Using EGARCH models to predict volatility in unconsolidated financial markets: the case of European carbon allowances.

IF 1.9 Q3 ENVIRONMENTAL SCIENCES
Elena Villar-Rubio, María-Dolores Huete-Morales, Federico Galán-Valdivieso
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Abstract

The growing interest and direct impact of carbon trading in the economy have drawn an increasing attention to the evolution of the price of CO2 allowances (European Union Allowances, EUAs) under the European Union Emissions Trading Scheme (EU ETS). As a novel financial market, the dynamic analysis of its volatility is essential for policymakers to assess market efficiency and for investors to carry out an adequate risk management on carbon emission rights. In this research, the main autoregressive conditional heteroskedasticity (ARCH) models were applied to evaluate and analyze the volatility of daily data of the European carbon future prices, focusing on the last finished phase of market operations (phase III, 2013-2020), which is structurally and significantly different from previous phases. Some empirical findings derive from the results obtained. First, the EGARCH (1,1) model exhibits a superior ability to describe the price volatility even using fewer parameters, partly because it allows to collect the sign of the changes produced over time. In this model, the Akaike information criterion (AIC) is lower than ARCH (4) and GARCH (1,1) models, and all its coefficients are significative (p < 0.02). Second, a sustained increase in prices is detected at the end of phase III, which makes it possible to foresee a stabilization path with higher prices for the first years of phase IV. These changes will motivate both companies and individual energy investors to be proactive in making decisions about the risk management on carbon allowances.

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使用EGARCH模型预测未合并金融市场的波动性:以欧洲碳配额为例。
碳交易在经济中日益增长的兴趣和直接影响,使人们越来越关注欧盟排放交易计划(EU ETS)下二氧化碳配额(欧盟配额,EUA)价格的演变。作为一个新兴的金融市场,对其波动性的动态分析对于决策者评估市场效率和投资者对碳排放权进行充分的风险管理至关重要。在本研究中,主要的自回归条件异方差(ARCH)模型被应用于评估和分析欧洲碳期货价格每日数据的波动性,重点关注市场操作的最后一个完成阶段(第三阶段,2013-2020),该阶段在结构上与前几阶段有显著差异。一些经验发现来源于所获得的结果。首先,即使使用较少的参数,EGARCH(1,1)模型也显示出描述价格波动的优越能力,部分原因是它可以收集随时间变化的迹象。在该模型中,Akaike信息准则(AIC)低于ARCH(4)和GARCH(1,1)模型,并且其所有系数都是有意义的(p
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来源期刊
CiteScore
3.60
自引率
9.50%
发文量
75
期刊介绍: The Journal of Environmental Studies and Sciences is the official publication for the Association for Environmental?Studies and Sciences?(AESS). Interdisciplinary environmental studies require an integration of many different scientific and professional disciplines. The AESS and the Journal provide fora for the advancement of interdisciplinary approaches to the study of the coupled human-nature systems. A major goal of AESS is to encourage this advancement by promoting related teaching research and service and by facilitating communication across boundaries that may inhibit environmental discourse across traditional academic disciplines—for example between and among the physical biological social sciences the humanities and environmental professions. This commitment also involves supporting the professional development of Association members and advancing the educational status of Environmental Studies and Sciences programs. The Journal provides a peer-reviewed academically rigorous and professionally recognized venue for the publication of explicitly interdisciplinary environmental research policy analysis and advocacy educational discourse and other related matters. Contributions are welcome from any discipline or combination of disciplines any vocation or professional affiliation any national ethnic or cultural background. Articles may relate to any historical and global setting. These contributions should explicitly involve multi-disciplinary or trans-disciplinary aspects of environmental issues; and identify the way(s) in which the work will contribute to environmental research policy making advocacy education or related activities.
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