Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies

ABSTRACT

The aim of this work is to study in a first step the dependence between oil and some commodity prices (cotton, rice, wheat, sucre, coffee, and silver) using copula theory, and then in a second step to determine the optimal hedging strategy for oil–commodity portfolio against the risk of negative variation in commodity markets prices. The model is implemented with an AR-GARCH model with innovations that follow t distribution for the marginal distribution and the extreme value copula for the joint distribution and parameters and dependence indices are re-estimated in each new day which allow taking into account nonlinear dependence, tails behavior, and their development over time. Various copula functions are used to model the dependence structure between oil and commodity markets. Empirical results show an increase in the dependence during the last 6 years. Volatility for commodity prices registered record levels in the same time with the increase in uncertainty. Optimal hedging ratio varies over time as a consequence of the change in the dependence structure.

KEYWORDS:

• Dependence structure
• multivariate GARCH
• Archimedean copulas
• oil–commodity portfolio
• hedging strategy
• optimal portfolio weight
• rolling estimation procedure

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Mean excess function and hill plot are two tools that are used to threshold determination.

2. For more details about Kendall's tau and Spearman's rho and their estimators, we can refer to Kendall and Stuart [47], Kruskal [53].