Department of Economics and Management, North China Electric Power University, No. 619, Yonghua North Street, Baoding, Hebei, China.
Environ Sci Pollut Res Int. 2022 Aug;29(36):54108-54121. doi: 10.1007/s11356-022-19679-w. Epub 2022 Mar 16.
Measuring the risks of the carbon financial market is of great significance for investment decision-making, risk supervision, and the healthy development of the carbon trading market. Different from previous studies based on traditional VaR (value at risk), this study measures the integrated risk of China's carbon market based on the Copula-EVT (Extreme Value Theory) -VaR model which can explore the unique strength of the copula and EVT-VaR models, of which the copula model is applied to capture the dependence between the different risk factors of carbon price volatility and macroeconomic fluctuation, while the EVT-VaR is used to explore the risk value. The empirical results show that the traditional VaR that only considers a single risk factor from carbon price volatility is likely to overestimate the risk. In addition, compared with other methods that do not consider the interdependence between risk factors, using the copula function to measure the carbon market integration risk is more effective, and backtesting also confirms this conclusion. This paper provides a specific reference for carbon emission companies to participate in the carbon market. It provides a theoretical basis for the supervision of the risk management of the carbon market.
衡量碳金融市场风险对投资决策、风险监管和碳交易市场的健康发展具有重要意义。与以往基于传统 VaR（风险价值）的研究不同，本研究基于 Copula-EVT（极值理论）-VaR 模型对中国碳市场的综合风险进行了测量，该模型可以探索 Copula 和 EVT-VaR 模型的独特优势，其中 Copula 模型用于捕捉碳价格波动和宏观经济波动的不同风险因素之间的相关性，而 EVT-VaR 则用于探索风险价值。实证结果表明，仅考虑碳价格波动单一风险因素的传统 VaR 可能会高估风险。此外，与不考虑风险因素之间相互依存关系的其他方法相比，使用 Copula 函数来衡量碳市场综合风险更为有效，回溯测试也证实了这一结论。本文为碳排放企业参与碳市场提供了具体参考，为碳市场风险管理的监管提供了理论依据。
