Commodity dynamics: A sparse multi-class approach

Luca Barbaglia, Ines Wilms and Christophe Croux

Energy Economics, 2016, vol. 60, issue C, 62-72

Abstract: The correct understanding of commodity price dynamics can bring relevant improvements in terms of policy formulation both for developing and developed countries. Agricultural, metal and energy commodity prices might depend on each other: although we expect few important effects among the total number of possible ones, some price effects among different commodities might still be substantial. Moreover, the increasing integration of the world economy suggests that these effects should be comparable for different markets. This paper introduces a sparse estimator of the Multi-class Vector AutoRegressive model to detect common price effects between a large number of commodities, for different markets or investment portfolios. In a first application, we consider agricultural, metal and energy commodities for three different markets. We show a large prevalence of effects involving metal commodities in the Chinese and Indian markets, and the existence of asymmetric price effects. In a second application, we analyze commodity prices for five different investment portfolios, and highlight the existence of important effects from energy to agricultural commodities. The relevance of biofuels is hereby confirmed. Overall, we find stronger similarities in commodity price effects among portfolios than among markets.

Keywords: Commodity prices; Multi-class estimation; Vector AutoRegressive model (search for similar items in EconPapers)
JEL-codes: C32 O13 Q02 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Working Paper: Commodity Dynamics: A Sparse Multi-class Approach (2016)
Working Paper: Commodity dynamics: a sparse multi-class approach (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:60:y:2016:i:c:p:62-72

DOI: 10.1016/j.eneco.2016.09.013

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