Dependence between Non-Energy Commodity Sectors Using Time-Varying Extreme Value Copula Methods

Zayneb Attaf^1, , Ahmed Ghorbel¹ and Younes Boujelbène¹

¹Faculty of Economics and Management sciences, University of Sfax, Tunisia

Cite this paper:
Zayneb Attaf, Ahmed Ghorbel and Younes Boujelbène. Dependence between Non-Energy Commodity Sectors Using Time-Varying Extreme Value Copula Methods. International Journal of Econometrics and Financial Management. 2015; 3(2):64-75. doi: 10.12691/ijefm-3-2-3

Abstract

In this work, our objective is to study the intensity of dependence between six non-energy commodity sectors in a bivariate context. Our methodology is to chose, in a first step, the appropriate copula flowing Akaike criteria. In a second step, we aim to calculate the dependence coefficients (Kendall’s tau, Spearman’s rho and tail dependence) using filtered data by the AR(1)-GARCH(1.1) model to study the dependence between the extreme events. Empirical results show that dependence between non-energy commodity markets increases during volatile periods but they offer many opportunities to investors to diversify their portfolio and reduce their degree of risk aversion in bearish market periods.

Keywords:
non-energy commodity dependence structure copula diversification time-varying correlations

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