碳市场风险测度及对冲策略研究

The risk caused by the fluctuation of carbon price will reduce the enthusiasm of the participants and lead to overall lack of trading activity. Therefore, it is urgent to explore the carbon market risk measurement and hedging strategy. Based on the identification of risk sources, scientific measurement and effective avoidance, this project uses the time series data mining method to research price volatility rule, risk measurement and hedging strategy in the carbon market. First, carbon price volatility rule is predicted by using phase space reconstruction technique and support vector machine aiming at the problem of less attention to chaos of carbon market. It provides theoretical basis for further improving the accuracy of risk measurement. Second, the correlation of multiple risk factors is described by Copula function and Value at Risk is measured by nonparametric kernel estimation aiming at the problem of ignoring the multiple sources of risk in the carbon market. It makes up for the deficiency of single risk measurement theory. Third, CVaR risk hedging model based on multiple influence factors is proposed aiming at the problem of ignoring tail loss, transaction cost and risk preference in risk hedging strategy of carbon market. The optimal hedging strategy is estimated by kernel estimation, Cornish-Fisher and multivariate GARCH model. Finally, we put forward some policy suggestions to strengthen the risk management. It provides decision-making reference for realizing stable operation and healthy development of the carbon market.

碳价波动引发的风险会降低参与主体的积极性，导致交易活跃度总体不足。因此，探索碳市场风险测度及对冲策略成为当前迫切需要解决的问题。项目以风险根源识别、科学度量与有效规避为主线，采用时间序列数据挖掘方法探讨碳市场价格波动规律、多源风险测度与最优对冲策略。第一，针对较少关注碳市场混沌特性的问题，将相空间重构技术与支持向量机相结合预测价格波动规律，为进一步提高风险测度准确性提供理论依据。第二，针对忽视碳市场多重风险来源的问题，采用Copula函数刻画多源风险因子相关性并通过非参数核估计得到VaR，弥补单一风险测度理论的不足。第三，针对碳市场风险对冲策略未考虑尾部损失、交易费用和风险偏好的问题，提出基于多种因素影响的CVaR风险对冲模型并采用核估计、Cornish-Fisher展开和多元GARCH得到最优对冲策略。最后，提出以加强风险管理为目标的政策建议，为实现碳市场平稳运行与健康发展提供决策参考。

气候变化是当今最大的环境挑战之一，得到国际社会广泛关注。在全球应对气候变化日趋紧迫的形势下，碳排放权交易机制作为一种低成本减排的市场化政策工具在全球范围内被广泛运用。我国启动碳市场前景虽好，但是风险控制能力不足，制约其平稳运行与健康发展。碳价波动引发的风险会降低参与主体的积极性，导致交易活跃度总体不足。因此，探索碳市场风险测度及对冲策略成为当前迫切需要解决的问题。项目以风险根源识别、科学度量与有效规避为主线，采用时间序列数据挖掘方法探讨碳市场价格波动规律、多源风险测度与最优对冲策略。主要研究成果包括：一是针对现有研究忽视碳市场多源风险来源的问题，引入Copula函数刻画多源风险因子相关性并通过非参数核估计得到CVaR，弥补单一风险测度理论的不足。二是提出基于Cornish-Fisher展开式的半参数估计最小CVaR风险对冲策略，为碳市场参与主体提高风险控制与管理能力提供决策支持。三是采用半参数分位数回归方法实证考察北京、湖北和深圳碳排放交易试点能源价格与宏观经济因素对碳价的影响，对我国碳市场的发展与定价机制提出相关对策建议。四是通过引入模糊信息粒化工具构建碳价变化空间预测模型以弥补以往点预测方法的不足，不仅为投资者抓住套利机会提供若干重要启示，而且为决策者管理碳市场波动风险提供早期预警。五是引入复杂非线性动力学思想分析中国八个试点碳市场行为特征与运行效率，为“十四五”期间完成碳市场从“试点”走向“全国”的阶段目标提供理论依据与政策指导。项目执行期间共完成学术成果15篇，其中在《Energy Economics》等重要国际学术期刊发表6篇SSCI检索收录论文，在《中国管理科学》等国内知名学术期刊发表4篇CSSCI检索收录论文。