Exogenous impacts on the links between energy and agricultural commodity markets

a r t i c l e i n f o The main purpose of this paper is to identify the effects of exogenous factors, which have been somewhat controversial , on the price links between the energy and agricultural commodity markets. Our study differs from other studies by employing multivariate normal mixture models to capture the structural properties of the price dependencies in the underlying states. This paper investigates price dependencies from both quantitative and structural perspectives. By analyzing the overall dependencies and structural heterogeneity in the empirical results, we conclude that the global financial crisis is the most influential shock on the price links between energy and agricultural commodities. Because price links are vulnerable to financial shocks, our results also suggest introducing state-based analysis to risk management and portfolio diversification across the energy and agriculture markets during times of turmoil. With the importance of agriculture prices in the economy increasing over the past decades, price links between energy and agriculture futures have attracted considerable attention from global investors (Apergis et al., 2014; Jebabli et al., 2014). A number of empirical studies document that these price links are affected by exogenous factors, such as the financialization of commodities, biofuel policies, food crises and the global financial crisis (see Baffes and Haniotis, 2010; Kristoufek et al., 2014; Nazlioglu et al., 2013). However, there is still no consensus about the consistency of energy and agricultural commodity prices. Because the possibility of multiple states plays an important role in investigating dependence among financial assets (Gray, 1996; Hamilton, 1988), considering dependence in the underlying states is a potential misconception in existing studies of energy and agriculture links. Therefore, the goal of this paper is to identify the impacts of these ex-ogenous shocks on the dependence structure of energy and agricultural commodity prices. The dependence structure here does more than describe dependencies during different critical periods; instead, it emphasizes investigating the correlations among the levels of their underlying states. To achieve this goal, we utilized multivariate normal mixture models, which have been used by Ang and Bekaert (2002), to accommodate the structure of dependence between energy and agriculture commodity prices during different sub-periods of the last decade. The main contribution of this paper consists of two parts. First, we show that a mixture of multivariate normal distributions provides the underlying structural features of the correlations, whereas other models of dependence, such as copula or …