Table 1.
Copula specifications.
Table 2.
Variables used in the regression analysis.
Fig 1.
Trading hours in the US and China.
Fig 2.
Dynamics of US-Chinese agricultural futures prices.
In the figure, the solid red line represents the dynamic trend of futures prices in the US, while the blue dashed line represents the dynamic of futures prices in China. The shaded areas correspond to various crisis periods.
Table 3.
Descriptive statistics for the returns.
Table 4.
Pearson correlations of returns in the US-China pair markets.
Table 5.
Estimations of the marginal distribution models.
Table 6.
The selected optimal copula based on log-likelihood values.
Table 7.
Estimated parameters of copula model.
Fig 3.
Smoothed probabilities for the regimes of dependence between and
.
Fig 4.
Smoothed probabilities for the regimes of dependence between and
.
Fig 5.
Dynamics of dependence between and
.
The horizontal lines in the figure are static dependence parameters. For the MSTV SJC copula model, the red line indicates the upward tail dependence, and the purple line indicates the downward tail dependence. In the figure, the periods for the GFC, the US-China trade war, the COVID-19 pandemic, and the Russia-Ukraine war are shaded.
Fig 6.
Dynamics of dependence between and
.
The horizontal lines in the figure are static dependence parameters. For the MSTV SJC copula model, the red line indicates the upward tail dependence, and the purple line indicates the downward tail dependence. In the figure, the periods for the GFC, the US-China trade war, the COVID-19 pandemic, and the Russia-Ukraine war are shaded.
Table 8.
Summarization of the VaR, CoVaR, and ΔCoVaR for agricultural futures.
Fig 7.
Up ΔCoVaR from the US to Chinese agricultural futures markets.
All values of ΔCoVaR have been multiplied by a factor of 100.
Fig 8.
Up ΔCoVaR from the Chinese to US agricultural futures markets.
All values of ΔCoVaR have been multiplied by a factor of 100.
Fig 9.
Down ΔCoVaR from the US to Chinese agricultural futures markets.
All values of ΔCoVaR have been multiplied by a factor of 100.
Fig 10.
Down ΔCoVaR from the Chinese to US agricultural futures markets.
All values of ΔCoVaR have been multiplied by a factor of 100. In the figure, we remove the dynamics of the risk spillovers for corn futures because their risk spillovers are not statistically significant.
Table 9.
K-S test for the asymmetry of upside and downside risk spillovers.
Table 10.
K-S test for the asymmetry of risk spillovers from the US to China and from China to the US.
Table 11.
Descriptive statistics of the sample from January 2006 to May 2020.
Table 12.
Pearson correlations of regression variables.
Table 13.
The regression results for all samples.
Table 14.
The regression results during the GFC.
Table 15.
The regression results during the US-China trade war (only including the period before the COVID-19 pandemic).
Table 16.
The regression results during the period of the COVID-19 pandemic and the Russia-Ukraine war in 2022.