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中国管理科学 ›› 2015, Vol. 23 ›› Issue (11): 12-20.doi: 10.16381/j.cnki.issn1003-207x.2015.11.002

• 论文 • 上一篇    下一篇

国际碳市场风险价值度量的新方法——基于EVT-CAViaR模型

张晨1, 丁洋1, 汪文隽2   

  1. 1. 合肥工业大学管理学院, 安徽合肥 230009;
    2. 合肥工业大学经济学院, 安徽合肥 230601
  • 收稿日期:2014-05-08 修回日期:2015-04-10 出版日期:2015-11-20 发布日期:2015-12-01
  • 作者简介:张晨(1968-),女(汉族),安徽合肥人,合肥工业大学管理院,经营决策与控制研究所所长,教授,博士生导师,研究方向:金融风险管理.
  • 基金资助:

    国家自然科学基金资助项目(71373065)

An Innovation of Estimating Value at Risk of International Carbon Market:Conditional Autoregressive Value at Risk Models with Refinements from Extreme Value Theory

ZHANG Chen1, DING Yang1, WANG Wen-jun2   

  1. 1. School of Management, Hefei University of Technology, Hefei 230009, China;
    2. School of Economics, Hefei University of Technology, Hefei 230601, China
  • Received:2014-05-08 Revised:2015-04-10 Online:2015-11-20 Published:2015-12-01

摘要: 受全球经济、政治、能源和政策等各方面因素影响,碳资产价格波动剧烈,探寻适合碳市场风险度量的计量方法具有重要的现实意义。论文以EUA和CER市场为研究对象,对比了CAViaR与GARCH-GED模型在不同预测区间、不同置信水平下度量碳市场风险时的表现,发现CAViaR模型在模型拟合和预测方面要优于GARCH-GED模型,但由于CER市场具有更大的不确定性,导致了CAViaR模型在CER市场的预测表现比EUA市场更差,并且在预测1%VaR时,CAViaR模型表现出不稳定性;论文进一步将EVT与CAViaR模型结合来改进碳市场1%VaR的预测效果,发现在处理具有高风险预测区间以及高风险的CER市场,EVT-CAViaR模型的预测表现都更加稳健,说明该方法能够一定程度上提升碳市场风险的预测精度。

关键词: 碳市场, 条件自回归分位数模型, 极值理论, 风险价值

Abstract: The price of carbon assets fluctuates heavily because of the global economy, politics, energy, and so on, thus it has been of realistic significance to have research on the risk measurement of carbon market. In this paper, EUA and CER markets are taken as the research objects, and the performance of CAViaR model and GARCH-GED model in measuring the risk of carbon markets under the different prediction intervals and confidence levels are compared, finding that:(1) CAViaR model is better than GARCH-GED model in fitting and prediction; (2) CER market has greater uncertainty relative to EUA market; (3) when predicting 1%VaR, the CAViaR model is instable. In hope of a better prediction effect, this paper takes the combination of CAViaR model and EVT is taken to predict 1%VaR, finding that the prediction of EVT-CAViaR model is more steady and reliable under the high-risk prediction intervals and the CER market, therefore a conclusion can be made that this new method promises to partly improve the prediction accuracy of the extreme risk of carbon markets.

Key words: carbon market, CAViaR, EVT, VaR

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