Copula-based local dependence between energy, agriculture and metal commodity markets

TL;DR

This paper introduces a novel copula-based method to analyze local dependence and asymmetries in extreme co-movements among energy, agriculture, and metal markets, revealing insights for risk management.

Contribution

It develops a new copula-based local dependence measure to identify nonlinear asymmetries and tail dependencies in commodity markets.

Findings

Increased co-movements in extreme market conditions

Stronger dependence between energy and other commodities at lower tails

Asymmetric co-movements in energy-metal pairs, often negative at peaks

Abstract

This paper studies the extreme dependencies between energy, agriculture and metal commodity markets, with a focus on local co-movements, allowing the identification of asymmetries and changing trend in the degree of co-movements. More precisely, starting from a non-parametric mixture copula, we use a novel copula-based local Kendall's tau approach to measure nonlinear local dependence in regions. In all pairs of commodity indexes, we find increased co-movements in extreme situations, a stronger dependence between energy and other commodity markets at lower tails, and a 'V-type' local dependence for the energy-metal pairs. The three-dimensional Kendall's tau plot for upper tails in quantiles shows asymmetric co-movements in the energy-metal pairs, which tend to become negative at peak returns. Therefore, we show that the energy market can offer diversification solutions for risk management in the case of extreme bull market events.