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<p>Understanding the co-movements and dependence between financial assets is crucial for investment decision-making and better economic policies. In this paper, I will analyze the multivariate dependence structure between commodity and equity markets. The ARMA-GARCH R-vine copula model, a flexible approach to model high-dimensional data, was employed to examine linear and tail dependencies among three principal stock markets: the SP500, MSCI China, and MSCI India, alongside four commodity indices (SP GSCI precious metals, SP GSCI industrial metals, SP GSCI energy, and SPGSCI agriculture). The findings suggest that the financialization of commodities had an impact on the increase of the correlation between commodity and stock markets. The role of agriculture and precious metals as a safe haven has been highlighted, while energy and industrial metals have a significant profit potential but are more risky. Thus, commodities cannot be viewed as a single homogeneous class, and their behavior differs depending on the sector. Finally, the efficiency of the vine copula approach has been confirmed using a risk management analysis.</p>

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Multivariate Dependence Between Stock and Commodity Markets, A Vine Approach

  • 期刊论文

  • 发表日期：

    2026年5月15日

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  • Manel Soury

摘要

Understanding the co-movements and dependence between financial assets is crucial for investment decision-making and better economic policies. In this paper, I will analyze the multivariate dependence structure between commodity and equity markets. The ARMA-GARCH R-vine copula model, a flexible approach to model high-dimensional data, was employed to examine linear and tail dependencies among three principal stock markets: the SP500, MSCI China, and MSCI India, alongside four commodity indices (SP GSCI precious metals, SP GSCI industrial metals, SP GSCI energy, and SPGSCI agriculture). The findings suggest that the financialization of commodities had an impact on the increase of the correlation between commodity and stock markets. The role of agriculture and precious metals as a safe haven has been highlighted, while energy and industrial metals have a significant profit potential but are more risky. Thus, commodities cannot be viewed as a single homogeneous class, and their behavior differs depending on the sector. Finally, the efficiency of the vine copula approach has been confirmed using a risk management analysis.