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Understanding Dynamic Conditional Correlations between Commodities Futures Markets

Authors: Behmiri, Niaz Bashiri; Manera, Matteo; Nicolini, Marcella; Behmiri, Niaz Bashiri; Manera, Matteo; Nicolini, Marcella;

Understanding Dynamic Conditional Correlations between Commodities Futures Markets

Abstract

We estimate dynamic conditional correlations between 10 commodities futures returns in energy, metals and agriculture markets over the period 1998-2014 with a DCC-GARCH model. We look at the factors influencing those correlations, adopting a pooled mean group (PMG) estimator. Macroeconomic variables are significantly correlated with agriculture-energy and metals-energy dynamic conditional correlations; while financial variables are relevant in the agriculture-energy correlations and poorly significant in the metals-energy ones. Speculative activity is generally not statistically significant. Correlations started increasing in the years before the financial crisis and decreased at the end of our period of analysis.

Keywords

Commodities, Future Markets, Multivariate GARCH, Financial Economics, Dynamic Conditional Correlations

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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