The fluctuation characteristics of the correlations between China and the US agricultural futures markets have attracted extensive attention from academic circles and government departments. As the main factor that affects the agricultural futures price, the impact of international crude oil futures price on the correlations of the Sino-US agricultural futures markets is also worth discussing. Therefore, this paper adopts the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal detrended partial cross-correlation analysis (MF-DPXA) to explore the fluctuation characteristics of cross-correlations for China and the US agricultural futures markets before and after removing the West Texas Intermediate (WTI) crude oil futures price as well as the impact on the cross-correlations. The results show that the fluctuation characteristics of the cross-correlations and partial cross-correlations between the corresponding varieties of China and the US agricultural futures markets as well as among the varieties within the markets are multifractal. The cross-correlation behaviors and the cross-market risks are all affected to varying degrees by the West Texas Intermediate (WTI) crude oil futures. The West Texas Intermediate (WTI) crude oil futures weaken the cross-market risk of the Sino-US soybean futures, while strengthening the cross-market risk of the Sino-US corn and wheat futures. In addition, the impact of the West Texas Intermediate (WTI) crude oil futures on the cross-market risks among China agricultural futures is greater than those among the US corresponding agricultural futures.

This paper investigates the fluctuation characteristics and asymmetry of cross-correlations between economic policy uncertainty (EPU) and agricultural futures prices in China and the US by using the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA). We find that the multifractal cross-correlations exist between EPU and agricultural futures prices, and the cross-correlations are anti-persistent and asymmetric. The anti-persistent cross-correlations in China are all stronger than those in the US. The multifractal degree of cross-correlation between EPU and soybean futures price is lower in China than in the US, while the multifractal degree of cross-correlation between EPU and soybean meal, soybean oil or corn futures price is higher in China than in the US. Moreover, China’s soybean futures price is more susceptible to the upward and downward trends in China’s EPU, while the US soybean meal, soybean oil, and corn futures prices are more susceptible to them in the US EPU.

Agricultural commodity futures are the earliest listed futures in the world. The rapid development of their markets has greatly affected the world agricultural production and circulation. Thereby, the volatility characteristics of agricultural futures markets and the cross-correlations between the futures and spot markets have attracted extensive attention from investors, regulators and researchers. Two new fractal statistical methods are firstly developed in this paper. Then, from the perspective of system theory, some multifractal analysis methods, including the two newly developed methods, are used to study the autocorrelation, cross-correlation and coupling correlation for the return series of five agricultural futures and their corresponding spot varieties in CBOT. The empirical results show that the autocorrelations and cross-correlations of both the futures and spot systems are multifractal and present different dynamic fluctuation characteristics at different time scales. The long-term co-movement between the two systems is not strong and the overall risk spillover effect is not obvious. In addition, the coupling cross-correlations are found between the corresponding components, but the strengths are distinct due to the different influences of long-range correlations and fat-tailed distributions.

This paper investigates China’s grain trade potential and the influencing factors with RCEP partner countries by using the stochastic frontier gravity and trade inefficiency models and explores the impact of the RCEP negotiations on grain trade cooperation between China and RCEP partner countries. The research results verify that the institutional distance, economic distance, and tariff level hinder the grain trade efficiency between China and RCEP partner countries, where the tariff level has the smallest resistance. The transportation and communication infrastructure level can significantly improve the grain trade efficiency, but the transportation infrastructure level has a greater stimulative effect. China’s grain trade potential with RCEP partner countries is enormous, and there is evident heterogeneity in the grain trade potential of different countries. The grain trade relations between China and RCEP partner countries have been improved after the RCEP negotiations. However, there are still greater trade potential and expansion space for New Zealand and Laos. Therefore, some policy suggestions are put forward, such as establishing the risk assessment and early warning system, implementing the tariff reduction measures in the agreement, and developing grain trade cooperation according to local conditions, which provides practical guidance for expanding the grain trade scale.

This paper investigates the presence and asymmetry of cross-correlations between agricultural futures markets in China and the US as well as the impact of price support policies and public emergencies (Sino–US trade conflict and COVID-19 pandemic) on the cross-correlations by the multifractal methods. The results show that the fluctuation characteristics and conduction directions of cross-correlations are asymmetric. The price fluctuations of soybean and corn futures in China are easier to be affected by the US soybean and corn futures. We find that the cross-correlations are multifractal under different price support policies and pubic emergencies. The price support policies with greater interventions on soybean and corn prices have aggravated the complexity of cross-correlations between the two futures markets in China and the US. The soybean and corn futures in China are hardly correlated to the US futures under the dual effect of the Sino–US trade conflict and the COVID-19 pandemic. The Sino–US trade conflict strengthens the complexity of cross-correlation for soybean futures and weakens it for corn futures, while the COVID-19 pandemic enhances the complexity of cross-correlations for soybean and corn futures. In addition, the fat-tailed probability distributions in different price support policy and public emergency periods have a dominant influence on the multifractality of cross-correlations.