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我国碳交易价格波动风险预警研究——基于深圳市碳交易市场试点数据的实证检验 被引量:17

The research on early warning mechanism of fluctuation’scarbon trading prise risk in China——Based on Shenzhen carbon trading pilots
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摘要 碳排放权交易试点的深入发展,为我国碳市场的建立和碳排放权价格的制定提供了宝贵的经验,但碳交易价格波动仍存在很大风险。本文首先运用因子分析的方法确定碳交易价格风险的警兆指标,将深圳市碳排放权交易价格作为警情指标,选取2013年9月-2016年12月的深圳市碳交易的月均价格作为训练数据,构建BP人工神经网络模型;其次,利用2017年2-12月的数据作为测试数据,检验BP人工神经网络模型是否能够有效的预测碳排放权价格波动的风险。结果表明,可以通过BP人工神经网络模型对深圳市碳交易价格波动风险进行预警。 As the developments of carbon trading pilots,the establishment of the carbon market in China has been provided valuable experiences. Shenzhen is the first city to be a carbon pilot in China.Using factors analysis, this paper reveals that indicates are warning indexes about the early warming of carbon trading's price rick.The carbon trading's prices in Shenzhen are sentiment targets. Some carbon emissions monthly average prices chosen from Shenzhen Exchange,from September 2013 to December2017,are the training data to establish a warming system by BP ANN Model. In order to research on the efficiency of the BP ANN Model, Others are test data, from February 2017 to December 2017.The results show that fluctuation's carbon trading price risk can be early warned by BP ANN Model and fluctuation's carbon trading price can be predicted.There are some propositions to build an early warming mechanism of carbon trading fluctuation's prise risk in China basedon this conclusion.
出处 《价格理论与实践》 CSSCI 北大核心 2018年第10期49-52,共4页 Price:Theory & Practice
基金 河北省高等学校人文社会科学研究2018年度重点项目(SD181051)
关键词 碳交易 碳交易价格 碳价波动风险 价格预警模型 BP人工神经网络 Carbon trading Carbon trading price Carbon Price Fluctuation Risk Price Warning Model BP Artificial neural Network
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  • 1吴国华,刘清清,吴琳.碳减排潜力差异分析及目标设定[J].中国人口·资源与环境,2011,21(S2):308-312. 被引量:6
  • 2朱帮助.国际碳市场价格驱动力研究——以欧盟排放交易体系为例[J].北京理工大学学报(社会科学版),2014,16(3):22-29. 被引量:16
  • 3战雪丽,张世英.金融风险管理及其度量方法进展研究[J].西安电子科技大学学报(社会科学版),2006,16(2):23-26. 被引量:3
  • 4柏满迎,孙禄杰.三种Copula-VaR计算方法与传统VaR方法的比较[J].数量经济技术经济研究,2007,24(2):154-160. 被引量:41
  • 5Chevallier J. Detecting instability in the volatility of car- bonprices [J]. Energy Economics, 2011, 33(1): 99- 110.
  • 6Sklar A. Fonctions de repartition d n dimensions et leurs marges [J]- Publication de l'Institut de Statistique 1' Universite Paris, 1959,8 : 229- 231.
  • 7Nelson R B. An introduction to Copulas IMp. New York ~ Springer-Verlag, 1999.
  • 8Ernbrechts P,McNeil A, Straumann D. Correlation: Pi- flails and alternatives [J]. RISK, 1999,12(5)~ 11-21.
  • 9Bouy6 E , Durrleman V, Nikeghbali A, et al. Copulas for finance: A reading guide and some applications[R]. Working Paper, Financial Econometrics Research Cen- tre, City University Business School, 2000.
  • 10Roekinger M, Jondeau E. Conditional dependency of financial series: An application of copulas[~J]. Journal of Economic Dynamics and Control, 2003,27(10) :1699 -1737.

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