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Dependency, centrality and dynamic networks for international commodity futures prices

Author

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  • Wu, Fei
  • Zhao, Wan-Li
  • Ji, Qiang
  • Zhang, Dayong

Abstract

This paper adopts a network approach to measure dependency among a set of international commodity futures prices. We first use partial correlations to construct a static dependency network for a vector of variables, and then illustrate within-system connections in a minimum spanning tree (MST) to evaluate the centrality of the variables. Rolling-window estimation is then applied to address time variations in both dependency and centrality networks. We show that crude oil price plays a pivotal role in connecting together components in the networks and there is clear evidence of time-varying within-system dependency. Our method demonstrates a new and easy-to-apply way to investigate dependency. The empirical results provide new evidence to the recent intensive discussions on financialisation in energy and commodity markets.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:reveco:v:67:y:2020:i:c:p:118-132
    DOI: 10.1016/j.iref.2020.01.004
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    References listed on IDEAS

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