Zhao Yuexu, Xu Weiqi
College of Economics, Hangzhou Dianzi University, Hangzhou, 310018, China.
Heliyon. 2023 Jun 1;9(6):e16794. doi: 10.1016/j.heliyon.2023.e16794. eCollection 2023 Jun.
To accurately measure the spillover effect of China's green financial carbon emission market, a new measurement of conditional value at risk (CoVaR) based on the B-spline quantile methods is proposed. Firstly, the variable coefficient CoVaR model is constructed, and the model coefficients are estimated by the B-spline quantile method. Then, the relationship between Δconditional value at risk (ΔCoVaR) and value at risk (VaR) is considered. In the empirical analysis, we investigate five carbon trading quota risk measurements of the carbon emission projects in China from 2014 to 2022, and verify the B-spline superiority by Monte Carlo simulation. The empirical results show that B-spline method has the highest risk fitting success rate and the smallest error.
为准确测度中国绿色金融碳排放市场的溢出效应，提出一种基于B样条分位数方法的条件风险价值（CoVaR）新测度方法。首先，构建可变系数CoVaR模型，并采用B样条分位数方法估计模型系数。然后，考虑条件风险价值增量（ΔCoVaR）与风险价值（VaR）之间的关系。在实证分析中，我们考察了2014年至2022年中国碳排放项目的五种碳交易配额风险测度，并通过蒙特卡洛模拟验证了B样条方法的优越性。实证结果表明，B样条方法具有最高的风险拟合成功率和最小的误差。
