Modelling extreme risks for carbon emission allowances — Evidence from European and Chinese carbon markets

Abstract

Modelling the dynamics of carbon emission allowance prices has been of keen interest to academicians from around the world. The distribution of tails is different from that of centres for carbon allowance prices, invalidating regular methods and conventions applied in quantitative finance. Value-at-Risk (VaR) and Expected Shortfall (ES) are traditionally useful tools to measure the extreme risk of carbon markets. On this basis, this study uses the semiparametric method to estimate the time-varying VaR and ES of European Union Allowance (EUA) and Chinese carbon emission allowance (CEA) in downside and upside events. Our results show that the GAS model outperforms the rolling estimate in describing the time-varying downside and upside VaR and ES. We find two breaks in VaR and ES for EUA whilst no break for CEA. We also find the evidence of asymmetry in CEA and reversed asymmetry in EUA, but it differs across periods and between VaR and ES. In addition, the results reveal that the downside CEA VaR and ES are significantly greater than those of EUA. Meanwhile, the relationship between upside EUA and CEA series varies across periods as well as between VaR and ES. These findings have important implications for entrepreneurs, investors, risk managers, and policy makers.