dabat

Abstract

This paper analyses co-movements in a wide group of commodity prices during the time period 1992-2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co-movement of the commodity prices in our time sample, however from mid-2008 to the end of 2009 co-movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains and oilseeds) and which have increased their degree of co-movement during the sampled period. These results suggest that speculation and uncertainty are drivers of the sharp slump in commodity prices synchronization.

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  • David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler & German Dabat, 2011. "Co-movements in commodity prices: A note based on network analysis," CREMA Working Paper Series 2011-21, Center for Research in Economics, Management and the Arts (CREMA).
  • Handle: RePEc:cra:wpaper:2011-21
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    1. repec:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-017-2659-0 is not listed on IDEAS
    2. Fernández, Andrés & González, Andrés & Rodríguez, Diego, 2018. "Sharing a ride on the commodities roller coaster: Common factors in business cycles of emerging economies," Journal of International Economics, Elsevier, vol. 111(C), pages 99-121.
    3. Chen, Peng, 2015. "Global oil prices, macroeconomic fundamentals and China's commodity sector comovements," Energy Policy, Elsevier, vol. 87(C), pages 284-294.
    4. Trancoso, Tiago, 2014. "Emerging markets in the global economic network: Real(ly) decoupling?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 499-510.
    5. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
    6. Matesanz, David & Ortega, Guillermo J., 2015. "Sovereign public debt crisis in Europe. A network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 756-766.

    More about this item

    Keywords

    commodity prices; co-movement; hierarchy and topology; networks; complex systems;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)

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