Commodity Connectedness
30 Pages Posted: 21 Aug 2017 Last revised: 20 Mar 2023
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Commodity Connectedness
Commodity Connectedness
Date Written: August 2017
Abstract
We use variance decompositions from high-dimensional vector autoregressions to characterize connectedness in 19 key commodity return volatilities, 2011-2016. We study both static (full-sample) and dynamic (rolling-sample) connectedness. We summarize and visualize the results using tools from network analysis. The results reveal clear clustering of commodities into groups that match traditional industry groupings, but with some notable differences. The energy sector is most important in terms of sending shocks to others, and energy, industrial metals, and precious metals are themselves tightly connected.
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