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中文摘要：
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。
英文摘要：
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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