An empirical analysis of the correlation between large daily changes in grain and oil futures prices

Fretheim, Torun

doi:10.1016/j.jcomm.2018.07.002

Cited by 3 publications

(1 citation statement)

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“…Paris (2018) used a nonlinear framework to prove the long-term eff ect of oil prices on agricultural commodity prices. Fretheim (2019) provided evidence of a comovement between crude oil price changes and grain prices after 2006. Dahl et al (2020) found that the correlation between crude oil and agricultural prices increased during fi nancial and economic turmoil periods.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Comovement Between China's Commodity Futures and World Crude Oil Prices

Zhang,

Zeng,

2023

Prague Economic Papers

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We examine the comovement between China's commodity futures and world crude oil prices based on their daily return series. Using a dynamic time-varying approach, we combine the generalized autoregressive score (GAS) model with the copula approach, allowing for asymmetry and tail dependence. Our results demonstrate a significant nonlinear causal impact of world crude oil prices on each of China's commodities. The comovement between China's commodity futures and crude oil prices is positive, with varying degrees of significance across different commodity types. Notably, non-ferrous metal and chemical commodity futures are more vulnerable to rising crude oil prices. From a dynamic perspective, we observe continued volatility in the comovement between China's commodity futures and world crude oil prices in recent years. Moreover, the time-varying dependence between the three non-ferrous metals and crude oil prices is higher than that of other commodities. These findings hold significant implications for global investors, risk managers and policymakers.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of Comovement Between China's Commodity Futures and World Crude Oil Prices

Zhang,

Zeng,

2023

Prague Economic Papers

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A high-dimensional attribute reduction method modeling and evaluation based on green economy data: evidence from 15 sub-provincial cities in China

Liu

et al. 2019

Soft Comput

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Common factors and the dynamics of cereal prices. A forecasting perspective

Kwas

Paccagnini

Rubaszek

2022

Journal of Commodity Markets

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This article investigates what determines the price dynamics of the main cereals: barley, maize, rice and wheat. Using an extensive dataset of monthly time series covering the years 1980 -2019, we extract four different common factors explaining the dynamics of commodity prices, exchange rates, financial and macroeconomic indicators. Next, we examine whether these factors are useful in explaining the movements of cereal prices. We show that models incorporating all four factors outperform significantly the naive random walk model in out-of-sample forecasting competition, especially for longer horizons. However, they have only marginally better performance than a simpler model based on the commodity factor alone.

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An empirical analysis of the correlation between large daily changes in grain and oil futures prices

Cited by 3 publications

References 22 publications

Analysis of Comovement Between China's Commodity Futures and World Crude Oil Prices

Analysis of Comovement Between China's Commodity Futures and World Crude Oil Prices

A high-dimensional attribute reduction method modeling and evaluation based on green economy data: evidence from 15 sub-provincial cities in China

Common factors and the dynamics of cereal prices. A forecasting perspective

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