Dependency, centrality and dynamic networks for international commodity futures prices
Qiang Ji () and
Dayong Zhang ()
International Review of Economics & Finance, 2020, vol. 67, issue C, 118-132
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.
Keywords: Commodity futures prices; Crude oil; Dependency network; Financialisation; Time-varying (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:67:y:2020:i:c:p:118-132
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