中文摘要：

随着金融属性日益显现.碳排放交易市场呈现出与其它资本市场相类似的特征.如波动聚集。由于离散随机事件时常发生.碳排放交易市场的价格也可能出现不同程度的跳跃。准确刻画碳排放交易市场价格的跳跃特征.有利于该市场的风险管理和产品定价。考虑到欧盟碳排放交易市场发展相对比较成熟.文章选取该代表性市场作为研究对象.以期得到更具有普适性的研究结论。首先.文章选取2010年1月4日到2014年12月31日欧盟碳排放配额（EUA）现货价格的日收益率数据.构建常数跳跃强度模型.研究不同发展阶段上EUA收益率数据的跳跃行为。研究结果表明：碳排放交易市场EUA的收益率发生了异常波动.且这种异常波动的状态将会保持一段时间;在不同阶段上.EUA现货市场的跳跃呈现动态的时变性。其次.文章假设跳跃幅度具有条件动态性.分别采用ARJI-R,GARCH模型和ARJI-R,R1-1^2GARCH模型研究跳跃幅度及其方差是否对市场波动率存在敏感性。最后.文章运用ARJI-R,GARCH模型.分析跳跃幅度的方差对GARCH波动率的敏感性。实证研究发现：引入动态跳跃强度的ARJI-R,GARCH模型ARJI-R1-1^2,GARCH模型、ARJI-h2GARCH模型.均优于常数跳跃强度GAHCH模型;碳资产价格的时变跳跃特征不能忽略.其跳跃强度的持久度为0.316.即市场上此一时刻的强（或弱）跳跃在下一时刻仍然呈现强（或弱）跳跃的概率;同时.这种跳跃与整个市场的波动率、GARCH波动率之间都存在显著的敏感性.其敏感系数分别为1.635和0.378。此外.历史离散随机事件对碳排放交易市场产生的影响程度较小.敏感度仅为0.043.且事件的冲击不存在显著的持久性。鉴于此.建议我国在发展碳排放交易市场时一方面应该尽量保持相关政策的稳定性.稳步推进市场发展.减少市场本身所产生的非系统性风险;另一方面可以研发更多的碳金融产品.以?

英文摘要：

Due to the emerging financial feature, carbon emission trading market exhibits the same characteristics as the other capital markets, e.g. volatility clustering. Because discrete stochastic events frequently happen in the capital markets, the price of carbon emission trading market could appear different degrees of jumps. Precisely describing the jumps is beneficial for risk management and derivative pricing in the carbon emission trading market. Considering the maturity of European carbon emission trading market, this paper selects the typical market as the target to obtain more general results. Firstly, this paper uses the daily returns of EUA spot market from January 4, 2010 to December 31, 2014, builds the constant jump-GARCH model and studies the jumps on different phases of EUA spot market. It is found that the EUA spot market appears abnormal volatility and the dynamic time-varying jumps display on the market in both two phases. Secondly, the paper supposes that jump intensity follows conditional dynamics, and respectively analyzes the sensitivity of jump intensity and its variance to market＇s volatility using the ARJI-Rt GARCH model and the ARJI-Rt_ 12 GARCH model. Finally, it models the ARJI-ht GARCH process to test for the sensitivity of the variance of jump intensity to GARCH volatility. The empirical results show that the models of ARJI-R, GARCH, APOI-Rt_ 2 GARCH and ARJI-ht GARCH with dynamic jumps are superior to the constant jump-GARCH model on the performance of fitting. It also shows that the time-varying jumps of carbon capital＇ s prices can＇ t be neglected, and the coefficient of persistence of jump intensity is O. 316, i.e. the probability of a big or small jump in this term is followed by another big or weak jump in the next term. Meanwhile, there is significant sensitivity of jumps to market＇ s volatility and GARCH volatility, and the coefficients of sensitivity are respectively 1. 635 and 0. 378. Furthermore, there are few impacts of historical discrete events to carbon emission mar