Related Experiment Video
Updated: Sep 8, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
Published on: June 13, 2020
High-dimensional nonlinear dependence and risk spillovers analysis between China's carbon market and its major
Shaobin Zhang1, Hao Ji1, Maoxi Tian1
1College of Economics and Management, Northwest A&F University, 3 Taicheng Rd, Yangling, 712100 Shaanxi People's Republic of China.
Abstract:
In July 2021, China began its national emissions trading scheme, marking a new stage of development for the country's carbon market. This study analyzes the multidimensional correlation between carbon prices in the Guangdong pilot market and eight influencing factors from three perspectives (the international carbon market, energy prices, and China's economic situation), using the ARMA-GARCH-vine copula model. The CoVaR between the carbon price and each factor is then calculated using copula-CoVaR. The results show that the crude oil market plays the primary role in the vine structure, and that the carbon market is not strongly correlated with other markets. China's carbon market is still a regional market driven by government policy, and the international carbon and energy markets (especially the crude oil market) have upward risk spillover effects upon it. This indicates an asymmetric risk spillover between influencing factors and the carbon market. The findings of this study will help market participants prepare risk management strategies and make related investment decisions, and provide a reference for policy makers to formulate national emission trading scheme policies.
More Related Videos
Related Concept Videos
Factors Affecting Activity Coefficient
The activity coefficient value for an ion is close to one when the solution has almost zero ionic strength, i.e., when the solution shows close to ideal behavior. As the ionic strength of the solution increases from 0 to 0.1 mol/L, a...
Factorial Design
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Outliers and Influential Points
Calculating and Interpreting the Linear Correlation Coefficient
Factors Affecting Pulmonary Ventilation
Alveolar Surface Tension
The alveolar fluid lines the luminal surface of the alveoli and exerts a force called surface tension. This force is caused by the polar water molecules in the liquid being more strongly attracted to each...

