摘要
选取欧盟碳金融市场收益率数据作为研究对象,基于极值理论通过对数据建立区组极大值模型(BMM)和超阈值模型(POT)来拟合收益率数据的尾部。结果表明:正态分布不能很好地描述欧盟碳金融市场收益率数据特征,而基于极值理论地的BMM和POT模型可以较好地拟合数据尾部;基于正态性假定下计算的风险度量指标,在高置信水平下会低估尾部数据的风险水平;基于极值理论的模型可以更好地拟合碳金融市场收益率数据,由此得到的风险度量指标可以更好地帮助风险管理者们监控和应对风险。
This paper establisheda block maximum model(BMM) and an over-threshold model(POT)based on the extreme value theory by selecting EU carbon financial market yield dataas the research object. The results showed that the normal distribution couldn’t describe the data characteristics of the EU carbon financial market yield data well, while the BMM and POT models could fit the tail of the data wellbased on extreme value theory. Besides, it found that the risk measure calculated based on the normality assumption indicatorswould underestimate the risk level of the tail data under the high confidence level. It found that the models could better fit the carbon financial market return data based on extreme value theory, and the resulting risk metrics could better help risk managers Monitor and respond to risks.
作者
杨奕
杨爱军(指导)
YANG Yi(College of Economics and Management,Nanjing Forestry University,Nanjing 210037,China)
出处
《中国林业经济》
2020年第2期61-64,共4页
China Forestry Economics
关键词
碳金融市场
极值理论
广义极值分布
广义帕累托分布
风险管理
carbon financial markets
extreme value theory
generalized extreme value distribution
generalized Pareto distribution
risk management