| 基于三状态Markov模型的欧盟碳排放交易市场的状态转换结构研究 |
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| 引用本文： | 胡根华,吴恒煜.基于三状态Markov模型的欧盟碳排放交易市场的状态转换结构研究[J].软科学,2017(2):136-140. |
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| 作者姓名： | 胡根华 吴恒煜 |
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| 作者单位： | 1. 安徽工业大学商学院;安徽创新驱动与产业转型升级发展研究中心,安徽马鞍山243032;2. 暨南大学管理学院,广州,510632 |
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| 基金项目： | 国家自然科学基金重大项目、面上项目(91218301、71171168)，教育部人文社会科学研究青年基金项目(16YJC790030)，教育部人文社会科学研究西部和边疆地区项目(14XJA790002)，安徽省自然科学基金项目(1708085QG163)，安徽工业大学人才项目(DT16100008) |
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| 摘 要： | 采用EUA现货与期货价格、CER期货价格日数据,结合AR-GARCH与Markov机制转换模型,研究碳排放市场的波动聚集与结构转换特征.结果发现:(1)市场存在尖峰厚尾与波动聚集,且存在较大的尾部风险;(2)市场呈现明显的状态转换结构特征,其中EUA现货与期货市场的结构变化较大且在较长时期内处于下跌状态;(3)市场在上涨、盘整和下跌状态下的期望持续期均大约为5天.此外,从盘整状态和下跌状态到上涨状态的转换概率比较小,市场将会在较长时间内处于某一状态下.
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| 关 键 词： | 碳排放配额 核证减排量 状态转换 Markov机制转换模型 |
State Switching Structure of European Union Carbon Emission Trading Market Based on Three-State Markov Model |
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| HU Gen-hua,WU Heng-yu.State Switching Structure of European Union Carbon Emission Trading Market Based on Three-State Markov Model[J].Soft Science,2017(2):136-140. |
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| Authors: | HU Gen-hua WU Heng-yu |
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| Abstract: | This paper applied AR-GARCH model to study volatility clustering and proposed a Markov regime switching model to capture structural switches,based on the data of EUA spot prices,EUA futures'prices and CER futures'prices.Result showed that:Firstly,lepkurtosis,heavy tails and volatility clustering existed in the carbon emission trading markets,indicated that the tailed risks happened in the markets with a large probability.Secondly,the Markov regime switching model captured the threshold of different stages of the carbon emission trading markets,and identified a large change of the structures of EUA spot and futures markets and being the fall state in a long time.Besides,the expected durations of the states of the rise,the consolidation and the fall were five days.Additionally,the transition probabilities were small from the states of the consolidation and the fall to the rise,and the markets were in one of the three states for a long time. |
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| Keywords: | carbon emission allowance certified emission reduction state switching Markov regime-switching model |
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