Dynamic spillovers among major energy and cereal commodity prices

Abstract

Over the past decade, the sharp increases in the prices of oil and agricultural commodities have raised serious concerns about the heightened volatility of these markets and the possible negative interactions between them. This article deals with the dynamic return and volatility spillovers across internationally traded energy and cereal commodity markets. It also examines the impacts of three types of OPEC news announcements on the volatility spillovers and persistence in these markets. For this purpose, we make use of the VAR-BEKK-GARCH and VAR-DCC-GARCH models for the daily prices of eight major commodities including WTI oil, Europe Brent oil, gasoline, heating oil #2, barley, corn, sorghum, and wheat. Our results provide evidence of significant linkages between the energy and cereal markets. Moreover, the OPEC news announcements are found to exert influence on the oil markets as well as on the oil-cereal relationships. Finally, we show that the persistence of volatility decreases (increases) for the crude oil and heating (gasoline) returns after accounting for the OPEC announcements in these multivariate GARCH models. However, the results are more mixed for the cereal markets. Overall, our results can be used to improve the risk-adjusted performance by having more diversified portfolios and also serve to hedge the oil risk more effectively.

Return Dynamics and Volatility Spillovers Between FOREX and Stock Markets in MENA Countries: What to Remember for Portfolio Choice?

“…Regarding cross-markets mean interdependencies, the results were mixed, confirm the weak-form of informational efficiency, but help predict the trend of stock market pricing behavior. This observation corroborates the observations Mensi et al [2014] using the DCC-GARCH and BEKK-GARCH class model for dynamic spillovers between international commodities markets.…”

“…We state that the current findings seem plausible, and corroborate recent empirical investigations focusing on various interdependences such as oil versus stock sectors, and stock versus commodities markets. We cite, inter alia, Arouri et al [2011ab, 2012, Chang et al [2011], Mensi et al [2013Mensi et al [ , 2014.…”

“…We make use of the VAR-GARCH model, of Ling and McAleer [2003] which has been applied by Chan et al [2005Chan et al [ , 2011 and Hammoudeh et al [2009], Arouri et al [2012], Mensi et al [2014] for miscellaneous economic topics, to explore the interdependence between various markets. The conditional mean equation and the conditional variance equation in the multivariate framework are presented separately.…”

The Halloween effect on the agricultural commodities markets

“…Much attention has been paid to the relation between the oil prices and agricultural commodities prices (Mensi et al 2014;Wang et al 2014). On the other hand, only a little attention has been paid to the Halloween effect and other seasonal patterns on commodities markets, let alone on agricultural commodities markets.…”

Dynamic and Volatility of World Agricultural Market Prices: Impacts on Importations and Food Security in WAEMU

“…The analysis of agri-food price dynamics is generally based on the classic econometric models of time series such as autoregressive vector (VAR), Structural VAR (SVAR), and error correction model (Wang, 2014;Sadrosky, 2014;Mensi et al, 2014;Jababli et al, 2014;Gross, 2017). In the last decade, new models of analysis of short and long-term relationships, and asymmetric price transmission tests between producers, processors and retailers such as Autoregressive Threshold (TAR) and Momentum Models Autoregressive Threshold (MTAR) were developed and applied (Enders & Siklos, 2001;Olemu & Ogundeji, 2010;Sun 2011;Surathkal et al, 2014, Ning & Sun, 2014Alam & Jha, 2016;Ankamah-Yeboah & Bronnmam, 2017).…”