Crude Oil Price Volatility Spillovers and Agricultural Commodities: A Study in Time and Frequency Domains

2012

This study analyzes the interrelationship and volatility between grain and oil prices. Specifically, the objective of this study is to investigate the volatility transmission mechanism of grain prices with oil prices, under the assumption that an increase in crude oil prices not only affects corn and soybean prices but also other grain commodity prices such as wheat and rice. The results presented in this paper suggest several conclusions. First, there is a short-run relationship between the grain market and oil prices, which implies that recent co-movements of oil and grain prices are just a temporary phenomenon. Second, grain prices, except for rice, are affected by oil prices to some degree. Finally, the volatilities of oil prices influence the volatilities of corn and soybean prices, and vice versa.

Applied Economics and Finance

The aim of this article is to examine the interdependence relationship among the volatilities of crude oil price, U.S. dollar exchange rate, and a set of agricultural commodities prices. An autoregressive (AR) with an exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model or AR-EGARCH process and vector error correction model (VECM) approach was used on monthly data spanning from Jan 1986 to Dec 2005 as the pre-crisis period and from Jan 2006 to Nov 2015 as the post-crisis period. The results show that volatility in the agricultural commodity returns for most cases are affected by the volatility of the crude oil returns in the post-crisis period. Also, the volatility of the U.S. dollar exchange rate highly affects the agricultural commodities returns in the pre-crisis than the post-crisis periods. Furthermore, crude oil returns volatility does affect the U.S. dollar exchange rate volatility in the post-crisis period, which in turn affects the volatility...

2017

Crude Oil prices are thought to have direct and indirect effect through the exchange rate on the international agricultural commodities prices. The aim of this paper is to examine the interdependence relationship between crude oil futures prices, US dollar exchange rate, and international agricultural commodities prices, including corn (maize), sorghum, wheat, sugar, coconut oil, fishmeal, olive oil, palm oil, groundnut oil, groundnuts, rapeseed oil, soybean meal, soybean oil, soybeans, and sunflower prices. Using autoregressive (AR) model with an exponential generalized autoregressive conditional heteroskedasticity (EGARCH), namely AR-EGARCH model, we describe mean and variance equation in EGARCH model and then extract GARCH variance time series to investigate the volatility spillover from crude oil returns and US dollar exchange rate to the international agricultural commodities returns. To this end, the vector auto-regression (VAR) and vector error correction model (VECM) Granger...

Agricultural Economics (Zemědělská ekonomika), 2016

Th e paper examines the price volatility spillovers among the crude oil, soybeans, corn, wheat, and sugar futures markets over the period 1/1/2006-11/29/2013. We separately investigate the periods of the pre-crisis, the crisis, and the post-crisis in fi nancial markets. We use the Yang-Zhang estimators for the historical volatility and fi nd that there is a volatility sprawl from the crude oil to corn markets. Th ere is also bi-directional causality between the corn and soybeans markets. In addition, we observe signifi cant volatility spillovers from both the soybeans and the corn markets to the wheat markets. Th e results are also valid in a diff erent sub-period analysis.

2018

This study examines the dynamic nexus betwixt oil prices, twenty-two world agricultural commodity prices and given the evolution of the relative strength of the US dollar in a panel setting. We use panel cointegration and Panel Granger causality methods for a panel of twenty-two agricultural products based on annual observations ranging from 1980 to 2015. The empirical results provide a strong evidence of long-term relationship between Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate. Contrary to the findings of many studies in the literature that report neutrality of agricultural prices to oil price changes, we find strong support of bi-directional causal linkages among Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate. The long-run causality analysis thereby implies that the oil prices and the dollar have a predictive power to forecast the agricultural prices, which could be a good tool to prioritize the allocation of resources across indust...

Theoretical Economics Letters

The paper examines volatility transmission from crude oil market to agricultural commodities like wheat, corn, cotton and soybeans. We find that the volatility transmission from crude oil to agricultural commodities exhibits sudden changes over a study period. We also examine whether the sudden changes in volatility influence the observed sudden changes in volatility transmission from crude oil to agricultural commodities. Our results indicate the observed sudden change in volatility transmission mechanism is not influenced by sudden changes in volatility series.

2 ULYSSES project assess the literature on prices volatility of food, feed and non-food commodities. It attempt to determine the causes of markets' volatility, identifying the drivers and factors causing markets volatility. Projections for supply shocks, demand changes and climate change impacts on agricultural production are performed to assess the likelihood of more volatile markets. ULYSSES is concerned also about the impact of markets' volatility in the food supply chain in the EU and in developing countries, analysing traditional and new instruments to manage price risks. It also evaluates impacts on households in the EU and developing countries. Results will help the consortium draw policy-relevant conclusions that help the EU define market management strategies within the CAP after 2013 and inform EU's standing in the international context. The project is led by Universidad Politécnica de Madrid.

International Journal of Managerial and Financial Accounting, 2012

This paper investigates the volatility spillover and the dynamic correlation between crude oil and stock index returns. Monthly returns from January 1997 to December 2010 of the crude oil, oil-importing and oil-exporting stock indices are analysed using three multivariate GARCH specifications specifically the BEKK-GARCH model, the CCC-GARCH model and the DCC-GARCH model. Based on the BEKK-GARCH estimation results, we find strong evidence of volatility spillovers from crude oil to all oil-importing and oil-exporting stock markets. Based on the CCC model, the estimates of conditional correlations for returns across crude oil and market indexes are very low, which means the conditional shocks are correlated only in the same market. Though, the DCC estimates of the conditional correlations are always significant. This finding suggests that the assumption of constant conditional correlations is not supported empirically. The time varying correlations of crude oil and stocks returns do not differ for oil-importer or oil-exporter countries. Oil price shocks seem to have a significant impact on the relationship between oil and stock indices returns in world turmoil periods. The extent of the effect of the 2008 stock market crash on the correlation coefficients is significantly important than those of the previous financial crises.

Energy Policy, 2011

The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies.

This paper quantified the behaviour and extent of oil price and selected food commodity price volatilities using a multivariate-BEKK GARCH model to analyse the shocks and volatility transmission effect between crude oil and these commodities prices during 1990-2015. In line with the properties of time series data, a series of test such as collinearity, unit root as well as the presence of ARCH effects were conducted. The objective of this paper was to understand the most volatile commodity due to changes in world crude oil price returns and explore ways to reduce volatility relevant to food security and its stability for future planning purposes. The paper further used real price returns and demeans for normalization. Empirical results showed significant volatility transmission effects between crude oil and the all the food commodity except for dairy. Strong correlations existed between crude oil price returns and meat, cereal, edible oils and sugars. Shocks were also observed food commodity prices and its first lags.