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Commodity market financialization, herding and signals: An asymmetric GARCH R-vine copula approach

Xiao, Qin; Zhang, Dalu; Yan, Meilan


Dalu Zhang

Meilan Yan


Institutional investors have significantly increased their exposure to commodity futures after 2004 in the process of commodity market financialization, raising questions about the risk-sharing and
price-discovery functions of the market. We identify some symptoms of financialization through examining S&P500, JPM bond index, and 18 S&P GSCI excess return indices, employing ARMA-GARCH R-vine copula approach that can flexibly model high-dimensional multivariate asymmetric tail dependence. We discover three trends: an increased resemblance between the news impact curve of
stocks and those of commodities; an increased bi-variate stock-commodity tail dependence; and an increased multivariate tail-dependence across all commodities. We also explore the market structural change underlying these symptoms using an augmented news impact curve. We suggest and provide evidence that herding, in addiction to leverage effect, explains the observed symptoms. The findings have profound implications for commercial hedgers and financial traders, and for regulators who are concerned about the functionalities of commodity futures market.


Xiao, Q., Zhang, D., & Yan, M. (2023). Commodity market financialization, herding and signals: An asymmetric GARCH R-vine copula approach. International review of financial analysis, 89, Article 102743.

Journal Article Type Article
Acceptance Date Jun 27, 2023
Online Publication Date Jul 13, 2023
Publication Date Oct 1, 2023
Deposit Date Jun 29, 2023
Publicly Available Date Jan 14, 2025
Journal International Review of Financial Analysis
Print ISSN 1057-5219
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 89
Article Number 102743
Keywords Commodity market financialization; Herding; Asymmetric tail dependence; Risk-sharing; Information friction
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